diff --git a/docker-compose.docs-snapshots.yml b/docker-compose.docs-snapshots.yml
index 5903f3bb2..3ad278390 100644
--- a/docker-compose.docs-snapshots.yml
+++ b/docker-compose.docs-snapshots.yml
@@ -8,15 +8,17 @@ services:
       [
         'sh',
         '-c',
-        'node extract.cjs --directory /extract/plotly-express --output /results/plotly-express; node extract.cjs --directory /extract/ui --output /results/ui',
+        'node extract.cjs --directory /extract/plotly-express --output /results/plotly-express; node extract.cjs --directory /extract/ui --output /results/ui; node extract.cjs --directory /extract/tradingview-lightweight --output /results/tradingview-lightweight',
       ]
     volumes:
       - ./plugins/ui/docs:/extract/ui
       - ./plugins/plotly-express/docs:/extract/plotly-express
+      - ./plugins/tradingview-lightweight/docs:/extract/tradingview-lightweight
       # exclude doc build directories by overriding with empty volumes
       # We could extract from the build directories, but we need to output the snapshots to the build directory itself for Salmon to pick up...
       - /extract/plotly-express/build/
       - /extract/ui/build/
+      - /extract/tradingview-lightweight/build/
       - test-sets:/results
 
   # Read the test sets from the results directory and run them against the test server, taking a snapshot of the results.
@@ -33,7 +35,7 @@ services:
       [
         'sh',
         '-c',
-        'node snapshot.cjs --directory /test-sets/plotly-express --output /results/plotly-express --errors /errors/plotly-express; node snapshot.cjs --directory /test-sets/ui --output /results/ui --errors /errors/ui',
+        'node snapshot.cjs --directory /test-sets/plotly-express --output /results/plotly-express --errors /errors/plotly-express; node snapshot.cjs --directory /test-sets/ui --output /results/ui --errors /errors/ui; node snapshot.cjs --directory /test-sets/tradingview-lightweight --output /results/tradingview-lightweight --errors /errors/tradingview-lightweight',
       ]
     volumes:
       - /var/run/docker.sock:/var/run/docker.sock # Allows the snapshotter to start its own docker containers for the test server
@@ -42,8 +44,110 @@ services:
       # Map all the results back to the snapshots directory for those docs
       - ./plugins/ui/docs/snapshots:/results/ui
       - ./plugins/plotly-express/docs/snapshots:/results/plotly-express
+      - ./plugins/tradingview-lightweight/docs/snapshots:/results/tradingview-lightweight
       - ./snapshot-results/errors:/errors
 
+  # Pass 2: capture widget PNGs for the tradingview-lightweight docs. Runs
+  # AFTER salmon's Pass 1 snapshotter has finished and torn its server down.
+  # Brings up its own python-snapshotter compose via the mounted docker
+  # socket so it can join the shared snapshot network. The image-snapshotter
+  # tool itself is plugin-agnostic; per-plugin settings come from
+  # SNAPSHOTTER_* env vars below.
+  deephaven-plugins-docs-image-snapshotter-tvl:
+    build:
+      context: ./tools/image-snapshotter
+    container_name: deephaven-plugins-docs-image-snapshotter-tvl
+    depends_on:
+      deephaven-plugins-docs-snapshotter:
+        condition: service_completed_successfully
+    environment:
+      SNAPSHOTTER_BASE_URL: 'http://server:10000/ide/'
+      SNAPSHOTTER_PLUGIN_ROOT: '/work'
+      SNAPSHOTTER_PLUGIN: 'tradingview-lightweight'
+      SNAPSHOTTER_TARGET_SELECTOR: '.dh-tvl-chart'
+      SNAPSHOTTER_WIDGET_TYPE: 'deephaven.plot.tradingview_lightweight.TvlChart'
+      SNAPSHOTTER_APP_ID: 'tvl.docs.examples'
+      SNAPSHOTTER_APP_NAME: 'TVL Docs Examples'
+      SNAPSHOTTER_COMPOSE_FILE: '/workspace/docker/python-snapshotter/docker-compose.yml'
+      SNAPSHOTTER_SERVER_CONTAINER: 'tvl-snapshotter-server'
+      # Pass through the host's SNAPSHOTTER_FORCE so callers can opt in to
+      # cache-busting recapture without editing this file.
+      SNAPSHOTTER_FORCE: ${SNAPSHOTTER_FORCE:-}
+      CI: 'true'
+      # The Pass 2 entrypoint brings up the python-snapshotter test server
+      # via the mounted docker socket. That compose file bind-mounts the
+      # generated app.d, which is interpreted against the HOST filesystem
+      # (the socket is the host's). `${PWD}` is evaluated by compose at
+      # compose-up time against the user's shell, so HOST_PWD inside the
+      # container always carries the host's working directory.
+      HOST_PWD: ${PWD}
+    volumes:
+      # Allows the snapshotter to start its own server container alongside us.
+      - /var/run/docker.sock:/var/run/docker.sock
+      # docker/python-snapshotter/docker-compose.yml is resolved from the
+      # host's view of the socket — mount the repo at a stable path inside
+      # the container so SNAPSHOTTER_COMPOSE_FILE resolves correctly.
+      - ${PWD}:/workspace
+      # The spec walks docs/*.md (read-only) and writes PNGs + JSON envelopes
+      # into docs/snapshots. PLUGIN_ROOT resolves to /work, so /work/docs is
+      # the docs tree and /work/docs/snapshots is the output dir.
+      - ./plugins/tradingview-lightweight/docs:/work/docs:ro
+      - ./plugins/tradingview-lightweight/docs/snapshots:/work/docs/snapshots
+
+  # Surface snapshot errors to the user. Compose's `depends_on` conditions
+  # only fire on success (`service_completed_successfully`); there's no
+  # "completed-with-any-exit" condition. And dependency stdout doesn't
+  # stream to the terminal when you `docker compose run <target>` — only
+  # the target's own stdout does. So the salmon snapshotter's errors were
+  # silently written to /errors and never shown.
+  #
+  # Workaround: this service has no depends_on. The npm `update-doc-snapshots`
+  # script invokes it as its own `compose run` target right after the main
+  # chain — so its stdout streams to the user, regardless of whether the
+  # snapshotter passed or failed. Bind-mounts the same errors dir the
+  # snapshotter writes to. Exits non-zero if any errors are present.
+  # Also acts as the post-run chown step. The salmon snapshotter and the
+  # Pass-2 image-snapshotter both run as root, so the PNGs + JSON envelopes
+  # they write into docs/snapshots land owned by root and the host user
+  # can't edit them. Bind-mounting those dirs here (rw) and chowning them
+  # to SNAPSHOT_UID:SNAPSHOT_GID (exported by tools/run_docker.sh) makes
+  # them editable on the host. Runs whether or not snapshots succeeded.
+  deephaven-plugins-docs-error-reporter:
+    image: alpine:3.20
+    environment:
+      SNAPSHOT_UID: ${SNAPSHOT_UID:-0}
+      SNAPSHOT_GID: ${SNAPSHOT_GID:-0}
+    volumes:
+      - ./snapshot-results/errors:/errors
+      - ./plugins/ui/docs/snapshots:/snapshots/ui
+      - ./plugins/plotly-express/docs/snapshots:/snapshots/plotly-express
+      - ./plugins/tradingview-lightweight/docs/snapshots:/snapshots/tradingview-lightweight
+    command:
+      - sh
+      - -c
+      - |
+        if [ "$$SNAPSHOT_UID" != "0" ]; then
+          chown -R "$$SNAPSHOT_UID:$$SNAPSHOT_GID" /errors /snapshots 2>/dev/null || true
+        fi
+        had=0
+        for plugin in plotly-express ui tradingview-lightweight; do
+          f="/errors/$$plugin/errors.txt"
+          if [ -s "$$f" ]; then
+            had=1
+            echo ""
+            echo "==================== $$plugin ($$f) ===================="
+            head -n 200 "$$f"
+            n=$$(wc -l < "$$f")
+            if [ "$$n" -gt 200 ]; then
+              echo "... ($$n total lines; full file at snapshot-results/errors/$$plugin/errors.txt)"
+            fi
+          fi
+        done
+        if [ "$$had" -eq 0 ]; then
+          echo "[error-reporter] no snapshot errors recorded."
+        fi
+        exit $$had
+
   # Validate MDX and the snapshots that were written are valid
   deephaven-plugins-docs-validator:
     image: ghcr.io/deephaven/salmon-validator
@@ -51,6 +155,7 @@ services:
     volumes:
       - ./plugins/ui/docs/build/markdown:/validate/ui
       - ./plugins/plotly-express/docs/build/markdown:/validate/plotly-express
+      - ./plugins/tradingview-lightweight/docs/build/markdown:/validate/tradingview-lightweight
       - ./docker/build/validator-results:/results
 
 volumes:
diff --git a/docker-compose.docs.yml b/docker-compose.docs.yml
index 7d8cb008d..bbf35f02f 100644
--- a/docker-compose.docs.yml
+++ b/docker-compose.docs.yml
@@ -9,3 +9,4 @@ services:
     volumes:
       - ./plugins/ui/docs${BUILT+/build/markdown}:/salmon/core/ui/docs
       - ./plugins/plotly-express/docs${BUILT+/build/markdown}:/salmon/core/plotly/docs
+      - ./plugins/tradingview-lightweight/docs${BUILT+/build/markdown}:/salmon/core/tradingview-lightweight/docs
diff --git a/docker/python-snapshotter/docker-compose.yml b/docker/python-snapshotter/docker-compose.yml
new file mode 100644
index 000000000..d1138b542
--- /dev/null
+++ b/docker/python-snapshotter/docker-compose.yml
@@ -0,0 +1,43 @@
+# Pass 2 (image-snapshotter) test server. Plugin-agnostic.
+#
+# Reuses the python-server image already built by salmon's Pass 1
+# (../python/docker-compose.yml). The only differences vs. that compose:
+#
+#   - We mount a generated app.d directory at /app.d so the docs examples
+#     are pre-loaded as Deephaven panels (the Pass 2 server is otherwise
+#     headless — no code is ever sent over the console).
+#   - START_OPTS adds -Ddeephaven.application.dir=/app.d to enable app
+#     mode against that directory.
+#   - DEEPHAVEN_PLUGINS_STATIC_DATA=1 forces tvl.data / dx.data into
+#     static mode so screenshots are deterministic.
+#
+# image-snapshotter's entrypoint sets PASS2_APPD_HOST_PATH to the host
+# filesystem path of the generated app.d (bind mounts traverse the host
+# because the docker socket is the host's). The `:?` makes compose fail
+# fast if the entrypoint forgot to export it.
+#
+# SNAPSHOTTER_SERVER_CONTAINER lets parallel plugin invocations produce
+# unique container names. Serial Pass 2 invocations (the default
+# docs-snapshots compose flow) can rely on the default.
+#
+# The image tag matches what `docker/python/docker-compose.yml` builds —
+# `image: python-server:latest` rather than a `build:` block because Pass 1
+# always runs first and produces the image. On a clean run with Pass 1
+# skipped the image won't exist locally and `up` will fail; that's the
+# documented contract.
+services:
+  server:
+    image: python-server:latest
+    container_name: ${SNAPSHOTTER_SERVER_CONTAINER:-deephaven-snapshotter-server}
+    expose:
+      - 10000
+    environment:
+      - START_OPTS=-Xmx4g -DAuthHandlers=io.deephaven.auth.AnonymousAuthenticationHandler -Ddeephaven.console.type=python -Ddeephaven.application.dir=/app.d
+      - DEEPHAVEN_PLUGINS_STATIC_DATA=1
+    volumes:
+      - ${PASS2_APPD_HOST_PATH:?PASS2_APPD_HOST_PATH must be set}:/app.d:ro
+
+networks:
+  default:
+    name: deephaven-plugins-docs-snapshot-network
+    external: true
diff --git a/docker/python/docker-compose.yml b/docker/python/docker-compose.yml
index dd393c530..b88d1660a 100644
--- a/docker/python/docker-compose.yml
+++ b/docker/python/docker-compose.yml
@@ -8,6 +8,11 @@ services:
       - 10000
     environment:
       - START_OPTS=-Xmx4g -DAuthHandlers=io.deephaven.auth.AnonymousAuthenticationHandler -Ddeephaven.console.type=python
+      # Force tvl.data / dx.data into static mode so docs snapshots are
+      # reproducible AND so doc blocks that chain `.update(["X = (double)ii"])`
+      # onto a generator output don't blow up on the refreshing-formula check
+      # (the merged static+time_table isn't classified as append-only).
+      - DEEPHAVEN_PLUGINS_STATIC_DATA=1
 
 networks:
   default:
diff --git a/package-lock.json b/package-lock.json
index 46d5acfd3..7717ff458 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -231,6 +231,7 @@
       "integrity": "sha512-CGOfOJqWjg2qW/Mb6zNsDm+u5vFQ8DxXfbM09z69p5Z6+mE1ikP2jUXw+j42Pf1XTYED2Rni5f95npYeuwMDQA==",
       "dev": true,
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "@babel/code-frame": "^7.29.0",
         "@babel/generator": "^7.29.0",
@@ -876,6 +877,7 @@
       "integrity": "sha512-D+OrJumc9McXNEBI/JmFnc/0uCM2/Y3PEBG3gfV3QIYkKv5pvnpzFrl1kYCrcHJP8nOeFB/SHi1IHz29pNGuew==",
       "dev": true,
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "@babel/helper-plugin-utils": "^7.28.6"
       },
@@ -1801,6 +1803,7 @@
       "integrity": "sha512-61bxqhiRfAACulXSLd/GxqmAedUSrRZIu/cbaT18T1CetkTmtDN15it7i80ru4DVqRK1WMxQhXs+Lf9kajm5Ow==",
       "dev": true,
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "@babel/helper-annotate-as-pure": "^7.27.3",
         "@babel/helper-module-imports": "^7.28.6",
@@ -2311,7 +2314,6 @@
       "integrity": "sha512-FvEb29x5wVwu/Kf93IWwsOOEuhHh6dYCJF3vcKLzXc0KXIW181AOzv6ceT4ZpBHDvAfG60eqb+ekmrnLHIy+jw==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@cacheable/utils": "^2.4.0",
         "@keyv/bigmap": "^1.3.1",
@@ -2325,7 +2327,6 @@
       "integrity": "sha512-WbzE9sdmQtKy8vrNPa9BRnwZh5UF4s1KTmSK0KUVLo3eff5BlQNNWDnFOouNpKfPKDnms9xynJjsMYjMaT/aFQ==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "hashery": "^1.4.0",
         "hookified": "^1.15.0"
@@ -2354,7 +2355,6 @@
       "integrity": "sha512-eiFgzCbIneyMlLOmNG4g9xzF7Hv3Mga4LjxjcSC/ues6VYq2+gUbQI8JqNuw/ZM8tJIeIaBGpswAsqV2V7ApgA==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "hashery": "^1.5.1",
         "keyv": "^5.6.0"
@@ -2366,7 +2366,6 @@
       "integrity": "sha512-CYDD3SOtsHtyXeEORYRx2qBtpDJFjRTGXUtmNEMGyzYOKj1TE3tycdlho7kA1Ufx9OYWZzg52QFBGALTirzDSw==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@keyv/serialize": "^1.1.1"
       }
@@ -2399,7 +2398,6 @@
         }
       ],
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": ">=20.19.0"
       },
@@ -2448,7 +2446,6 @@
         }
       ],
       "license": "MIT-0",
-      "peer": true,
       "peerDependencies": {
         "css-tree": "^3.2.1"
       },
@@ -2495,7 +2492,6 @@
         }
       ],
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": ">=20.19.0"
       },
@@ -2520,7 +2516,6 @@
         }
       ],
       "license": "MIT-0",
-      "peer": true,
       "engines": {
         "node": ">=20.19.0"
       },
@@ -2544,7 +2539,6 @@
         }
       ],
       "license": "MIT-0",
-      "peer": true,
       "engines": {
         "node": ">=20.19.0"
       },
@@ -3169,6 +3163,10 @@
       "resolved": "plugins/theme-pack/src/js",
       "link": true
     },
+    "node_modules/@deephaven/js-plugin-tradingview-lightweight": {
+      "resolved": "plugins/tradingview-lightweight/src/js",
+      "link": true
+    },
     "node_modules/@deephaven/js-plugin-ui": {
       "resolved": "plugins/ui/src/js",
       "link": true
@@ -3476,6 +3474,7 @@
       "resolved": "https://registry.npmjs.org/@dnd-kit/core/-/core-6.3.1.tgz",
       "integrity": "sha512-xkGBRQQab4RLwgXxoqETICr6S5JlogafbhNsidmrkVv2YRs5MLwpjoF2qpiGjQt8S9AoxtIV603s0GIUpY5eYQ==",
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "@dnd-kit/accessibility": "^3.1.1",
         "@dnd-kit/utilities": "^3.2.2",
@@ -4089,6 +4088,7 @@
       "resolved": "https://registry.npmjs.org/@fortawesome/fontawesome-svg-core/-/fontawesome-svg-core-6.7.2.tgz",
       "integrity": "sha512-yxtOBWDrdi5DD5o1pmVdq3WMCvnobT0LU6R8RyyVXPvFRd2o79/0NCuQoCjNTeZz9EzA9xS3JxNWfv54RIHFEA==",
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "@fortawesome/fontawesome-common-types": "6.7.2"
       },
@@ -4102,6 +4102,7 @@
       "integrity": "sha512-mtBFIi1UsYQo7rYonYFkjgYKGoL8T+fEH6NGUpvuqtY3ytMsAoDaPo5rk25KuMtKDipY4bGYM/CkmCHA1N3FUg==",
       "deprecated": "v0.2.x is no longer supported. Unless you are still using FontAwesome 5, please update to v3.1.1 or greater.",
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "prop-types": "^15.8.1"
       },
@@ -4164,7 +4165,8 @@
       "version": "5.0.1",
       "resolved": "https://registry.npmjs.org/redux/-/redux-5.0.1.tgz",
       "integrity": "sha512-M9/ELqF6fy8FwmkpnF0S3YKOqMyoWJ4+CS5Efg2ct3oY9daQvd/Pc71FpGZsVsbl3Cpb+IIcjBDUnnyBdQbq4w==",
-      "license": "MIT"
+      "license": "MIT",
+      "peer": true
     },
     "node_modules/@humanwhocodes/config-array": {
       "version": "0.13.0",
@@ -5225,6 +5227,17 @@
         "node": ">=6.0.0"
       }
     },
+    "node_modules/@jridgewell/source-map": {
+      "version": "0.3.11",
+      "resolved": "https://registry.npmjs.org/@jridgewell/source-map/-/source-map-0.3.11.tgz",
+      "integrity": "sha512-ZMp1V8ZFcPG5dIWnQLr3NSI1MiCU7UETdS/A0G8V/XWHvJv3ZsFqutJn1Y5RPmAPX6F3BiE397OqveU/9NCuIA==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@jridgewell/gen-mapping": "^0.3.5",
+        "@jridgewell/trace-mapping": "^0.3.25"
+      }
+    },
     "node_modules/@jridgewell/sourcemap-codec": {
       "version": "1.5.5",
       "resolved": "https://registry.npmjs.org/@jridgewell/sourcemap-codec/-/sourcemap-codec-1.5.5.tgz",
@@ -5248,8 +5261,7 @@
       "resolved": "https://registry.npmjs.org/@keyv/serialize/-/serialize-1.1.1.tgz",
       "integrity": "sha512-dXn3FZhPv0US+7dtJsIi2R+c7qWYiReoEh5zUntWCf4oSpMNib8FDhSoed6m3QyZdx5hK7iLFkYk3rNxwt8vTA==",
       "dev": true,
-      "license": "MIT",
-      "peer": true
+      "license": "MIT"
     },
     "node_modules/@mapbox/geojson-rewind": {
       "version": "0.5.2",
@@ -6419,6 +6431,7 @@
       "integrity": "sha512-/g2d4sW9nUDJOMz3mabVQvOGhVa4e/BN/Um7yca9Bb2XTzPPnfTWHWQg+IsEYO7M3Vx+EXvaM/I2pJWIMun1bg==",
       "dev": true,
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "@octokit/auth-token": "^4.0.0",
         "@octokit/graphql": "^7.1.0",
@@ -6907,7 +6920,6 @@
       "integrity": "sha512-fdDH1LSGfZdTH2sxdpVMw31BanV28K/Gry0cVFxaNP77neJSkd82mM8ErPNYs9e+0O7SdHBLTDzDgwUuy18RnQ==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": "^12.20.0 || ^14.18.0 || >=16.0.0"
       },
@@ -7137,6 +7149,7 @@
       "resolved": "https://registry.npmjs.org/@adobe/react-spectrum/-/react-spectrum-3.47.0.tgz",
       "integrity": "sha512-EDQuMzz0kUeiMUUlxoeLFQyyxOXaAC7qlBw2PYOUfFLYd87xcV7VVV0JxiYx8zGk1IIY3UgQHgXrS1fv7CgezQ==",
       "license": "Apache-2.0",
+      "peer": true,
       "dependencies": {
         "@internationalized/date": "^3.12.1",
         "@react-types/shared": "^3.34.0",
@@ -7207,6 +7220,7 @@
       "resolved": "https://registry.npmjs.org/@adobe/react-spectrum/-/react-spectrum-3.47.0.tgz",
       "integrity": "sha512-EDQuMzz0kUeiMUUlxoeLFQyyxOXaAC7qlBw2PYOUfFLYd87xcV7VVV0JxiYx8zGk1IIY3UgQHgXrS1fv7CgezQ==",
       "license": "Apache-2.0",
+      "peer": true,
       "dependencies": {
         "@internationalized/date": "^3.12.1",
         "@react-types/shared": "^3.34.0",
@@ -7277,6 +7291,7 @@
       "resolved": "https://registry.npmjs.org/@adobe/react-spectrum/-/react-spectrum-3.47.0.tgz",
       "integrity": "sha512-EDQuMzz0kUeiMUUlxoeLFQyyxOXaAC7qlBw2PYOUfFLYd87xcV7VVV0JxiYx8zGk1IIY3UgQHgXrS1fv7CgezQ==",
       "license": "Apache-2.0",
+      "peer": true,
       "dependencies": {
         "@internationalized/date": "^3.12.1",
         "@react-types/shared": "^3.34.0",
@@ -7346,6 +7361,7 @@
       "resolved": "https://registry.npmjs.org/@adobe/react-spectrum/-/react-spectrum-3.47.0.tgz",
       "integrity": "sha512-EDQuMzz0kUeiMUUlxoeLFQyyxOXaAC7qlBw2PYOUfFLYd87xcV7VVV0JxiYx8zGk1IIY3UgQHgXrS1fv7CgezQ==",
       "license": "Apache-2.0",
+      "peer": true,
       "dependencies": {
         "@internationalized/date": "^3.12.1",
         "@react-types/shared": "^3.34.0",
@@ -7415,6 +7431,7 @@
       "resolved": "https://registry.npmjs.org/@adobe/react-spectrum/-/react-spectrum-3.47.0.tgz",
       "integrity": "sha512-EDQuMzz0kUeiMUUlxoeLFQyyxOXaAC7qlBw2PYOUfFLYd87xcV7VVV0JxiYx8zGk1IIY3UgQHgXrS1fv7CgezQ==",
       "license": "Apache-2.0",
+      "peer": true,
       "dependencies": {
         "@internationalized/date": "^3.12.1",
         "@react-types/shared": "^3.34.0",
@@ -7485,6 +7502,7 @@
       "resolved": "https://registry.npmjs.org/@adobe/react-spectrum/-/react-spectrum-3.47.0.tgz",
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+      "resolved": "https://registry.npmjs.org/css-loader/-/css-loader-7.1.4.tgz",
+      "integrity": "sha512-vv3J9tlOl04WjiMvHQI/9tmIrCxVrj6PFbHemBB1iihpeRbi/I4h033eoFIhwxBBqLhI0KYFS7yvynBFhIZfTw==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "icss-utils": "^5.1.0",
+        "postcss": "^8.4.40",
+        "postcss-modules-extract-imports": "^3.1.0",
+        "postcss-modules-local-by-default": "^4.0.5",
+        "postcss-modules-scope": "^3.2.0",
+        "postcss-modules-values": "^4.0.0",
+        "postcss-value-parser": "^4.2.0",
+        "semver": "^7.6.3"
+      },
+      "engines": {
+        "node": ">= 18.12.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/webpack"
+      },
+      "peerDependencies": {
+        "@rspack/core": "0.x || ^1.0.0 || ^2.0.0-0",
+        "webpack": "^5.27.0"
+      },
+      "peerDependenciesMeta": {
+        "@rspack/core": {
+          "optional": true
+        },
+        "webpack": {
+          "optional": true
+        }
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/monaco-editor": {
+      "version": "0.41.0",
+      "resolved": "https://registry.npmjs.org/monaco-editor/-/monaco-editor-0.41.0.tgz",
+      "integrity": "sha512-1o4olnZJsiLmv5pwLEAmzHTE/5geLKQ07BrGxlF4Ri/AXAc2yyDGZwHjiTqD8D/ROKUZmwMA28A+yEowLNOEcA==",
+      "dev": true,
+      "license": "MIT"
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/nanoid": {
+      "version": "5.1.15",
+      "resolved": "https://registry.npmjs.org/nanoid/-/nanoid-5.1.15.tgz",
+      "integrity": "sha512-kBg3RpGtIe+RpTbyXwoI6pk5yD7KUiI3sygUqgeBMRst42KmhB4RZC7eiO9Wa1HIpaCCtpE2DJ6OI4Wi5ebwFw==",
+      "dev": true,
+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/ai"
+        }
+      ],
+      "license": "MIT",
+      "bin": {
+        "nanoid": "bin/nanoid.js"
+      },
+      "engines": {
+        "node": "^18 || >=20"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/plotly.js": {
+      "version": "2.35.3",
+      "resolved": "https://registry.npmjs.org/plotly.js/-/plotly.js-2.35.3.tgz",
+      "integrity": "sha512-7RaC6FxmCUhpD6H4MpD+QLUu3hCn76I11rotRefrh3m1iDvWqGnVqVk9dSaKmRAhFD3vsNsYea0OxnR1rc2IzQ==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@plotly/d3": "3.8.2",
+        "@plotly/d3-sankey": "0.7.2",
+        "@plotly/d3-sankey-circular": "0.33.1",
+        "@plotly/mapbox-gl": "1.13.4",
+        "@turf/area": "^7.1.0",
+        "@turf/bbox": "^7.1.0",
+        "@turf/centroid": "^7.1.0",
+        "base64-arraybuffer": "^1.0.2",
+        "canvas-fit": "^1.5.0",
+        "color-alpha": "1.0.4",
+        "color-normalize": "1.5.0",
+        "color-parse": "2.0.0",
+        "color-rgba": "2.1.1",
+        "country-regex": "^1.1.0",
+        "css-loader": "^7.1.2",
+        "d3-force": "^1.2.1",
+        "d3-format": "^1.4.5",
+        "d3-geo": "^1.12.1",
+        "d3-geo-projection": "^2.9.0",
+        "d3-hierarchy": "^1.1.9",
+        "d3-interpolate": "^3.0.1",
+        "d3-time": "^1.1.0",
+        "d3-time-format": "^2.2.3",
+        "fast-isnumeric": "^1.1.4",
+        "gl-mat4": "^1.2.0",
+        "gl-text": "^1.4.0",
+        "has-hover": "^1.0.1",
+        "has-passive-events": "^1.0.0",
+        "is-mobile": "^4.0.0",
+        "maplibre-gl": "^4.5.2",
+        "mouse-change": "^1.4.0",
+        "mouse-event-offset": "^3.0.2",
+        "mouse-wheel": "^1.2.0",
+        "native-promise-only": "^0.8.1",
+        "parse-svg-path": "^0.1.2",
+        "point-in-polygon": "^1.1.0",
+        "polybooljs": "^1.2.2",
+        "probe-image-size": "^7.2.3",
+        "regl": "npm:@plotly/regl@^2.1.2",
+        "regl-error2d": "^2.0.12",
+        "regl-line2d": "^3.1.3",
+        "regl-scatter2d": "^3.3.1",
+        "regl-splom": "^1.0.14",
+        "strongly-connected-components": "^1.0.1",
+        "style-loader": "^4.0.0",
+        "superscript-text": "^1.0.0",
+        "svg-path-sdf": "^1.1.3",
+        "tinycolor2": "^1.4.2",
+        "to-px": "1.0.1",
+        "topojson-client": "^3.1.0",
+        "webgl-context": "^2.2.0",
+        "world-calendars": "^1.0.3"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/react": {
+      "version": "17.0.2",
+      "resolved": "https://registry.npmjs.org/react/-/react-17.0.2.tgz",
+      "integrity": "sha512-gnhPt75i/dq/z3/6q/0asP78D0u592D5L1pd7M8P+dck6Fu/jJeL6iVVK23fptSUZj8Vjf++7wXA8UNclGQcbA==",
+      "license": "MIT",
+      "peer": true,
+      "dependencies": {
+        "loose-envify": "^1.1.0",
+        "object-assign": "^4.1.1"
+      },
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/react-dom": {
+      "version": "17.0.2",
+      "resolved": "https://registry.npmjs.org/react-dom/-/react-dom-17.0.2.tgz",
+      "integrity": "sha512-s4h96KtLDUQlsENhMn1ar8t2bEa+q/YAtj8pPPdIjPDGBDIVNsrD9aXNWqspUe6AzKCIG0C1HZZLqLV7qpOBGA==",
+      "dev": true,
+      "license": "MIT",
+      "peer": true,
+      "dependencies": {
+        "loose-envify": "^1.1.0",
+        "object-assign": "^4.1.1",
+        "scheduler": "^0.20.2"
+      },
+      "peerDependencies": {
+        "react": "17.0.2"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/react-virtualized-auto-sizer": {
+      "version": "1.0.6",
+      "resolved": "https://registry.npmjs.org/react-virtualized-auto-sizer/-/react-virtualized-auto-sizer-1.0.6.tgz",
+      "integrity": "sha512-7tQ0BmZqfVF6YYEWcIGuoR3OdYe8I/ZFbNclFlGOC3pMqunkYF/oL30NCjSGl9sMEb17AnzixDz98Kqc3N76HQ==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">8.0.0"
+      },
+      "peerDependencies": {
+        "react": "^15.3.0 || ^16.0.0-alpha || ^17.0.0",
+        "react-dom": "^15.3.0 || ^16.0.0-alpha || ^17.0.0"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/redux-thunk": {
+      "version": "2.4.1",
+      "resolved": "https://registry.npmjs.org/redux-thunk/-/redux-thunk-2.4.1.tgz",
+      "integrity": "sha512-OOYGNY5Jy2TWvTL1KgAlVy6dcx3siPJ1wTq741EPyUKfn6W6nChdICjZwCd0p8AZBs5kWpZlbkXW2nE/zjUa+Q==",
+      "dev": true,
+      "license": "MIT",
+      "peerDependencies": {
+        "redux": "^4"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/regl": {
+      "name": "@plotly/regl",
+      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/@plotly/regl/-/regl-2.1.2.tgz",
+      "integrity": "sha512-Mdk+vUACbQvjd0m/1JJjOOafmkp/EpmHjISsopEz5Av44CBq7rPC05HHNbYGKVyNUF2zmEoBS/TT0pd0SPFFyw==",
+      "dev": true,
+      "license": "MIT"
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/scheduler": {
+      "version": "0.20.2",
+      "resolved": "https://registry.npmjs.org/scheduler/-/scheduler-0.20.2.tgz",
+      "integrity": "sha512-2eWfGgAqqWFGqtdMmcL5zCMK1U8KlXv8SQFGglL3CEtd0aDVDWgeF/YoCmvln55m5zSk3J/20hTaSBeSObsQDQ==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "loose-envify": "^1.1.0",
+        "object-assign": "^4.1.1"
+      }
+    },
+    "plugins/tradingview-lightweight/src/js/node_modules/semver": {
+      "version": "7.8.5",
+      "resolved": "https://registry.npmjs.org/semver/-/semver-7.8.5.tgz",
+      "integrity": "sha512-Y7/KDsb8LjooZpwaqGyulO6DQlksgCncchHGk+sZIY4SBvUocMBEFH5Ur1fI4dV+Jvl0w6cjvucaIi40puRioA==",
+      "dev": true,
+      "license": "ISC",
+      "bin": {
+        "semver": "bin/semver.js"
+      },
+      "engines": {
+        "node": ">=10"
+      }
+    },
     "plugins/ui/src/js": {
       "name": "@deephaven/js-plugin-ui",
       "version": "0.38.0",
diff --git a/package.json b/package.json
index 0d15b4b9e..b3972cd92 100644
--- a/package.json
+++ b/package.json
@@ -28,7 +28,7 @@
     "update-dh-packages": "lerna run --concurrency 1 update-dh-packages",
     "update-dh-packages:ui": "npm run update-dh-packages -- --scope=@deephaven/js-plugin-ui --",
     "validate-marketplace": "node tools/validate-marketplace.mjs",
-    "update-doc-snapshots": "./tools/run_docker.sh ./docker-compose.docs-snapshots.yml deephaven-plugins-docs-snapshotter",
+    "update-doc-snapshots": "docker compose -f ./docker/python/docker-compose.yml build server && (./tools/run_docker.sh ./docker-compose.docs-snapshots.yml deephaven-plugins-docs-image-snapshotter-tvl; ec=$?; ./tools/run_docker.sh ./docker-compose.docs-snapshots.yml deephaven-plugins-docs-error-reporter || true; exit $ec)",
     "validate-doc-snapshots": "./tools/run_docker.sh ./docker-compose.docs-snapshots.yml deephaven-plugins-docs-validator"
   },
   "devDependencies": {
diff --git a/plugins/tradingview-lightweight/.gitignore b/plugins/tradingview-lightweight/.gitignore
new file mode 100644
index 000000000..054da38f1
--- /dev/null
+++ b/plugins/tradingview-lightweight/.gitignore
@@ -0,0 +1,10 @@
+build/
+dist/
+.venv/
+/venv
+*.egg-info/
+.idea
+.DS_store
+__pycache__/
+docs/build/
+app.d/docs_examples/
diff --git a/plugins/tradingview-lightweight/AGENTS.md b/plugins/tradingview-lightweight/AGENTS.md
new file mode 100644
index 000000000..3973aa0c4
--- /dev/null
+++ b/plugins/tradingview-lightweight/AGENTS.md
@@ -0,0 +1,434 @@
+# Local Development & Testing
+
+tradingview-lightweight charts I call tvl for short.
+
+## Quick Start
+
+Use the root `tools/plugin_builder.py` to build the JS bundle + Python wheel
+and bring up a Deephaven server with the plugin installed. From the repo root:
+
+```bash
+python tools/plugin_builder.py --js --reinstall --server tradingview-lightweight
+```
+
+The plugin name is a positional argument — there is no `--plugin` flag.
+`--js` builds the JS bundle, `--reinstall` rebuilds and force-reinstalls the
+wheel (needed when the version number hasn't changed), and `--server` (`-s`)
+starts the Deephaven server. After code changes, re-run the same command to
+rebuild and restart. Run `python tools/plugin_builder.py --help` for all flags.
+
+App.d fixtures for local dev/snapshot capture live under `app.d/` at the
+plugin root (`disconnect_test.py`, `downsample_compare.py`). Point the
+Deephaven server at this directory with `-Ddeephaven.application.dir=$(pwd)/app.d`
+when you need the fixtures pre-loaded.
+
+## Testing with agent-browser
+
+After the server is running:
+
+```bash
+# Open the IDE and set viewport
+agent-browser open http://localhost:10000/ide/
+agent-browser wait --load networkidle
+agent-browser wait 5000
+agent-browser set viewport 1920 1080
+```
+
+### Running code in the DH console
+
+The DH IDE opens panels for **new variable assignments**, not bare expressions.
+Typing `tvl_line` alone will not open a panel. You must assign to a new name:
+
+```bash
+# 1. Find the console editor
+agent-browser snapshot -i          # look for the textbox ref
+agent-browser click @e15           # click the editor (ref may vary)
+
+# 2. Type a variable assignment and execute
+agent-browser keyboard type "my_chart = tvl_line"
+agent-browser press Escape         # dismiss autocomplete
+agent-browser wait 100
+agent-browser press Enter          # execute (Enter works; Ctrl+Enter may not)
+agent-browser wait 5000            # wait for panel to open and data to load
+
+# 3. Move mouse away and screenshot
+agent-browser mouse move 0 0
+agent-browser wait 500
+agent-browser screenshot /tmp/tvl_test.png
+```
+
+Multi-statement commands work the same way:
+
+```bash
+agent-browser keyboard type "from deephaven.plot import tradingview_lightweight as tvl"
+agent-browser press Escape && agent-browser wait 100 && agent-browser press Enter
+agent-browser wait 2000
+
+agent-browser keyboard type "my_by = tvl.line(_by_table, time='Timestamp', value='Price', by='Sym')"
+agent-browser press Escape && agent-browser wait 100 && agent-browser press Enter
+agent-browser wait 5000
+```
+
+To verify a panel opened, check the Golden Layout tabs:
+
+```bash
+agent-browser eval "JSON.stringify(Array.from(document.querySelectorAll('.lm_tab')).map(e => e.textContent).filter(t => t.length > 0))"
+# Should include your variable name, e.g. ["Console","Log","Command History","File Explorer","my_chart"]
+```
+
+### Opening widgets from the Panels menu (alternative)
+
+The Panels menu lists all exported variables. This approach does NOT
+reliably open widget panels — it works for tables but may silently
+fail for plugin widgets. Prefer the console assignment method above.
+
+```bash
+agent-browser snapshot -i -c
+agent-browser click @e3            # "Panels" button — ref may vary
+agent-browser wait 500
+agent-browser snapshot -i -c       # find the search box ref
+agent-browser fill @e7 "tvl_candlestick"
+agent-browser wait 500
+agent-browser snapshot -i -c       # find the button ref
+agent-browser click @e11           # ref may vary
+agent-browser wait 3000
+```
+
+### Screenshotting an individual chart
+
+After opening a chart panel, isolate the chart and screenshot:
+
+```bash
+# Move mouse off chart to avoid hover tooltips
+agent-browser mouse move 0 0
+agent-browser wait 500
+
+# Screenshot the full page (chart will be visible in the panel area)
+agent-browser screenshot /tmp/tvl_chart.png
+
+# Or check for chart elements
+agent-browser eval "document.querySelectorAll('.dh-tvl-chart').length"
+```
+
+View the screenshot with the `Read` tool on the image path. Always screenshot into the local directory so the user can also verify if needed.
+
+### Important Notes
+
+- **Refs change between snapshots.** Always run `agent-browser snapshot -i` before clicking to get fresh refs.
+- **Charts render on canvas.** Use screenshots to verify chart content — DOM queries won't see rendered lines/candles.
+- **Use variable assignments** to open widget panels (e.g., `my_chart = tvl_line`). Bare expressions evaluate but don't open panels.
+- **Enter, not Ctrl+Enter.** Plain `Enter` executes single-line commands. `Ctrl+Enter` may insert a newline instead.
+- **Dismiss autocomplete** with `agent-browser press Escape` before pressing Enter, otherwise it may select a completion instead of executing.
+- **Zombie processes.** If the server seems stale (serving old JS), kill any
+  lingering `deephaven_server` processes (`pkill -f deephaven_server`) and
+  re-run `tools/plugin_builder.py`.
+
+## How It Works
+
+`tools/plugin_builder.py --js --reinstall --server tradingview-lightweight`:
+
+1. Builds the JS bundle via `npm run build` in `src/js/`.
+2. Builds the Python wheel and installs it into a Deephaven server venv.
+3. Starts the DH server on port 10000.
+
+The DH web client loads the JS plugin via `/js-plugins/manifest.json`. The
+CJS bundle uses `require()` for modules the DH client provides (react,
+`@deephaven/plugin`, etc.) — these are resolved by the client's built-in
+require shim.
+
+## API Reference Notes
+
+For TradingView Lightweight Charts v5.2 API documentation, fetch the
+upstream docs at https://tradingview.github.io/lightweight-charts/docs (the
+local notes/api-reference/ snapshot has been removed to keep the plugin
+tree clean).
+
+## Architecture Overview
+
+### JS Component Hierarchy
+
+```
+TradingViewPlugin (plugin registration)
+├── component: TradingViewChart         — for inline/embedded use
+└── panelComponent: TradingViewChartPanel — for standalone panels
+    └── WidgetPanel (@deephaven/dashboard-core-plugins)
+        ├── Session disconnect/reconnect detection
+        ├── LoadingOverlay (spinner + error + disconnect)
+        └── TradingViewChart
+            ├── TradingViewChartModel  — data pipeline, table subscriptions
+            └── TradingViewChartRenderer — LWC chart instance, series management
+```
+
+### Key Files
+
+| File                                          | Role                                                              |
+| --------------------------------------------- | ----------------------------------------------------------------- |
+| `src/js/src/TradingViewChartPanel.tsx`        | WidgetPanel wrapper — session disconnect, loading overlay         |
+| `src/js/src/TradingViewChart.tsx`             | Main component — init, data updates, zoom/pan, downsample UX      |
+| `src/js/src/TradingViewChartModel.ts`         | Model — widget messages, table subscriptions, autobin/EVENT       |
+| `src/js/src/TradingViewChartRenderer.ts`      | LWC wrapper — chart creation, series CRUD, markers, price lines   |
+| `src/js/src/TradingViewEventPayload.ts`       | Builds the press-event payload sent to Python (hit test, series)  |
+| `src/js/src/TradingViewChart.css`             | Downsample scrim/status bar styles (inlined via `?inline` import) |
+| `src/deephaven/.../auto_bin.py`               | Server-side time-bin aggregation for Histogram/Candlestick/Bar    |
+| `src/deephaven/.../events.py`                 | Press-event payloads + handler plumbing (`wrap_callable`)         |
+| `src/deephaven/.../communication/listener.py` | Message handler — RETRIEVE/AUTOBIN_ZOOM/AUTOBIN_RESET/EVENT        |
+
+### CSS Injection
+
+Plugin CSS files aren't loaded by the DH client. TVL uses Vite's `?inline` import to embed CSS as a string, injected via a `<style>` tag in the component. The `WidgetPanel`'s CSS (LoadingOverlay, scrim) comes from `@deephaven/dashboard-core-plugins` which is loaded by the IDE.
+
+Z-index note: `.dh-tvl-panel > .fill-parent-absolute { z-index: 50 }` ensures WidgetPanel's LoadingOverlay renders above the chart's `position: relative` container.
+
+### Downsample / Autobin Architecture
+
+There are two distinct density-reduction paths depending on series type:
+
+**Line / Area / Baseline — JS-side downsample** (`runChartDownsample`):
+min/max-per-bin reduction performed client-side over the data the model has
+already received.
+
+**Histogram / Candlestick / Bar — server-side autobin** (`auto_bin.py`):
+these can't be min/max downsampled, so the server time-bin aggregates them.
+
+- `build_histogram_view()` / `build_ohlc_view()` aggregate via
+  `update_view(["Bin = upperBin(time, w)"])` + `agg_by(..., by=["Bin"])`
+- Bin width is chosen from the visible range and snapped to a "nice" duration
+  (`nice_bin_width()`); target bin count derives from pixel width (`BAR_PX`)
+- On zoom, the listener handles `AUTOBIN_ZOOM` and swaps in a finer
+  aggregation; `AUTOBIN_RESET` returns to the full-range view
+- Works on ticking tables (no `ii`/`k`/`where_in`)
+
+**JS-side downsample UX:**
+
+- Progressive scrim: 200ms delay → scrim sweeps down (150ms CSS transition), 500ms → status bar with indeterminate animation
+- Scrim stays until `DATA_UPDATED` (not `DOWNSAMPLE_PENDING(false)` which fires before data arrives)
+- `lockRangeOnNextUpdateRef` prevents tick updates from snapping viewport back after zoom
+- Snap-to-live: auto-scrolls when right edge is within 1% of latest data point
+- Double-click resets both time scale (`fitContent`) and price scales (`setAutoScale(true)`)
+
+### Press Events
+
+A chart can call back into Python on press / double-press, following the
+deephaven.ui event convention (`on_press` / `on_double_press`, a plain Python
+callable receiving one camelCase-keyed event dict, or no argument).
+
+- Handlers are accepted on `tvl.chart(...)` and on every per-type constructor
+  (`line`, `area`, `candlestick`, `bar`, `baseline`, `histogram`)
+- **JS side** (`TradingViewEventPayload.ts`): on press, builds a payload that
+  mirrors lightweight-charts' `MouseEventParams` — `time` under the cursor,
+  `point`, `logical`, `paneIndex`, `seriesData` (every series' data at the
+  location, keyed by friendly id), the hovered series as `hoveredSeries`
+  (friendly id) + `hoveredSeriesId` (stable `series_<n>`), and the modifier
+  keys — and sends an `EVENT` message to the model. Two deviations from raw
+  `MouseEventParams`: the hovered `ISeriesApi` becomes a string id, and `time`
+  becomes a Deephaven timestamp server-side.
+- **Python side** (`events.py`): the listener dispatches the `EVENT` to the
+  registered handler. `wrap_callable` (ported from deephaven.ui) adapts the
+  handler so it can be called with one positional arg regardless of its arity;
+  `build_press_event` converts the client payload into a `TvlPressEvent`. Event
+  keys are **camelCase**, matching `MouseEventParams` and deephaven.ui's own
+  event payloads (its `PressEvent` uses `shiftKey` etc.), so the wire → event
+  copy is verbatim. The `timestamp` mirrors the hovered series' time-column
+  dtype (resolved via `hoveredSeriesId`).
+- Unresolved fields are omitted rather than set to `None` (e.g. a press outside
+  the data range omits `timestamp`; not over a series omits `hoveredSeries`)
+- User-facing docs: `docs/events.md`
+
+### Disconnect Handling
+
+Uses `WidgetPanel` from `@deephaven/dashboard-core-plugins` for session-level disconnect detection. Panel wrapper passes `onSessionClose`/`onSessionOpen` callbacks that set error state → WidgetPanel's LoadingOverlay shows "Chart disconnected". Model also listens for `Widget.EVENT_CLOSE` and `Table.EVENT_DISCONNECT/RECONNECT`.
+
+### Timezone Handling
+
+Lightweight-charts has no timezone support, so the model shifts every time
+value by the user's timezone offset (`convertTime` in `TradingViewUtils.ts`)
+before it reaches the chart; axis labels then read in the configured zone.
+
+The timezone comes from the user's Deephaven setting via Redux
+(`useSelector(getTimeZone)` in `TradingViewChart.tsx`), falling back to the
+browser's local zone — matching the plotly-express plugin.
+
+> **Build gotcha:** `@deephaven/redux` must be **bundled**, not externalized —
+> it is intentionally absent from `vite.config.ts` `external`. The DH client's
+> plugin require shim does not provide `@deephaven/redux`, so externalizing it
+> makes the plugin fail to load entirely (`Could not require '@deephaven/redux'`).
+> `react-redux`/`redux` ARE client-provided and stay externalized. plotly-express
+> does the same (bundles `@deephaven/redux`, externalizes `react-redux`).
+
+When the user
+changes their timezone in Settings, a dedicated effect calls
+`model.setTimeZone(tz)`, which re-subscribes every active table so its time
+columns re-convert in the new zone (mirrors plotly-express's
+`fireTimeZoneUpdated`) — no full teardown. The current downsample / auto-bin
+scope is preserved (the already-subscribed table is reused), and if the user
+had zoomed/panned the viewport is re-anchored to the same wall-clock window by
+re-projecting the visible range through the old and new offsets
+(`unconvertTime(old)` → `convertTime(new)`).
+
+### Test Fixtures
+
+Hand-written app.d fixtures live under `app.d/` at the plugin root. Point
+the DH server at this directory with `-Ddeephaven.application.dir=$(pwd)/app.d`
+to pre-load them as panels:
+
+- `disconnect_test.py` — grid + plotly + tvl for disconnect comparison
+- `downsample_compare.py` — 100K table for downsample size comparison
+
+The docs snapshotter (`tools/image-snapshotter`) generates its own per-block
+app.d into `snapshot-results/<plugin>-app.d/` at run time; that directory
+is build output and not checked in.
+
+## Downsample Benchmarking
+
+Use `dh exec` to benchmark downsample approaches headlessly. **Each approach must run in its own `dh exec` process** — the JVM warms up (JIT compilation, memory pools) across runs within a single process, biasing later approaches to look faster.
+
+### How to run
+
+1. Write each approach as a standalone `.py` file under a scratch dir.
+2. Run with: `dh exec bench_my_experiment.py 2>&1 | grep "^RESULT:"`
+3. Compare approaches by running each in a separate `dh exec` invocation, or use `bench_isolated.sh` which automates this.
+
+### Writing a benchmark script
+
+```python
+"""Benchmark: <description>. Run with: dh exec bench_<name>.py"""
+import time
+from deephaven import empty_table, agg, merge as dh_merge
+
+ROW_COUNT = 10_000_000
+NUM_BINS = 1000
+
+big = empty_table(ROW_COUNT).update(
+    [
+        "Timestamp = '2020-01-01T00:00:00Z' + (long)(ii * (10L * 365 * 24 * 3600 * 1_000_000_000L / 10_000_000))",
+        "Price = 100 + Math.sin(ii * 0.0001) * 50",
+        "Volume = 1000 + Math.cos(ii * 0.0002) * 500",
+        "Spread = 0.5 + Math.sin(ii * 0.0003) * 0.3",
+    ]
+)
+
+tc = "Timestamp"
+value_cols = ["Price", "Volume", "Spread"]
+out_cols = [tc] + value_cols
+# ... get rmin, rmax, bw from head/tail ...
+
+times = []
+for i in range(5):
+    t0 = time.perf_counter()
+    # ... approach under test ...
+    _ = merged.size  # force materialization
+    times.append(time.perf_counter() - t0)
+
+print(
+    f"RESULT: avg={sum(times)/len(times):.3f}s  best={min(times):.3f}s  rows={merged.size}"
+)
+```
+
+### Key pitfalls
+
+- Always call `_.size` or similar to force materialization — DH operations are lazy.
+- Run 5+ iterations per script to capture warm-JVM timing within a single process.
+- Compare across scripts (separate processes) for fair cold-start comparisons.
+- The `agg_by` scan dominates cost (~89%). Post-agg steps (merge, sort on ~8K rows) are cheap.
+- `merge_sorted` throws `UnsupportedOperationException` on refreshing (ticking) tables.
+
+## Running Unit Tests
+
+```bash
+# Python (uses uv-managed Python 3.13)
+PY=/home/sandbox/.local/share/uv/python/cpython-3.13.12-linux-x86_64-gnu/bin/python3.13
+$PY -m pip install pytest --break-system-packages
+$PY -m pytest test/ -v
+
+# JavaScript
+cd src/js
+npx jest --verbose
+
+# TypeScript type check
+cd src/js
+npx tsc --noEmit
+```
+
+## End-to-End Tests (Playwright)
+
+The unit tests (jest + jsdom) simulate the DOM. The **e2e** suite under
+`src/js/e2e/` runs the real plugin in a real Deephaven IDE in Chromium via
+Playwright, so it catches wiring / serialization / render bugs the unit tests
+can't. It is self-booting: Playwright's `webServer` starts and tears down the
+Deephaven server for you.
+
+### One-time setup
+
+```bash
+cd src/js
+npm run test:e2e:setup           # provision a venv with deephaven-server + this plugin
+```
+
+`test:e2e:setup` runs `e2e/setup-venv.sh`: it `uv venv`s `<plugin>/.venv`,
+installs `deephaven-server` + `deephaven-plugin-utilities`, builds the JS
+bundle, and installs the plugin into that venv. Re-run it only when the
+**Python** deps change — after JS changes you don't need to (see below).
+
+**Browser.** The config resolves Chromium in this order: `TVL_E2E_CHROMIUM`
+env var → a system Chromium at `/usr/bin/chromium` → Playwright's bundled
+browser. So if a system Chromium is present (common in CI images and this
+sandbox) nothing extra is needed. Otherwise install the bundled browser once:
+
+```bash
+npx playwright install chromium chromium-headless-shell
+```
+
+> Browsers live in the shared `~/.cache/ms-playwright`. There is no separate
+> "plugin" vs "root" Playwright — both use the repo-root `@playwright/test`
+> and the same browser cache. `npx playwright install` prunes builds that
+> don't match the installed Playwright version, so install once and reuse.
+> Chromium runs with `--no-sandbox` (required as root).
+
+### Running
+
+```bash
+cd src/js
+npm run test:e2e                 # builds JS, boots a server, runs the specs, tears it down
+```
+
+`test:e2e` = `build` then `test:e2e:run` (Playwright). On each run
+`e2e/start-server.sh` **syncs the freshly built bundle into the installed
+package**, so the suite always exercises HEAD — you never reinstall the wheel
+after a JS change, just `npm run test:e2e` again. For fast iteration against a
+server you already have up, `reuseExistingServer` is on locally, so a running
+server on :10000 is reused instead of booting a new one.
+
+### How the server is launched (two load-bearing quirks)
+
+`e2e/start-server.sh` boots Deephaven with anonymous auth and
+`-Ddeephaven.application.dir=e2e/app.d` (which auto-opens the
+`tooltip_demo.py` chart as a panel). Two things are required in this sandbox
+and are easy to get wrong:
+
+1. **stdin must stay open.** The `deephaven` CLI prints "Press Control-C to
+   exit" and reads stdin; on stdin EOF (what a backgrounded/non-TTY process
+   gets) it aborts immediately with `Aborted!`. We feed it `tail -f /dev/null |`
+   so stdin never closes. (`< /dev/zero` does NOT work — that floods stdin with
+   bytes and the CLI exits.)
+2. **stdout must be a pipe, not a file.** We append `| cat`. Redirecting the
+   server's stdout to a file makes the JVM abort.
+
+Letting Playwright's `webServer` own the process handles teardown cleanly and
+sidesteps the sandbox rule that a hand-backgrounded JVM gets reaped.
+
+> **Never use shell `sleep` in this sandbox — it exits 144 and kills the
+> script.** Wait via Playwright's own APIs (`page.waitForSelector`,
+> `page.waitForTimeout`) or a `timeout … bash -c 'until curl -sf URL; do :; done'`
+> busy-loop, not `sleep`.
+
+### Writing e2e tests
+
+Add a `*.spec.ts` under `src/js/e2e/`. Assert against the DOM seams the
+components publish rather than screenshotting the canvas:
+
+- `.tvl-tooltip` + its `data-tvl-tooltip` attribute — the tracking tooltip's
+  rendered `title | value | date` (see `tooltip.spec.ts`).
+- `data-tvl-last-event` on the chart container — the last press-event payload.
+
+Hover the chart via `page.mouse.move(...)` over the `.dh-tvl-chart` bounding
+box; the tooltip follows the crosshair just like a real cursor.
diff --git a/plugins/tradingview-lightweight/CLAUDE.md b/plugins/tradingview-lightweight/CLAUDE.md
new file mode 100644
index 000000000..43c994c2d
--- /dev/null
+++ b/plugins/tradingview-lightweight/CLAUDE.md
@@ -0,0 +1 @@
+@AGENTS.md
diff --git a/plugins/tradingview-lightweight/LICENSE b/plugins/tradingview-lightweight/LICENSE
new file mode 100644
index 000000000..d64569567
--- /dev/null
+++ b/plugins/tradingview-lightweight/LICENSE
@@ -0,0 +1,202 @@
+
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diff --git a/plugins/tradingview-lightweight/Makefile b/plugins/tradingview-lightweight/Makefile
new file mode 100644
index 000000000..80d1d2f62
--- /dev/null
+++ b/plugins/tradingview-lightweight/Makefile
@@ -0,0 +1,44 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?= -c .
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = docs
+BUILDDIR      = docs/build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile docs-snapshots
+
+# Clean target: remove all files in BUILDDIR but keep directories
+# Salmon preview tool uses docker volume mounts to share the markdown directory
+# If the markdown directory is removed, the volume mount will break
+clean:
+	rm -rf $(BUILDDIR)/**/*
+
+# Pass 2 docs snapshotter: captures widget PNGs for every `order=` block in
+# docs/*.md, merges into docs/snapshots/<md5>.json, and prunes orphan assets.
+# Requires a running Deephaven server (default http://localhost:10000).
+# The image-snapshotter tool lives at the repo root; per-plugin selectors
+# and widget type are passed via env.
+docs-snapshots:
+	cd ../../tools/image-snapshotter && npm install && npm run build && \
+	  SNAPSHOTTER_PLUGIN_ROOT=$(CURDIR) \
+	  SNAPSHOTTER_PLUGIN=tradingview-lightweight \
+	  SNAPSHOTTER_TARGET_SELECTOR=.dh-tvl-chart \
+	  SNAPSHOTTER_WIDGET_TYPE=deephaven.plot.tradingview_lightweight.TvlChart \
+	  SNAPSHOTTER_APP_ID=tvl.docs.examples \
+	  SNAPSHOTTER_APP_NAME='TVL Docs Examples' \
+	  npx playwright test
+	cd ../../tools/image-snapshotter && \
+	  SNAPSHOTTER_PLUGIN_ROOT=$(CURDIR) \
+	  node dist/cli.js --prune-only
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
diff --git a/plugins/tradingview-lightweight/README.md b/plugins/tradingview-lightweight/README.md
new file mode 100644
index 000000000..7b58c8776
--- /dev/null
+++ b/plugins/tradingview-lightweight/README.md
@@ -0,0 +1,149 @@
+# deephaven-plugin-tradingview-lightweight
+
+A Deephaven plugin for creating TradingView Lightweight Charts from Python.
+
+## Usage
+
+```python
+from deephaven.plot import tradingview_lightweight as tvl
+
+# Simple candlestick chart
+chart = tvl.candlestick(
+    ohlc_table,
+    time="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+)
+
+# Multi-series chart
+chart = tvl.chart(
+    tvl.candlestick(
+        ohlc_table,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+    ),
+    tvl.line(
+        sma_table,
+        timestamp="Timestamp",
+        value="SMA_20",
+        color="#2962FF",
+        title="SMA 20",
+    ),
+    crosshair_mode="magnet",
+    time_visible=True,
+)
+```
+
+## Docs
+
+User-facing documentation lives in [`docs/`](./docs/README.md) and follows
+the same structure plotly-express does: one Markdown page per chart type and
+concept, ending with a `## API Reference` block that `dhautofunction` expands
+from the Python docstrings.
+
+### Build the docs locally
+
+From the repo root:
+
+```shell
+pip install -r ../../sphinx_ext/sphinx-requirements.txt
+pip install dist/deephaven_plugin_tradingview_lightweight-*.whl
+python make_docs.py
+```
+
+The rendered Markdown lands in `docs/build/markdown/`. Don't commit it —
+`docs/build/` is gitignored.
+
+### Use `plugin_builder.py` (recommended)
+
+The same `plugin_builder.py` workflow used for `ui` and `plotly-express`
+works here. From the repo root:
+
+```shell
+# Reinstall the wheel, then build docs.
+python tools/plugin_builder.py --docs --reinstall tradingview-lightweight
+
+# Build docs and regenerate Pass-1 (table) snapshots.
+python tools/plugin_builder.py --docs --snapshots --reinstall tradingview-lightweight
+```
+
+### Preview the docs
+
+```shell
+# Live preview at http://localhost:3001 (uses source markdown, no API reference).
+npm run docs
+
+# Or, after running `python tools/plugin_builder.py --docs tradingview-lightweight`:
+BUILT=true npm run docs
+```
+
+### Snapshot pipeline
+
+Doc snapshots are split into two passes:
+
+1. **Pass 1 — salmon snapshotter.** Walks `docs/*.md`, executes each
+   `python order=...` code block against a test Deephaven server, and writes
+   `docs/snapshots/<code_md5>.json` for the `Table` objects in `order=`.
+   `TvlChart` objects are skipped with a warning — Pass 1 doesn't know how
+   to render canvas-based charts.
+
+2. **Pass 2 — image-snapshotter.** Lives at `tools/image-snapshotter/` at
+   the repo root (shared across plugins). Drives Playwright against a live
+   DH server, screenshots every `TvlChart` in the docs (selector and widget
+   type are passed in via `SNAPSHOTTER_TARGET_SELECTOR` /
+   `SNAPSHOTTER_WIDGET_TYPE`), hashes the PNG, writes
+   `docs/snapshots/assets/<image_sha>.png`, and merges the chart entry
+   into the same `<code_md5>.json` file Pass 1 wrote.
+
+Both passes are wired into the repo-root docker pipeline. From the repo
+root run:
+
+```shell
+npm run update-doc-snapshots
+```
+
+or equivalently:
+
+```shell
+python tools/plugin_builder.py --snapshots tradingview-lightweight
+```
+
+This brings up the salmon extractor + snapshotter + validator, and then a
+fourth service (`deephaven-plugins-docs-image-snapshotter-tvl`) that runs
+Pass 2 inside Playwright's official Docker image against a fresh server.
+No hand-started DH server is required.
+
+The merged JSON envelope carries both the Pass-1 `Table` entries and the
+Pass-2 `TvlChart` entries, keyed by the `order=` symbol names. Salmon
+renders the table entries directly; the chart entries point at the
+content-addressed PNG asset.
+
+#### Local iteration (no docker)
+
+The plugin-local `make docs-snapshots` target still exists for tight
+iteration loops against a hand-started server, but it is **not** how CI
+generates snapshots — use the repo-root command above for anything that
+needs to match CI.
+
+```shell
+python tools/plugin_builder.py --plugin tradingview-lightweight   # separate terminal
+make docs-snapshots                                                # build + run Playwright + prune orphans
+```
+
+Or, even more manually:
+
+```shell
+cd tools/image-snapshotter
+npm install
+npx playwright install chromium   # one-time
+npm run build
+SNAPSHOTTER_PLUGIN_ROOT=$PWD/../../plugins/tradingview-lightweight \
+  SNAPSHOTTER_TARGET_SELECTOR=.dh-tvl-chart \
+  SNAPSHOTTER_WIDGET_TYPE=deephaven.plot.tradingview_lightweight.TvlChart \
+  node dist/cli.js --update         # local; `--check` for CI gate
+```
diff --git a/plugins/tradingview-lightweight/app.d/disconnect_test.py b/plugins/tradingview-lightweight/app.d/disconnect_test.py
new file mode 100644
index 000000000..0fb9eae5e
--- /dev/null
+++ b/plugins/tradingview-lightweight/app.d/disconnect_test.py
@@ -0,0 +1,22 @@
+"""Test fixture for disconnect comparison: iris-grid table, plotly-express chart, TVL chart."""
+from deephaven import empty_table
+from deephaven.time import to_j_instant
+from deephaven.plot import express as dx
+from deephaven.plot import tradingview_lightweight as tvl
+
+_start = to_j_instant("2024-01-01T00:00:00 ET")
+test_table = empty_table(1000).update(
+    [
+        "Timestamp = _start + (long)(ii * 86_400_000_000_000L)",
+        "Price = 100 + Math.sin(ii * 0.05) * 20",
+    ]
+)
+
+# iris-grid panel (plain table)
+grid_panel = test_table
+
+# plotly-express panel
+dx_panel = dx.line(test_table, x="Timestamp", y="Price")
+
+# TVL panel
+tvl_panel = tvl.line(test_table, timestamp="Timestamp", value="Price")
diff --git a/plugins/tradingview-lightweight/app.d/downsample_compare.py b/plugins/tradingview-lightweight/app.d/downsample_compare.py
new file mode 100644
index 000000000..d47ee457d
--- /dev/null
+++ b/plugins/tradingview-lightweight/app.d/downsample_compare.py
@@ -0,0 +1,16 @@
+"""Compare downsample output sizes: plotly-express vs TVL.
+
+Creates the SAME 100K-row table. Charts are created interactively
+in the console to avoid startup load.
+"""
+from deephaven import empty_table
+from deephaven.time import to_j_instant
+
+# Shared source: 100K rows, 1 year of data
+_start = to_j_instant("2024-01-01T00:00:00 ET")
+source_100k = empty_table(100_000).update(
+    [
+        "Timestamp = _start + (long)(ii * (365L * 24 * 3600 * 1_000_000_000L / 100_000))",
+        "Price = 100 + Math.sin(ii * 0.001) * 50 + (ii * 0.0003)",
+    ]
+)
diff --git a/plugins/tradingview-lightweight/app.d/events_demo.py b/plugins/tradingview-lightweight/app.d/events_demo.py
new file mode 100644
index 000000000..5ba1f7093
--- /dev/null
+++ b/plugins/tradingview-lightweight/app.d/events_demo.py
@@ -0,0 +1,301 @@
+"""Interactive press-event showcase: a deephaven.ui dashboard driven by chart clicks.
+
+A single candlestick + EMA chart is the only input device. Every panel around it
+reacts to the chart's press events (``on_press`` / ``on_double_press``):
+
+- **Single-click** a series -> *inspect* that moment. The Inspector shows what you
+  hit (series, time, price, modifier keys) and unpacks the event's ``seriesData``
+  payload: the candle series resolves to an OHLC dict, the EMA series to a single
+  value, both at the instant you clicked. The Drill-down table filters the raw
+  data to a window around that time.
+- **Shift-click** or **double-click** -> *pin* that point into a live log table.
+  The pinned log ticks as you click, and a summary badge aggregates it live.
+
+Data comes entirely from ``tvl.data`` (the deterministic ``ohlc`` candle series),
+so the demo is self-contained. Load it by pointing the server at this directory:
+
+    python tools/plugin_builder.py --js --reinstall --server tradingview-lightweight \
+        -- -Ddeephaven.application.dir=$(pwd)/plugins/tradingview-lightweight/app.d
+"""
+
+from __future__ import annotations
+
+from deephaven import ui, new_table
+from deephaven import dtypes as dht
+from deephaven.column import datetime_col, string_col, double_col
+from deephaven.stream.table_publisher import table_publisher
+from deephaven.plot import tradingview_lightweight as tvl
+
+
+# --------------------------------------------------------------------------- #
+# Data - a candle series with a built-in EMA column. Candles and the EMA share
+# every timestamp, so one press resolves a value for *both* series. Static seed
+# keeps the window filter and snapshots reproducible for the demo.
+# --------------------------------------------------------------------------- #
+candles = tvl.data.ohlc(ticking=False)
+
+
+# --------------------------------------------------------------------------- #
+# A live "pinned levels" table. table_publisher emits a blink stream; tailing it
+# accumulates the pins so the log grows as the user clicks (mirrors events.md).
+# Created at module scope so its liveness outlives any single render.
+# --------------------------------------------------------------------------- #
+_pins_blink, _pins_pub = table_publisher(
+    "Pinned levels",
+    {"Time": dht.Instant, "Series": dht.string, "Price": dht.double},
+)
+pinned = _pins_blink.tail(500)
+
+
+def _pin(event: dict) -> None:
+    """Append a pressed (time, series, price) to the live log table."""
+    t = event.get("time")
+    price = event.get("price")
+    if t is None or price is None:
+        return  # press landed on empty area beyond the data - nothing to pin
+    _pins_pub.add(
+        new_table(
+            [
+                datetime_col("Time", [t]),
+                string_col("Series", [event.get("seriesId", "(between series)")]),
+                double_col("Price", [price]),
+            ]
+        )
+    )
+
+
+# --------------------------------------------------------------------------- #
+# Helpers that turn one press event into a small renderable table.
+# --------------------------------------------------------------------------- #
+def _series_snapshot(event: dict):
+    """Unpack the event's ``seriesData`` into a tidy (Series, Field, Value) table.
+
+    ``seriesData`` maps each series id to its value at the pressed time: a single
+    float for line/area/baseline/histogram series, or an OHLC dict for
+    candlestick/bar series. We unpack an OHLC dict into four rows so both shapes
+    render in one table.
+    """
+    series_data = event.get("seriesData", {}) or {}
+    series, fields, values = [], [], []
+    for sid, val in series_data.items():
+        if isinstance(val, dict):
+            for field in ("open", "high", "low", "close"):
+                if field in val:
+                    series.append(str(sid))
+                    fields.append(field)
+                    values.append(float(val[field]))
+        else:
+            series.append(str(sid))
+            fields.append("value")
+            values.append(float(val))
+    if not series:
+        series, fields, values = ["(no series under cursor)"], ["-"], [float("nan")]
+    return new_table(
+        [
+            string_col("Series", series),
+            string_col("Field", fields),
+            double_col("Value", values),
+        ]
+    )
+
+
+def _window(event: dict):
+    """Filter the raw data to a +/- 10-day window around the pressed time."""
+    t = event.get("time")
+    if t is None:
+        return candles.where("false")  # empty
+    # `t` is a real Deephaven Instant; reference it directly in the formula.
+    return candles.where("Timestamp >= (t - 'PT240H') && Timestamp <= (t + 'PT240H')")
+
+
+# --------------------------------------------------------------------------- #
+# Live summary of the pinned log - counts and averages, recomputed as it ticks.
+# --------------------------------------------------------------------------- #
+@ui.component
+def pinned_summary():
+    prices = ui.use_column_data(pinned.view("Price")) or []
+    count = len(prices)
+    if count == 0:
+        return ui.badge("No levels pinned yet", variant="neutral")
+    avg = sum(prices) / count
+    return ui.flex(
+        ui.badge(f"{count} pinned", variant="positive"),
+        ui.badge(f"avg {avg:.2f}", variant="info"),
+        ui.badge(f"low {min(prices):.2f}", variant="info"),
+        ui.badge(f"high {max(prices):.2f}", variant="info"),
+        gap="size-100",
+        wrap=True,
+        flex_grow=0,
+    )
+
+
+# --------------------------------------------------------------------------- #
+# Inspector - reacts to the most recent single-click.
+# --------------------------------------------------------------------------- #
+@ui.component
+def inspector(selected: dict | None):
+    # Hooks must run unconditionally and in the same order every render, so
+    # build the snapshot via use_memo before any early return.
+    snapshot = ui.use_memo(
+        lambda: _series_snapshot(selected) if selected else None,
+        [selected],
+    )
+
+    if not selected:
+        return ui.illustrated_message(
+            ui.icon("vsInspect"),
+            ui.heading("Click the chart"),
+            ui.content(
+                "Single-click a series to inspect that moment. "
+                "Shift-click or double-click to pin it."
+            ),
+            width="100%",
+        )
+
+    series = selected.get("seriesId", "(between series)")
+    price = selected.get("price")
+    t = selected.get("time")
+    pane = selected.get("paneIndex")
+
+    chips = [
+        ui.badge(f"series: {series}", variant="purple"),
+        ui.badge(
+            f"price: {price:.2f}" if price is not None else "price: -",
+            variant="info",
+        ),
+    ]
+    if t is not None:
+        chips.append(ui.badge(f"time: {t}", variant="neutral"))
+    if pane is not None:
+        chips.append(ui.badge(f"pane: {pane}", variant="neutral"))
+
+    # Modifier keys - show which were held, to advertise the shift-to-pin trick.
+    held = [k for k in ("shift", "ctrl", "meta", "alt") if selected.get(f"{k}Key")]
+    mods = ui.badge(
+        "modifiers: " + (", ".join(held) if held else "none"),
+        variant=("positive" if held else "neutral"),
+    )
+
+    return ui.flex(
+        ui.heading("Inspecting press", level=4),
+        ui.flex(*chips, mods, gap="size-100", wrap=True, flex_grow=0),
+        ui.text(
+            "Series values at this instant (unpacked from the event's seriesData):"
+        ),
+        ui.table(snapshot, density="compact"),
+        direction="column",
+        gap="size-100",
+    )
+
+
+# --------------------------------------------------------------------------- #
+# Drill-down - raw rows near the clicked time.
+# --------------------------------------------------------------------------- #
+@ui.component
+def drilldown(selected: dict | None):
+    has_time = bool(selected) and selected.get("time") is not None
+    windowed = ui.use_memo(
+        lambda: _window(selected) if has_time else None,
+        [selected],
+    )
+    if not has_time:
+        return ui.illustrated_message(
+            ui.icon("vsListFilter"),
+            ui.heading("No window yet"),
+            ui.content("Click a point on the chart to filter the raw data around it."),
+            width="100%",
+        )
+    return ui.flex(
+        ui.text("Raw rows within +/- 10 days of the click:"),
+        ui.table(
+            windowed,
+            reverse=True,
+            front_columns=["Timestamp", "Close", "Volume", "Ema"],
+            density="compact",
+        ),
+        direction="column",
+        gap="size-100",
+    )
+
+
+# --------------------------------------------------------------------------- #
+# The dashboard itself.
+# --------------------------------------------------------------------------- #
+@ui.component
+def events_dashboard():
+    selected, set_selected = ui.use_state(None)
+
+    def handle_press(event: dict):
+        set_selected(event)
+        # Power-user shortcut: shift-click pins without needing a double-click.
+        if event.get("shiftKey"):
+            _pin(event)
+
+    def handle_double(event: dict):
+        _pin(event)
+
+    chart = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.candlestick(
+                candles,
+                timestamp="Timestamp",
+                open="Open",
+                high="High",
+                low="Low",
+                close="Close",
+                title="Price",
+            ),
+            tvl.line(
+                candles,
+                timestamp="Timestamp",
+                value="Ema",
+                title="EMA",
+            ),
+            on_press=handle_press,
+            on_double_press=handle_double,
+        ),
+        [],
+    )
+
+    intro = ui.markdown(
+        """
+### Press-Event Explorer
+
+Every panel here is driven by **chart clicks** - no other input.
+
+- **Single-click** a series -> *inspect* that moment (Inspector).
+- **Shift-click** or **double-click** -> *pin* it to the live log (Pinned levels).
+
+The Inspector unpacks the event's `seriesData`: the candle series resolves to an
+**OHLC dict**, the EMA line to a single **value**, both at the instant you
+clicked. The Drill-down filters the raw table to a window around that time. The
+Pinned log and its summary tick live as you click.
+"""
+    )
+
+    chart_panel = ui.panel(
+        ui.flex(intro, chart, direction="column", height="100%"),
+        title="Candles - click to explore",
+    )
+
+    inspector_panel = ui.panel(inspector(selected), title="Inspector")
+
+    drilldown_panel = ui.panel(drilldown(selected), title="Drill-down (window)")
+
+    pinned_panel = ui.panel(
+        ui.flex(
+            pinned_summary(),
+            ui.table(pinned, reverse=True, density="compact"),
+            direction="column",
+            gap="size-100",
+        ),
+        title="Pinned levels (live)",
+    )
+
+    return ui.column(
+        ui.row(chart_panel, inspector_panel, height=2),
+        ui.row(drilldown_panel, pinned_panel, height=1),
+    )
+
+
+tvl_events_demo = ui.dashboard(events_dashboard())
diff --git a/plugins/tradingview-lightweight/app.d/events_demos.app b/plugins/tradingview-lightweight/app.d/events_demos.app
new file mode 100644
index 000000000..578f9e9fb
--- /dev/null
+++ b/plugins/tradingview-lightweight/app.d/events_demos.app
@@ -0,0 +1,7 @@
+type=script
+scriptType=python
+enabled=true
+id=tvl.demos.events
+name=TVL Event Demos
+file_0=events_demo.py
+file_1=marker_tool_demo.py
diff --git a/plugins/tradingview-lightweight/app.d/marker_tool_demo.py b/plugins/tradingview-lightweight/app.d/marker_tool_demo.py
new file mode 100644
index 000000000..df94d3011
--- /dev/null
+++ b/plugins/tradingview-lightweight/app.d/marker_tool_demo.py
@@ -0,0 +1,182 @@
+"""Marker-drawing tool: click the chart to stamp markers, driven through a table.
+
+Pick a marker tool from the toolbar (Buy / Sell / Note), then click a spot on
+the chart. The press event's ``time`` is appended as a row to a live
+``table_publisher`` table. That table is wired to the chart with
+``markers_from_table``, so the new row immediately renders as a marker on the
+chart. The flow is entirely:
+
+    button selects a tool  ->  press the chart  ->  publish a row to a table
+                           ->  the table drives the chart's markers
+
+The markers table is shown alongside the chart so you can watch rows land and
+see that the chart's markers are column-driven, not hard-coded.
+
+Data is the deterministic ``tvl.data.ohlc`` candle series. Load with:
+
+    python tools/plugin_builder.py --js --reinstall --server tradingview-lightweight \
+        -- -Ddeephaven.application.dir=$(pwd)/plugins/tradingview-lightweight/app.d
+"""
+
+from __future__ import annotations
+
+from deephaven import ui, new_table
+from deephaven import dtypes as dht
+from deephaven.column import datetime_col, string_col
+from deephaven.stream.table_publisher import table_publisher
+from deephaven.plot import tradingview_lightweight as tvl
+
+
+# --------------------------------------------------------------------------- #
+# Candle data to draw on.
+# --------------------------------------------------------------------------- #
+candles = tvl.data.ohlc(ticking=False)
+
+
+# --------------------------------------------------------------------------- #
+# The marker tools. Each maps to the camelCase position/shape values that
+# Lightweight Charts expects in a table-driven marker spec.
+# --------------------------------------------------------------------------- #
+TOOLS = {
+    "buy": {
+        "text": "Buy",
+        "position": "belowBar",
+        "shape": "arrowUp",
+        "color": "#26a69a",
+    },
+    "sell": {
+        "text": "Sell",
+        "position": "aboveBar",
+        "shape": "arrowDown",
+        "color": "#ef5350",
+    },
+    "note": {
+        "text": "Note",
+        "position": "aboveBar",
+        "shape": "circle",
+        "color": "#2962ff",
+    },
+}
+
+
+# --------------------------------------------------------------------------- #
+# Live markers table. Each press appends one row; tailing the blink stream
+# accumulates them so the marker set grows as the user clicks.
+# --------------------------------------------------------------------------- #
+_markers_blink, _markers_pub = table_publisher(
+    "Drawn markers",
+    {
+        "Time": dht.Instant,
+        "Label": dht.string,
+        "Position": dht.string,
+        "Shape": dht.string,
+        "Color": dht.string,
+    },
+)
+markers_table = _markers_blink.tail(500)
+
+
+# --------------------------------------------------------------------------- #
+# The chart reads markers straight from the table via a per-row marker spec.
+# Created once (module scope) so its viewport survives every new marker.
+# --------------------------------------------------------------------------- #
+marker_spec = tvl.markers_from_table(
+    markers_table,
+    timestamp="Time",
+    text_column="Label",
+    position_column="Position",
+    shape_column="Shape",
+    color_column="Color",
+)
+
+
+@ui.component
+def marker_tool():
+    # Display state for the toolbar + a ref the press handler reads, so the
+    # memoized chart's handler always sees the *current* tool without the
+    # chart having to be rebuilt (which would reset zoom).
+    tool, set_tool = ui.use_state("buy")
+    tool_ref = ui.use_ref("buy")
+
+    def select_tool(key: str | None):
+        if key:
+            tool_ref.current = key
+            set_tool(key)
+
+    def handle_press(event: dict):
+        t = event.get("time")
+        if t is None:
+            return  # pressed empty area beyond the data - nothing to stamp
+        spec = TOOLS[tool_ref.current]
+        _markers_pub.add(
+            new_table(
+                [
+                    datetime_col("Time", [t]),
+                    string_col("Label", [spec["text"]]),
+                    string_col("Position", [spec["position"]]),
+                    string_col("Shape", [spec["shape"]]),
+                    string_col("Color", [spec["color"]]),
+                ]
+            )
+        )
+
+    chart = ui.use_memo(
+        lambda: tvl.candlestick(
+            candles,
+            timestamp="Timestamp",
+            open="Open",
+            high="High",
+            low="Low",
+            close="Close",
+            marker_spec=marker_spec,
+            on_press=handle_press,
+        ),
+        [],
+    )
+
+    toolbar = ui.radio_group(
+        ui.radio("[green] Buy", value="buy"),
+        ui.radio("[red] Sell", value="sell"),
+        ui.radio("[blue] Note", value="note"),
+        value=tool,
+        on_change=select_tool,
+        orientation="horizontal",
+        label="Marker tool",
+    )
+
+    intro = ui.markdown(
+        f"""
+### Marker Drawing Tool
+
+1. Pick a tool below. **Currently armed: `{TOOLS[tool]["text"]}`**
+2. Click anywhere on the candles - the press time is published as a row.
+3. That row drives a marker on the chart via `markers_from_table`.
+
+The table on the right is the single source of truth for the markers.
+"""
+    )
+
+    left = ui.flex(
+        intro,
+        toolbar,
+        chart,
+        direction="column",
+        gap="size-100",
+        height="100%",
+    )
+
+    right = ui.flex(
+        ui.heading("Markers table (drives the chart)", level=4),
+        ui.text("Each click appends one row. The chart re-reads this table live."),
+        ui.table(markers_table, reverse=True, density="compact"),
+        direction="column",
+        gap="size-100",
+    )
+
+    return ui.row(
+        ui.panel(left, title="Draw markers"),
+        ui.panel(right, title="Markers source table"),
+    )
+
+
+tvl_marker_tool = ui.dashboard(marker_tool())
diff --git a/plugins/tradingview-lightweight/conf.py b/plugins/tradingview-lightweight/conf.py
new file mode 100644
index 000000000..7ddf5892c
--- /dev/null
+++ b/plugins/tradingview-lightweight/conf.py
@@ -0,0 +1,49 @@
+# Configuration file for the Sphinx documentation builder.
+#
+# For the full list of built-in configuration values, see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+import os
+import sys
+
+sys.path.append(os.path.abspath("../../sphinx_ext"))
+
+# -- Project information -----------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
+
+project = "deephaven"
+copyright = "2024, Deephaven Data Labs"
+author = "Deephaven Data Labs"
+# we don't use release but sphinx requires it
+release = "0.1.0"
+
+# -- General configuration ---------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
+
+extensions = [
+    "myst_parser",
+    "sphinx.ext.autodoc",
+    "sphinx.ext.napoleon",
+    "deephaven_markdown_translator",
+    "sphinx_markdown_builder",
+    "sphinx_autodoc_typehints",
+    "deephaven_autodoc",
+    "deephaven_code_block",
+]
+
+source_suffix = [".rst", ".md"]  # Can use either rst or markdown files as input
+
+# show hints in the description so that the function definition is not cluttered
+autodoc_typehints = "description"
+
+# exclude build directory
+exclude_patterns = ["build", "Thumbs.db", ".DS_Store"]
+
+# options for sphinx_autodoc_typehints
+always_use_bars_union = True
+
+myst_all_links_external = True
+
+from deephaven_server import Server
+
+# need a server instance to pull types from the autodocs
+Server(port=10075)
diff --git a/plugins/tradingview-lightweight/docs/README.md b/plugins/tradingview-lightweight/docs/README.md
new file mode 100644
index 000000000..9ba1d1e3d
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/README.md
@@ -0,0 +1,77 @@
+# Deephaven TradingView Lightweight Charts
+
+Deephaven TradingView Lightweight Charts is a Python plotting plugin for Deephaven built on the [TradingView lightweight-charts](https://tradingview.github.io/lightweight-charts/) library. It is less general-purpose than `deephaven.plot.express`. The focus is financial charts and the layouts traders expect: candlesticks, bars, area / baseline / line series, histograms, multi-pane stacks, and yield curves. Viewport-aware downsampling and server-side autobinning keep render-time low on multi-million-row tables.
+
+## Quickstart
+
+Install via pip (or use a Docker image that already includes the plugin):
+
+```bash
+pip install deephaven-plugin-tradingview-lightweight
+```
+
+Inside Deephaven, build a two-pane chart with an OHLC candlestick + EMA overlay on top, and a volume histogram below:
+
+```python order=chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+chart = tvl.chart(
+    tvl.candlestick(ohlc),
+    tvl.line(ohlc, timestamp="Timestamp", value="Ema"),
+    tvl.histogram(ohlc, timestamp="Timestamp", value="Volume", pane=1),
+    pane_stretch_factors=[3, 1],
+)
+```
+
+## Key Features
+
+- **Live Table Support**: Direct integration with real-time Deephaven tables, so charts update as the underlying data ticks.
+- **Viewport-Aware Downsampling**: Pixel-accurate, whitespace-based downsampling that keeps panning and zooming smooth on multi-million-row series.
+- **Server-Side Autobinning**: Histograms compute bin widths and counts directly in the Deephaven query engine, avoiding round-trips of raw data.
+- **Multi-Pane Stacks**: Price, volume, and indicator series can be stacked into separate panes with independent height ratios via `pane_index`.
+- **Multiple Price Scales**: Left, right, and overlay price scales, with per-scale tick mark density and a configurable default scale for unbound series.
+- **Annotations**: First-class support for watermarks, price lines, and markers, including `markers_from_table` for table-driven annotation streams.
+
+## Chart Types
+
+<CardList>
+
+[![Area chart - A line with a filled region below it](_assets/plot_icons/area.svg)](area.md)
+[![Bar chart - Open/high/low/close bars for a financial instrument](_assets/plot_icons/bar.svg)](bar.md)
+[![Baseline chart - A two-color area split at a baseline value](_assets/plot_icons/baseline.svg)](baseline.md)
+[![Candlestick chart - Open/high/low/close candles for a financial instrument](_assets/plot_icons/candlestick.svg)](candlestick.md)
+[![Custom numeric - Hand-rolled series with custom numeric data](_assets/plot_icons/custom-numeric.svg)](custom-numeric.md)
+[![Histogram - Distribution of values displayed as bars](_assets/plot_icons/histogram.svg)](histogram.md)
+[![Line chart - A line connecting numeric values over time](_assets/plot_icons/line.svg)](line.md)
+[![Options chart - Option chain payoff or implied-vol surface](_assets/plot_icons/options-chart.svg)](options-chart.md)
+[![Yield curve - Interest rate vs. maturity for a set of instruments](_assets/plot_icons/yield-curve.svg)](yield-curve.md)
+
+</CardList>
+
+## Terminology
+
+The documentation for Deephaven TradingView Lightweight Charts routinely uses some common terms to help clarify how charts are intended to be composed:
+
+- **Pane**: A horizontally stretched section of the chart that shares the same time scale as every other pane but has its own price scale. A common layout is a price pane on top and a volume pane below; `pane_index` selects which pane a series renders into.
+- **Series**: A single drawn element on the chart: a candlestick, line, area, bar, baseline, or histogram series. A chart can contain many series across one or more panes.
+- **Price scale**: The vertical axis a series is drawn against. Each pane has a left and right price scale, plus optional overlay scales identified by `price_scale_id`.
+- **Price line**: A horizontal line drawn at a specific price level, optionally labeled. Useful for marking last close, breakeven, stop-loss, etc.
+- **Marker**: An annotation pinned to a specific time on a specific series: an arrow, circle, or labeled shape used to highlight events such as trades, news, or signals.
+- **Watermark**: Static text or an image drawn behind the chart, typically used for branding or to label the instrument being shown.
+- **Time scale**: The horizontal time axis shared by all panes. Tick mark density and business-day handling are configured here.
+- **Downsampling**: The viewport-aware reduction of plotted points so that the displayed series never contains more visually distinguishable points than the chart has horizontal pixels. Lossless at the visible resolution.
+- **Autobin**: Server-side selection of histogram bin width and edges from the data, avoiding the need to specify `bin_width` manually.
+
+## Contributing
+
+We welcome contributions to Deephaven TradingView Lightweight Charts! If you encounter any issues, have ideas for improvements, or would like to add new features, please open an issue or submit a pull request on the [GitHub repository](https://github.com/deephaven/deephaven-plugins).
+
+## License
+
+Deephaven's TradingView Lightweight Charts plugin is licensed under the [Apache License 2.0](https://github.com/deephaven/deephaven-plugins/blob/main/plugins/tradingview-lightweight/LICENSE). You are free to use, modify, and distribute this library in compliance with the terms of the license.
+
+## Acknowledgments
+
+We would like to express our gratitude to the TradingView team for creating the [lightweight-charts](https://tradingview.github.io/lightweight-charts/) library and making it open-source. Their work forms the foundation of the Deephaven TradingView Lightweight Charts plugin.
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new file mode 100644
index 000000000..67eba8c47
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diff --git a/plugins/tradingview-lightweight/docs/area.md b/plugins/tradingview-lightweight/docs/area.md
new file mode 100644
index 000000000..a9198ce9c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/area.md
@@ -0,0 +1,193 @@
+<!-- coverage-seen-elsewhere:
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  on_press -> events.md
+  on_double_press -> events.md
+  crosshair_mode -> styling.md
+  time_visible -> time-scale.md
+  watermark_text -> watermark.md
+  line_style -> line.md
+  line_type -> line.md
+  line_visible -> line.md
+  point_markers_visible -> line.md
+  point_markers_radius -> line.md
+  crosshair_marker_visible -> line.md
+  crosshair_marker_radius -> line.md
+  crosshair_marker_border_color -> line.md
+  crosshair_marker_background_color -> line.md
+  crosshair_marker_border_width -> line.md
+  last_price_animation -> line.md
+  last_value_visible -> titles-legends.md
+  title -> titles-legends.md
+  visible -> titles-legends.md
+  price_scale_id -> price-scale.md
+  price_format -> price-formats.md
+  price_line_visible -> price-lines.md
+  price_line_source -> price-lines.md
+  price_line_width -> price-lines.md
+  price_line_color -> price-lines.md
+  price_line_style -> price-lines.md
+  base_line_visible -> price-scale.md
+  base_line_color -> price-scale.md
+  base_line_width -> price-scale.md
+  base_line_style -> price-scale.md
+  auto_scale -> price-scale.md
+  scale_margin_top -> price-scale.md
+  scale_margin_bottom -> price-scale.md
+  scale_mode -> price-scale.md
+  scale_invert -> price-scale.md
+  scale_align_labels -> price-scale.md
+  scale_border_visible -> price-scale.md
+  scale_border_color -> price-scale.md
+  scale_text_color -> price-scale.md
+  scale_entire_text_only -> price-scale.md
+  scale_visible -> price-scale.md
+  scale_ticks_visible -> price-scale.md
+  scale_minimum_width -> price-scale.md
+  scale_ensure_edge_tick_marks_visible -> price-scale.md
+  pane -> multi-pane.md
+-->
+
+# Area Chart
+
+An area chart is a line chart with a vertical gradient fill underneath. The fill shows the magnitude of the value as well as its trajectory. Use it for single-series time series where you want to emphasize how much, such as equity curves, cumulative volume, or account balance, rather than the shape of small fluctuations.
+
+The fill is a vertical gradient between `top_color` (just below the line) and `bottom_color` (at the chart bottom).
+
+## What are area charts useful for?
+
+- **Emphasizing magnitude**: The shaded region under the line shows how big the value is, in addition to where it's going.
+- **Single-series time series**: When there is only one quantity to plot, an area chart carries more visual weight than a bare line and still reads as a trend at a glance.
+- **Cumulative quantities**: Volume traded, P&L, balance, headcount, and anything else that accumulates suits an area chart.
+- **Dashboard tiles**: A filled area stays legible on small chart tiles where the line alone would be too thin to register.
+
+## Examples
+
+### A basic area chart
+
+Pass a table with a `timestamp` column and a `value` column. With `tvl.data.values()` (columns `Timestamp` and `Value`) the defaults already match, but they are shown here explicitly for clarity.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+area = tvl.area(data, timestamp="Timestamp", value="Value")
+```
+
+The line traces the value; the area below it fades from the top color to the bottom color.
+
+### Customize the gradient
+
+`top_color` is the gradient stop at the line; `bottom_color` is the stop at the bottom of the chart. Both accept a Deephaven theme color (e.g. `"orange-800"`, `"accent-300"`), a hex code (`"#1f8a70"`), a named CSS color (`"crimson"`), or an `rgb()`/`rgba()` string for transparency. Theme colors adapt automatically when the user switches themes; hardcoded values do not.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+area = tvl.area(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    top_color="orange-800",
+    bottom_color="transparent",
+)
+```
+
+The gradient runs from a deep amber at the line down to fully transparent at the chart bottom.
+
+### Line width
+
+`line_width` sets the outline thickness as an integer 1-4 (the LWC default is 3). Wider outlines stand out on dashboards; thinner outlines disappear into the gradient on detail charts.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+area = tvl.area(data, timestamp="Timestamp", value="Value", line_width=1)
+```
+
+The outline is now one pixel wide.
+
+### One area per group with `by`
+
+Set `by` to a partition column and the chart draws one area per unique value, each with its own auto-assigned color from the user's theme palette. This is useful for comparisons, but note that the areas overlay rather than stack arithmetically.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.stocks()
+
+area = tvl.area(
+    data,
+    timestamp="Timestamp",
+    value="Price",
+    by="Sym",
+)
+```
+
+Each symbol gets its own translucent area, automatically colored.
+
+### Invert the filled area
+
+`invert_filled_area=True` flips the gradient so the area is drawn above the line instead of below it. This is the typical layout for "deficit" or "below-baseline" views, where the value of interest is the gap between the line and the top of the chart.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+area = tvl.area(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    invert_filled_area=True,
+)
+```
+
+The shaded region now extends from the line up to the top of the chart rather than down to the bottom.
+
+### Line color and a relative gradient
+
+`line_color` sets the outline color independently of the fill. `relative_gradient=True` anchors the gradient stops to the series' value range rather than the visible pane, so the fill keeps consistent colors as the chart scrolls.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+area = tvl.area(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    line_color="accent-500",
+    relative_gradient=True,
+)
+```
+
+### Per-point colors from columns
+
+`line_color_column`, `top_color_column`, and `bottom_color_column` drive the line and the two gradient stops from per-row table columns of color strings.
+
+```python order=area,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values().update_view(
+    [
+        "LineCol = Value >= 100 ? `#26a69a` : `#ef5350`",
+        "TopCol = Value >= 100 ? `rgba(38,166,154,0.4)` : `rgba(239,83,80,0.4)`",
+        "BotCol = `rgba(0,0,0,0)`",
+    ]
+)
+
+area = tvl.area(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    line_color_column="LineCol",
+    top_color_column="TopCol",
+    bottom_color_column="BotCol",
+)
+```
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.area
+```
diff --git a/plugins/tradingview-lightweight/docs/autobin.md b/plugins/tradingview-lightweight/docs/autobin.md
new file mode 100644
index 000000000..a8e4bb429
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/autobin.md
@@ -0,0 +1,165 @@
+<!-- coverage-seen-elsewhere:
+  large_prices -> example-data.md
+  values -> example-data.md
+  volume -> example-data.md
+-->
+
+# Autobinning
+
+Autobinning is TVL's server-side time-bucket aggregation for histograms, candlesticks, and bars. Unlike the min/max downsampling used by Line / Area / Baseline (see [downsampling](downsampling.md)), OHLC and histogram series can't be thinned out by dropping points; they need true aggregation. Autobinning runs that aggregation in the Deephaven query engine: `update_view` to compute a bin column, `agg_by` to reduce, snap the result back to the original time column name, and ship it to the chart.
+
+Use this page when you have a high-rate tick stream and want a histogram or candlestick chart over an automatically-chosen bin width, or when you want to override the chosen bin width manually.
+
+## What is autobinning useful for?
+
+- **Histograms over raw ticks**: A raw trade stream can be aggregated server-side to per-minute volume bars without writing the binning by hand.
+- **Candle / bar charts at arbitrary cadences**: Pass a raw price tick table; the chart aggregates first/max/min/last per bin for you.
+- **Zoom-responsive cadence**: As the user zooms in, the bin width auto-refines to a finer "nice" duration so the chart stays informative without showing sub-pixel bars.
+- **Server-side cost**: All aggregation happens in the Deephaven engine, so the browser never sees the raw ticks.
+
+## API surface
+
+Every aggregating series (`histogram`, `candlestick`, `bar`) accepts three parameters:
+
+| param | meaning |
+|---|---|
+| `auto_bin` | Tri-state: `None` (default) auto-detects; `True` forces autobinning on; `False` opts out. |
+| `bin_width` | ISO-8601 duration override (e.g. `"PT1S"`, `"PT5M"`, `"PT1H"`, `"P1D"`). |
+| `bin_count` | Target number of bins (default 5000). |
+| `agg` | (Histogram only) Reduction mode: `"sum"`, `"count"`, `"avg"`, `"last"`. |
+
+Default policy: when `auto_bin is None`, the chart auto-enables binning if the input table exceeds the `AUTO_BIN_THRESHOLD` (5000 rows). When `auto_bin=True`, binning is forced regardless of row count. When `auto_bin=False`, the chart uses the table as-is and assumes it's already aggregated.
+
+## Algorithm
+
+The source of truth is `src/deephaven/plot/tradingview_lightweight/auto_bin.py`. The pipeline is:
+
+1. **`target_bins_for_width(width_px, actual_width_px)`**: compute the number of bins the chart can usefully show, based on the chart's pixel width and a target bar-pixel-width of `BAR_PX = 8`. Defaults to `TARGET_BINS = DEFAULT_WIDTH_PX // BAR_PX = 2000 // 8 = 250` when the width isn't known. Clamps by `actual_width_px / MIN_BAR_PX (=5)` so each bar stays above 5px even when the cached pixel-width-bucket overshoots.
+2. **`nice_bin_width(range_ns, target_bins)`**: divide the time range by the target bin count, then snap the result up to the next "nice" duration from `NICE_BIN_WIDTHS_NS` (1ns, 100ns, 1µs, 100µs, 1ms, 10ms, 100ms, 1s, 5s, 15s, 30s, 1m, 5m, 15m, 30m, 1h, 4h, 12h, 1d, 7d, 30d, 90d, 365d).
+3. **`build_histogram_view` / `build_ohlc_view`**: apply `upperBin(time, bin_width)` then `agg_by` over each bin, restore the time column name, sort by time. When the visible window is strictly inside the data range, the view is built as `head_anchor + body + tail_anchor` so `fix_left_edge` / `fix_right_edge` have something to clamp to.
+
+The visible range listener triggers a re-aggregation when the bin count drifts outside the range `[MIN_VISIBLE_BINS=80, target_bins * MAX_VISIBLE_BINS_RATIO=2x]`.
+
+## Examples
+
+### Build a histogram over a value-time series
+
+Pass a raw value-by-time table to `histogram()`. With default `auto_bin=None` and a small (90-row) `tvl.data.values()` table, autobinning stays off and each row becomes a bar. Force `auto_bin=True` to opt in.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.histogram(values, timestamp="Timestamp", value="Value", auto_bin=True, agg="sum")
+```
+
+Without `auto_bin=True`, the small table renders without aggregation; the parameter is most useful on tables that genuinely tick fast.
+
+### Override the bin width
+
+Set `bin_width` to an ISO-8601 duration string (`"PT5M"` = 5 minutes; `"P1D"` = 1 day) to force a specific cadence. This bypasses `nice_bin_width()` and uses the duration exactly.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.histogram(
+    values,
+    timestamp="Timestamp",
+    value="Value",
+    auto_bin=True,
+    bin_width="P1D",
+    agg="sum",
+)
+```
+
+Valid duration patterns: `PnD`, `PTnHnMnS`, e.g. `"PT1S"`, `"PT5M"`, `"PT1H"`, `"P1D"`.
+
+### Override the bin count
+
+`bin_count` sets the target number of bins; the algorithm divides the data's time range by `bin_count` and snaps the result up to a "nice" duration. Use it to control density without committing to a specific cadence.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.histogram(
+    values,
+    timestamp="Timestamp",
+    value="Value",
+    auto_bin=True,
+    bin_count=20,
+    agg="sum",
+)
+```
+
+`bin_count` and `bin_width` are mutually exclusive in effect. If both are set, `bin_width` wins.
+
+### Pick an aggregation reduction
+
+The `agg` parameter on `histogram` / `histogram` selects the per-bin reduction. `"sum"` (default) sums the value column; `"count"` counts the rows per bin (the value column is ignored for the reduction); `"avg"` averages; `"last"` takes the most recent value per bin.
+
+```python order=sum_chart,count_chart,avg_chart,last_chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+sum_chart = tvl.histogram(values, timestamp="Timestamp", value="Value", auto_bin=True, agg="sum")
+count_chart = tvl.histogram(values, timestamp="Timestamp", value="Value", auto_bin=True, agg="count")
+avg_chart = tvl.histogram(values, timestamp="Timestamp", value="Value", auto_bin=True, agg="avg")
+last_chart = tvl.histogram(values, timestamp="Timestamp", value="Value", auto_bin=True, agg="last")
+```
+
+Use `"sum"` for volume bars; `"count"` for trade counts; `"avg"` for mid-price binning; `"last"` for last-tick-per-bin snapshots.
+
+### Aggregating OHLC bars
+
+Candlestick and bar charts use a fixed reduction. `first(open)`, `max(high)`, `min(low)`, `last(close)` per bin. The `agg` parameter doesn't exist here. Use `auto_bin=True` and `bin_width=` to control the cadence.
+
+```python order=chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+chart = tvl.candlestick(ohlc, auto_bin=True, bin_width="P1D")
+```
+
+For high-rate tick input, this is the usual way to render a candle chart at a user-selected cadence.
+
+### Opt out of autobinning
+
+`auto_bin=False` disables the path entirely. The chart consumes the input table as-is. Use this when you've already aggregated upstream (e.g. via a Deephaven `time_window` view) and don't want the chart to re-aggregate.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.histogram(values, timestamp="Timestamp", value="Value", auto_bin=False)
+```
+
+Be aware: with `auto_bin=False` on a large raw tick table, the browser receives every row, and rendering performance degrades.
+
+## Current status
+
+`notes/todo.md` previously noted "autobin histogram not working yet." Inspecting `auto_bin.py` against the current series wiring, the `build_histogram_view` and `build_ohlc_view` functions are fully implemented (whitespace-anchored head/body/tail merge, ISO-8601 parsing, nice-bin-width snapping). The recent commits `62c568ea` ("whitespace downsample works okay") and `f45886bb` ("autobin histogram") indicate the path landed. The Python-side aggregation is wired through `histogram` (line 984+ of `series.py` references `HIST_AGGS`) and through both `candlestick` and `bar`. End-to-end the path appears working as of the current commit; if you hit a regression, file an issue and capture the relevant `auto_bin.py` invocation in the bug report.
+
+## How tunables compose
+
+- **`width` on `chart()`** indirectly controls `target_bins_for_width`, since the client passes the chart's pixel width to the server's `target_bins` computation.
+- **`bin_count`** overrides the computed target.
+- **`bin_width`** bypasses the snapping logic and uses the user's duration directly.
+- **`fix_left_edge` / `fix_right_edge`** are honored: the head/tail anchor rows give them something to clamp to even when the visible window is inside the data range.
+
+For the cost trade-offs (server-side aggregation vs. client-side rendering), see [large-data](large-data.md).
+
+## API Reference
+
+The `auto_bin`, `bin_width`, `bin_count`, and `agg` parameters are accepted by each binnable chart type. See the per-type API references for the full signatures:
+
+- [`tvl.histogram`](histogram.md#api-reference)
+- [`tvl.candlestick`](candlestick.md#api-reference)
+- [`tvl.bar`](bar.md#api-reference)
diff --git a/plugins/tradingview-lightweight/docs/bar.md b/plugins/tradingview-lightweight/docs/bar.md
new file mode 100644
index 000000000..3f3ee158f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/bar.md
@@ -0,0 +1,155 @@
+<!-- coverage-seen-elsewhere:
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  on_press -> events.md
+  on_double_press -> events.md
+  auto_bin -> autobin.md
+  bin_width -> autobin.md
+  bin_count -> autobin.md
+  crosshair_mode -> styling.md
+  time_visible -> time-scale.md
+  watermark_text -> watermark.md
+  visible -> titles-legends.md
+  last_value_visible -> titles-legends.md
+  price_scale_id -> price-scale.md
+  price_format -> price-formats.md
+  price_line_visible -> price-lines.md
+  price_line_source -> price-lines.md
+  price_line_width -> price-lines.md
+  price_line_color -> price-lines.md
+  price_line_style -> price-lines.md
+  base_line_visible -> price-scale.md
+  base_line_color -> price-scale.md
+  base_line_width -> price-scale.md
+  base_line_style -> price-scale.md
+  auto_scale -> price-scale.md
+  scale_margin_top -> price-scale.md
+  scale_margin_bottom -> price-scale.md
+  scale_mode -> price-scale.md
+  scale_invert -> price-scale.md
+  scale_align_labels -> price-scale.md
+  scale_border_visible -> price-scale.md
+  scale_border_color -> price-scale.md
+  scale_text_color -> price-scale.md
+  scale_entire_text_only -> price-scale.md
+  scale_visible -> price-scale.md
+  scale_ticks_visible -> price-scale.md
+  scale_minimum_width -> price-scale.md
+  scale_ensure_edge_tick_marks_visible -> price-scale.md
+  color_column -> histogram.md
+  pane -> multi-pane.md
+  by -> multi-series.md
+-->
+
+# Bar (OHLC) Chart
+
+A bar chart renders each OHLC interval as a vertical range bar with a short tick on the left for the open and a short tick on the right for the close. Use it when you want the readability of OHLC data but prefer a thinner, less ink-heavy rendering than candlesticks. It works well for very dense intraday charts, and when you plan to layer markers on top.
+
+Like candlesticks, bars are color-coded by direction: an up bar has the close above the open, a down bar has the close below the open. Because the body is just two ticks instead of a filled rectangle, you can fit many more bars in the same horizontal space.
+
+## What are OHLC bar charts useful for?
+
+- **Dense intraday charts**: Bars take less horizontal pixel space than candles, so a 1-minute chart over a full session stays readable.
+- **Overlays and annotations**: A thinner price track leaves room for markers, price lines, and secondary series without visual conflict.
+- **Western technical analysis**: Many classical Western (vs. Japanese) chart conventions assume OHLC bars and read them more naturally than candles.
+- **Volatility scans**: Long vertical bars with ticks close together flag wide-range, indecisive periods.
+
+## Examples
+
+### A basic bar chart
+
+`tvl.bar` consumes the same OHLC table layout as `tvl.candlestick`. The `tvl.data.ohlc()` helper already has the canonical column names so the call is a one-liner.
+
+```python order=bar,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+bar = tvl.bar(data)
+```
+
+Each row in `data` becomes one vertical bar with an open tick on the left and a close tick on the right. When `up_color` / `down_color` are not provided, the chart pulls them from the active Deephaven theme palette so the same code reads correctly in both light and dark themes.
+
+### Map non-default OHLC column names
+
+When your table uses different column names (say `Ts`/`O`/`H`/`L`/`C` from a custom upstream join), pass them as kwargs. The chart only reads the columns you point at.
+
+```python order=bar,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc().rename_columns(["Ts=Timestamp", "O=Open", "H=High", "L=Low", "C=Close"])
+
+bar = tvl.bar(
+    data,
+    timestamp="Ts",
+    open="O",
+    high="H",
+    low="L",
+    close="C",
+)
+```
+
+### Customize up and down colors
+
+`up_color` and `down_color` set the bar color for up and down intervals. The bar (range line plus open/close ticks) inherits a single color per bar, unlike candlesticks where bodies and borders can diverge.
+
+```python order=bar,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+bar = tvl.bar(
+    data,
+    up_color="seafoam-800",
+    down_color="magenta-600",
+)
+```
+
+Both `up_color` and `down_color` accept a Deephaven theme color (e.g. `"seafoam-800"`, `"accent-300"`), a hex code (`"#26a69a"`), a named CSS color (`"crimson"`), or an `rgb()`/`rgba()` string for transparency. Theme colors adapt automatically when the user switches themes; hardcoded values do not. Leave them unset to inherit the active theme's palette.
+
+### Set a chart title
+
+`title` is the series legend label. Visible on hover and in the legend area. Use it whenever the chart will be embedded next to other content where the column names are not self-explanatory.
+
+```python order=bar,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+bar = tvl.bar(data, title="ES futures, 1m bars")
+```
+
+The legend now reads "ES futures, 1m bars".
+
+### Server-side autobinning
+
+Hand the chart a large OHLC table and TVL automatically aggregates it server-side into a viewport-friendly number of buckets. Override the bucket count or width via `bin_count` / `bin_width`, or set `auto_bin=False` to bypass it entirely for small tables.
+
+```python order=bar,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+bar = tvl.bar(data, auto_bin=True, bin_width="P7D")
+```
+
+See [autobin](autobin.md) for the full autobin surface: ISO-8601 duration grammar, when each `auto_bin` value is the right pick, and how the path interacts with the downsampler.
+
+### Thin bars and hidden open ticks
+
+Two bar-specific styling options trim the visual weight of each bar. `thin_bars=True` renders each bar with a narrower body, which is useful on very dense intraday charts; `open_visible=False` hides the short left "open" tick so each bar shows only the range line plus the right "close" tick, a cleaner look when the open price is not the focus.
+
+```python order=bar,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+bar = tvl.bar(
+    data,
+    thin_bars=True,
+    open_visible=False,
+)
+```
+
+The bars are now thinner and the left-side open tick is gone.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.bar
+```
diff --git a/plugins/tradingview-lightweight/docs/baseline.md b/plugins/tradingview-lightweight/docs/baseline.md
new file mode 100644
index 000000000..2c3b30817
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/baseline.md
@@ -0,0 +1,190 @@
+<!-- coverage-seen-elsewhere:
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  on_press -> events.md
+  on_double_press -> events.md
+  crosshair_mode -> styling.md
+  time_visible -> time-scale.md
+  watermark_text -> watermark.md
+  line_style -> line.md
+  line_type -> line.md
+  line_visible -> line.md
+  point_markers_visible -> line.md
+  point_markers_radius -> line.md
+  crosshair_marker_visible -> line.md
+  crosshair_marker_radius -> line.md
+  crosshair_marker_border_color -> line.md
+  crosshair_marker_background_color -> line.md
+  crosshair_marker_border_width -> line.md
+  last_price_animation -> line.md
+  last_value_visible -> titles-legends.md
+  title -> titles-legends.md
+  visible -> titles-legends.md
+  price_scale_id -> price-scale.md
+  price_format -> price-formats.md
+  price_line_visible -> price-lines.md
+  price_line_source -> price-lines.md
+  price_line_width -> price-lines.md
+  price_line_color -> price-lines.md
+  price_line_style -> price-lines.md
+  base_line_visible -> price-scale.md
+  base_line_color -> price-scale.md
+  base_line_width -> price-scale.md
+  base_line_style -> price-scale.md
+  auto_scale -> price-scale.md
+  scale_margin_top -> price-scale.md
+  scale_margin_bottom -> price-scale.md
+  scale_mode -> price-scale.md
+  scale_invert -> price-scale.md
+  scale_align_labels -> price-scale.md
+  scale_border_visible -> price-scale.md
+  scale_border_color -> price-scale.md
+  scale_text_color -> price-scale.md
+  scale_entire_text_only -> price-scale.md
+  scale_visible -> price-scale.md
+  scale_ticks_visible -> price-scale.md
+  scale_minimum_width -> price-scale.md
+  scale_ensure_edge_tick_marks_visible -> price-scale.md
+  pane -> multi-pane.md
+  by -> multi-series.md
+-->
+
+# Baseline Chart
+
+A baseline chart is an area chart split along a horizontal reference level: the portion *above* the baseline is filled with one color (typically green for "good"), the portion *below* with another (typically red for "bad"). Use it when the meaningful question is "are we above or below this number?", such as performance vs. a benchmark, P&L vs. zero, or latency vs. an SLA.
+
+The `base_value` parameter is the y-coordinate of the dividing line. By default it sits at 0, which is the right choice for P&L and other zero-centered quantities; set it explicitly when your baseline is a benchmark return, an SLA, or any non-zero reference.
+
+## What are baseline charts useful for?
+
+- **P&L and returns vs. zero**: Above the line is profit; below is loss. The color split makes runs of positive/negative days impossible to miss.
+- **Performance vs. a benchmark**: Set `base_value` to the benchmark's return and the chart immediately shows excess/deficit performance.
+- **SLA / threshold monitoring**: Latency, error rate, or any quantity with a "good vs. bad" threshold reads cleanly as a baseline.
+- **Index-relative views**: Anything reported as "vs. 100" or "vs. open" benefits from explicit above/below shading.
+
+## Examples
+
+### A basic baseline chart
+
+Pass a table with a `timestamp` column and a `value` column. With no `base_value` the chart uses 0 as the baseline. The `tvl.data.values()` series oscillates around 100, so for a meaningful split we set `base_value=100`.
+
+```python order=baseline,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+baseline = tvl.baseline(data, timestamp="Timestamp", value="Value", base_value=100.0)
+```
+
+Sections of the curve above 100 are shaded with the top color; sections below 100 with the bottom color.
+
+### Customize above/below line colors
+
+`top_line_color` and `bottom_line_color` set the outline color of the line itself when it's above/below the baseline. Color kwargs accept a Deephaven theme color (e.g. `"positive"`, `"seafoam-500"`, `"accent-300"`), a hex code (`"#1b5e20"`), a named CSS color (`"darkgreen"`), or an `rgb()`/`rgba()` string for transparency. Theme colors adapt automatically when the user switches themes; hardcoded values do not.
+
+```python order=baseline,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+baseline = tvl.baseline(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    base_value=100.0,
+    top_line_color="positive",
+    bottom_line_color="negative",
+)
+```
+
+The line uses the user's theme "positive" color above the baseline and "negative" color below.
+
+### Set the baseline at zero for P&L
+
+For a P&L series the natural baseline is 0. Gains above, losses below. Build a synthetic P&L by shifting the demo series and set `base_value=0`.
+
+```python order=baseline,pnl
+import deephaven.plot.tradingview_lightweight as tvl
+pnl = tvl.data.values().update(["PnL = Value - 100.0"])
+
+baseline = tvl.baseline(
+    pnl,
+    timestamp="Timestamp",
+    value="PnL",
+    base_value=0.0,
+)
+```
+
+Positive portions of the curve are profit days; negative portions are loss days.
+
+### Line width
+
+`line_width` is an integer pixel width from 1 to 4 (the LWC default is 3). Wide lines emphasize the trajectory; thin lines let the colored fill dominate.
+
+```python order=baseline,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+baseline = tvl.baseline(data, timestamp="Timestamp", value="Value", base_value=100.0, line_width=1)
+```
+
+The outline is now one pixel wide.
+
+### Customize the per-half gradient stops
+
+Each half of the chart has its own two-stop vertical gradient. Above the baseline, `top_fill_color1` is the stop nearer the line and `top_fill_color2` is the stop nearer the top edge; below the baseline, `bottom_fill_color1` is the stop nearer the line and `bottom_fill_color2` is the stop nearer the bottom edge. Fade either pair toward `"transparent"` to let the chart background show through at the extremes.
+
+```python order=baseline,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+baseline = tvl.baseline(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    base_value=100.0,
+    top_fill_color1="positive",
+    top_fill_color2="transparent",
+    bottom_fill_color1="negative",
+    bottom_fill_color2="transparent",
+)
+```
+
+The above-baseline half fades from a theme "positive" green at the line out to transparent at the top; the below-baseline half fades from a theme "negative" red at the line out to transparent at the bottom.
+
+### Relative gradient and per-point color columns
+
+`relative_gradient=True` anchors the two-tone gradient to the series' value range. Every per-half color can also be driven from a table column: `top_line_color_column` / `bottom_line_color_column` for the line above/below the baseline, and `top_fill_color1_column` / `top_fill_color2_column` / `bottom_fill_color1_column` / `bottom_fill_color2_column` for the gradient stops.
+
+```python order=baseline,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values().update_view(
+    [
+        "TopLine = `#26a69a`",
+        "TopF1 = `rgba(38,166,154,0.4)`",
+        "TopF2 = `rgba(38,166,154,0.0)`",
+        "BotLine = `#ef5350`",
+        "BotF1 = `rgba(239,83,80,0.4)`",
+        "BotF2 = `rgba(239,83,80,0.0)`",
+    ]
+)
+
+baseline = tvl.baseline(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    base_value=100.0,
+    relative_gradient=True,
+    top_line_color_column="TopLine",
+    top_fill_color1_column="TopF1",
+    top_fill_color2_column="TopF2",
+    bottom_line_color_column="BotLine",
+    bottom_fill_color1_column="BotF1",
+    bottom_fill_color2_column="BotF2",
+)
+```
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.baseline
+```
diff --git a/plugins/tradingview-lightweight/docs/candlestick.md b/plugins/tradingview-lightweight/docs/candlestick.md
new file mode 100644
index 000000000..7fd8b433d
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/candlestick.md
@@ -0,0 +1,210 @@
+<!-- coverage-seen-elsewhere:
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  on_press -> events.md
+  on_double_press -> events.md
+  auto_bin -> autobin.md
+  bin_width -> autobin.md
+  bin_count -> autobin.md
+  crosshair_mode -> styling.md
+  time_visible -> time-scale.md
+  watermark_text -> watermark.md
+  visible -> titles-legends.md
+  last_value_visible -> titles-legends.md
+  price_scale_id -> price-scale.md
+  price_format -> price-formats.md
+  price_line_visible -> price-lines.md
+  price_line_source -> price-lines.md
+  price_line_width -> price-lines.md
+  price_line_color -> price-lines.md
+  price_line_style -> price-lines.md
+  base_line_visible -> price-scale.md
+  base_line_color -> price-scale.md
+  base_line_width -> price-scale.md
+  base_line_style -> price-scale.md
+  auto_scale -> price-scale.md
+  scale_margin_top -> price-scale.md
+  scale_margin_bottom -> price-scale.md
+  scale_mode -> price-scale.md
+  scale_invert -> price-scale.md
+  scale_align_labels -> price-scale.md
+  scale_border_visible -> price-scale.md
+  scale_border_color -> price-scale.md
+  scale_text_color -> price-scale.md
+  scale_entire_text_only -> price-scale.md
+  scale_visible -> price-scale.md
+  scale_ticks_visible -> price-scale.md
+  scale_minimum_width -> price-scale.md
+  scale_ensure_edge_tick_marks_visible -> price-scale.md
+  pane -> multi-pane.md
+  by -> multi-series.md
+-->
+
+# Candlestick Chart
+
+A candlestick chart shows the open, high, low, and close (OHLC) of a price series as a stack of rectangular bodies with thin "wick" lines, giving a compact view of where price ranged within each interval. Use it when you have time-bucketed OHLC bars and need to read direction and range at a glance.
+
+In a bullish (up) candle the close sits above the open and the body is typically rendered green; in a bearish (down) candle the close sits below the open and the body is typically red. The wick (or "shadow") extends from the body to the period's high and low, so wick length communicates intra-bar volatility.
+
+## What are candlestick charts useful for?
+
+- **Reading short-term price action**: Bodies and wicks make direction and intra-bar range readable at a glance, which is why candlesticks are common on technical-analysis screens.
+- **Spotting reversal and continuation patterns**: Many classical patterns (engulfings, hammers, dojis) rely on the relative size of body and wicks, and candlesticks are the only chart type that surfaces both.
+- **Comparing volatility regimes**: Long wicks with small bodies signal indecision; tall bodies with short wicks signal momentum. Switching between regimes is easy to see.
+- **Confirming aggregations**: Because TVL aggregates OHLC server-side when the table is large, a candlestick chart is also a quick check that your binning matches what you expected.
+
+## Examples
+
+### A basic candlestick chart
+
+Hand the chart a Deephaven table that already contains OHLC columns and the rest is automatic. The defaults (`timestamp="Timestamp"`, `open="Open"`, `high="High"`, `low="Low"`, `close="Close"`) match the columns produced by `tvl.data.ohlc()`, so for the demo dataset you only need the table itself.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(data)
+```
+
+Each candle covers one row in `data`; green bodies are up days and red bodies are down days. `tvl.candlestick()` doesn't carry the last-price pulse animation that line / area / baseline series do. See [line](line.md) and [styling](styling.md) for the `LastPriceAnimationMode` examples.
+
+When `up_color` / `down_color` are not provided, the chart adapts to the active theme automatically. Light and dark themes both render correctly without code changes.
+
+### Map non-default OHLC column names
+
+If your table uses different column names, for example lowercase columns coming from a feed or a different timestamp column, pass them explicitly. Every column kwarg is just a string column name.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc().rename_columns(["Ts=Timestamp", "O=Open", "H=High", "L=Low", "C=Close"])
+
+candlestick = tvl.candlestick(
+    data,
+    timestamp="Ts",
+    open="O",
+    high="H",
+    low="L",
+    close="C",
+)
+```
+
+### Customize up and down colors
+
+Override the default green/red palette with `up_color` and `down_color`. Use this to match a brand palette, build a color-blind-friendly variant, or to dim the candles before overlaying markers and price lines.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(
+    data,
+    up_color="seafoam-800",
+    down_color="magenta-600",
+)
+```
+
+All color kwargs (`up_color`, `down_color`, `border_*_color`, `wick_*_color`) accept a Deephaven theme color (e.g. `"seafoam-800"`, `"accent-300"`), a hex code (`"#1f8a70"`), a named CSS color (`"crimson"`), or an `rgb()`/`rgba()` string for transparency. Theme colors adapt automatically when the user switches themes; hardcoded values do not. Leaving the up/down colors unset inherits the active theme's OHLC palette.
+
+### Outline-only candles via border colors
+
+`border_up_color` and `border_down_color` set the outline color of each candle independently of the body fill. Setting a border to `"transparent"` removes that border entirely, leaving only the body fill. Combine this with a neutral body fill and a single visible up border to get a "pavement" two-tone candle.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(
+    data,
+    up_color="gray-500",
+    down_color="gray-500",
+    border_up_color="gray-500",
+    border_down_color="transparent",
+)
+```
+
+Up candles use a neutral grey throughout; down candles drop their border so only the grey body remains.
+
+### Recolor the wicks
+
+`wick_up_color` and `wick_down_color` set the wick color separately from the body. Use this to dim the wicks while keeping bright bodies (for marker visibility), or to brighten the wicks on a dark background.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(
+    data,
+    wick_up_color="gray-500",
+    wick_down_color="gray-500",
+)
+```
+
+Both wicks are now grey; the bodies keep their defaults.
+
+### Set the chart title
+
+`title` is the legend label for the series. It appears on hover and in the chart toolbar. Use it whenever you have more than one series on a chart, or when the chart will be embedded somewhere a column name (`Open`/`Close`) is too generic.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(data, title="AAPL daily OHLC")
+```
+
+The legend now reads "AAPL daily OHLC" instead of the default series name.
+
+### Server-side autobinning
+
+Hand the chart a large OHLC table and TVL automatically aggregates it server-side into a viewport-friendly number of buckets, picking a "nice" bin width and computing `first(Open)` / `max(High)` / `min(Low)` / `last(Close)` per bin. Override the bucket count or width via `bin_count` / `bin_width`, or set `auto_bin=False` to bypass it entirely for small tables.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(data, auto_bin=True, bin_width="P7D")
+```
+
+See [autobin](autobin.md) for the full autobin surface: ISO-8601 duration grammar, when each `auto_bin` value is the right pick, and how the path interacts with the downsampler.
+
+### Single border / wick colors and toggles
+
+`border_color` and `wick_color` set one color for both up and down candles, shorthand for setting the `*_up_color` / `*_down_color` pair to the same value. `border_visible` and `wick_visible` toggle the outline and wick rendering entirely.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc()
+
+candlestick = tvl.candlestick(
+    data,
+    border_visible=True,
+    border_color="gray-500",
+    wick_visible=True,
+    wick_color="gray-400",
+)
+```
+
+### Per-bar colors from a column
+
+Drive each candle's color from a table column with `color_column` (body), `border_color_column` (outline), and `wick_color_column` (wick). Each names a column holding a CSS/theme color string per row. Here we color each bar by whether it closed up or down.
+
+```python order=candlestick,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.ohlc().update_view(
+    ["BarColor = Close >= Open ? `#26a69a` : `#ef5350`"]
+)
+
+candlestick = tvl.candlestick(
+    data,
+    color_column="BarColor",
+    border_color_column="BarColor",
+    wick_color_column="BarColor",
+)
+```
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.candlestick
+```
diff --git a/plugins/tradingview-lightweight/docs/chart.md b/plugins/tradingview-lightweight/docs/chart.md
new file mode 100644
index 000000000..e44aa7cda
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/chart.md
@@ -0,0 +1,63 @@
+# The Chart Container
+
+`tvl.chart()` is the container that hosts one or more series and carries every chart-level option: pane layout, axes, time scale, styling, watermark, and titles. Each per-type constructor (`tvl.line`, `tvl.candlestick`, `tvl.area`, `tvl.bar`, `tvl.baseline`, `tvl.histogram`) returns a one-series `TvlChart`. Pass any number of them positionally to `tvl.chart()` and the series are concatenated into a single composed chart with chart-level options applied on top.
+
+A standalone per-type call (e.g. `tvl.line(table, ...)`) is just shorthand for `tvl.chart(tvl.line(table, ...))` with default chart options. The moment you need *any* chart-level option, wrap the series call in `tvl.chart(..., option=value)`.
+
+## A composed multi-series, multi-pane chart
+
+The example below combines the two most common composition patterns in one snippet: a candlestick price series and a moving-average line on the same upper pane, plus a histogram volume series on a stretched lower pane. It also sets a few chart-level options so the role of `tvl.chart()` is concrete.
+
+```python order=composed,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+bars = tvl.candlestick(ohlc, pane=0)
+ema = tvl.line(
+    ohlc, timestamp="Timestamp", value="Ema",
+    color="#ff9800", line_width=2, pane=0, title="EMA(20)",
+)
+volume = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume",
+    color="rgba(120,120,120,0.5)", pane=1, title="Volume",
+)
+
+composed = tvl.chart(
+    bars,
+    ema,
+    volume,
+    pane_stretch_factors=[3, 1],
+    crosshair_mode="magnet",
+    time_visible=True,
+)
+```
+
+Three series, two panes, one shared time axis. `pane=0` / `pane=1` route series into panes; `pane_stretch_factors=[3, 1]` makes the price pane three times the height of the volume pane; the remaining kwargs are pure chart-level styling.
+
+## Configure the chart
+
+`tvl.chart()` accepts the full chart-level option set. The pages below drill into each option group.
+
+**Compose**
+- [Multiple series](multi-series.md). Overlaying several series on one chart.
+- [Multiple panes](multi-pane.md). Stacking panes inside one chart frame.
+- [Multiple axes](multiple-axes.md). Independent price scales on one pane.
+
+**Annotate**
+- [Titles and legends](titles-legends.md). Chart title (via watermark) and the in-chart legend driven by per-series `title=`.
+- [Markers](markers.md). Circles, squares, or arrows attached to a series at specific points in time to flag events.
+- [Price lines](price-lines.md). Horizontal lines drawn across a series at a fixed or table-driven price level.
+- [Watermark](watermark.md). Faint label drawn behind the data, for the ticker symbol, dataset name, or chart title.
+
+**Style**
+- [Styling](styling.md). Colors, fonts, grid, crosshair, layout.
+- [Time scale](time-scale.md). The horizontal axis.
+- [Price scale](price-scale.md). The vertical axes.
+- [Price formats](price-formats.md). Number formatting on price labels.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.chart
+```
diff --git a/plugins/tradingview-lightweight/docs/custom-numeric.md b/plugins/tradingview-lightweight/docs/custom-numeric.md
new file mode 100644
index 000000000..3432ed36f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/custom-numeric.md
@@ -0,0 +1,103 @@
+<!-- coverage-seen-elsewhere:
+  crosshair_mode -> styling.md
+  watermark_text -> watermark.md
+  background_color -> styling.md
+  text_color -> styling.md
+-->
+
+# Custom Numeric Chart
+
+A custom-numeric chart puts any numeric quantity on the horizontal axis. Unlike the candlestick / line / area family (which require time on the x-axis) and unlike the yield-curve chart (which expects months) and the options chart (which expects strikes), `tvl.custom_numeric` makes no assumption about what your x-values *mean*. They're just numbers.
+
+Internally `tvl.custom_numeric` uses the same `createOptionsChart` renderer as `tvl.options_chart`. Use it whenever your x-axis is a generic numeric quantity (frequency in Hz, distance in km, price level for a profile chart, basket index) rather than time, maturity, or strike. TVL also exposes a more flexible `createChartEx` entry point in JavaScript that lets you attach a custom JS `horzScaleBehavior`, which is intentionally not surfaced through the Python API.
+
+## What are custom-numeric charts useful for?
+
+- **Frequency / Bode plots**: Magnitude or phase vs. frequency on a numeric axis with no time semantics.
+- **Distance / depth profiles**: Price vs. depth-of-book level, density vs. depth, anything indexed by a numeric position.
+- **Price-level profiles**: Volume profile, market profile (TPO), and any other "histogram by price level" rendering.
+- **Custom indices**: Basket weights vs. constituent number, regression coefficients vs. feature index: any "value vs. integer position" view.
+
+## Examples
+
+### A basic line on a numeric x-axis
+
+The chart treats `x` as a numeric coordinate, so any numeric column will do. Pass it explicitly along with the value column. Build a small synthetic table inline by attaching an integer `X` to the `tvl.data.values()` series.
+
+```python order=custom_numeric,profile
+import deephaven.plot.tradingview_lightweight as tvl
+profile = tvl.data.values().update(["X = (double)ii"])
+
+custom_numeric = tvl.custom_numeric(profile, x="X", value="Value")
+```
+
+The line traces `Value` over the integer x-axis. Reuse a strike, tenor, or any other numeric column verbatim when you want a generic numeric rendering of data you might otherwise feed to `options_chart` or `yield_curve`.
+
+> [!NOTE]
+> Viewport-aware downsampling currently only applies to time-axis charts (`chart_type == "standard"`). Custom-numeric charts ship raw rows to the client, so keep the input table modest (tens of thousands of rows) or pre-aggregate server-side.
+
+### Switch to an area rendering
+
+`series_type="area"` swaps the line for a filled area. Combine it with `top_color`, `bottom_color`, and `line_color` for a custom gradient.
+
+```python order=custom_numeric,profile
+import deephaven.plot.tradingview_lightweight as tvl
+profile = tvl.data.values().update(["X = (double)ii"])
+
+custom_numeric = tvl.custom_numeric(
+    profile,
+    x="X",
+    value="Value",
+    series_type="area",
+    top_color="rgba(38, 166, 154, 0.45)",
+    bottom_color="rgba(38, 166, 154, 0.0)",
+    line_color="#26a69a",
+)
+```
+
+The gradient fades to transparent at the bottom.
+
+### Switch to a histogram rendering
+
+`series_type="histogram"` renders one bar per row, a natural fit for volume-profile and market-profile views where the x-axis is a price level.
+
+```python order=custom_numeric,profile
+import deephaven.plot.tradingview_lightweight as tvl
+profile = tvl.data.values().update(["X = (double)ii"])
+
+custom_numeric = tvl.custom_numeric(
+    profile,
+    x="X",
+    value="Value",
+    series_type="histogram",
+    color="#9467bd",
+)
+```
+
+A purple bar rises at each integer x-value.
+
+### Customize color, width, and title
+
+In line and area modes, `color`, `line_width`, and `title` work the same way as in the other chart types. `line_width` is an integer pixel width 1-4.
+
+```python order=custom_numeric,profile
+import deephaven.plot.tradingview_lightweight as tvl
+profile = tvl.data.values().update(["X = (double)ii"])
+
+custom_numeric = tvl.custom_numeric(
+    profile,
+    x="X",
+    value="Value",
+    color="#1f77b4",
+    line_width=3,
+    title="Custom profile",
+)
+```
+
+The line is blue, three pixels wide, with a custom legend entry.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.custom_numeric
+```
diff --git a/plugins/tradingview-lightweight/docs/downsampling.md b/plugins/tradingview-lightweight/docs/downsampling.md
new file mode 100644
index 000000000..3f84aea8c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/downsampling.md
@@ -0,0 +1,143 @@
+<!-- coverage-seen-elsewhere:
+  auto_bin -> autobin.md
+  bin_width -> autobin.md
+  bin_count -> autobin.md
+  large_prices -> example-data.md
+-->
+
+# Downsampling
+
+Downsampling is what keeps TVL responsive on multi-million-row tables. The Line, Area, and Baseline series automatically thin out points as the user pans and zooms, so the renderer never tries to draw more bars than the chart has pixels. The visible curve still includes every local minimum and maximum, so spikes and dips never disappear.
+
+This page is the conceptual reference: what downsampling is, when it kicks in, how to tune it, and (briefly) when to turn it off.
+
+## What is downsampling useful for?
+
+- **Smooth interaction on big tables**: A 1M-row line is unplayable if every pan ships 1M points to the browser; downsampling brings it down to ~viewport-width points and keeps interaction snappy.
+- **Faithful min/max preservation**: The downsampler picks the highest and lowest point in each pixel column, so a tall single-row spike survives even when nine of its neighbors are dropped.
+- **Zero authoring cost**: There's no separate "downsampled chart" mode. Write `tvl.line(table, ...)` against a 1M-row table and it works.
+- **Whitespace fills**: Whitespace-aware aggregation means leading and trailing gaps don't compress the visible region.
+
+## How it activates
+
+TVL has two server-side / client-side cooperating paths:
+
+1. **JS-side viewport downsampling** (Line / Area / Baseline). When a series has more points than the viewport has bars, the client requests a downsampled view from the server, asking for "give me the min and the max for each pixel column in the visible time range." The aggregation runs in the Deephaven query engine via `agg_by` with `first` / `last` / `sorted_first` / `sorted_last` reductions per bucket. On pan and zoom the client re-requests with the new range; on data ticks the buckets refresh.
+2. **Server-side autobinning** (Candlestick / Bar / Histogram). OHLC and histogram series can't be downsampled by min/max: they need a true aggregation. See [autobin](autobin.md) for that path.
+
+> **Numeric-axis charts don't downsample.** Viewport downsampling is gated to `chart_type == "standard"` and reads a hard-coded `time` column. `tvl.custom_numeric`, `tvl.options_chart`, and `tvl.yield_curve` therefore ship raw rows to the client. Keep their input tables modest (tens of thousands of rows) or pre-aggregate server-side.
+
+### What activates it
+
+- **Row count threshold.** Tables with more rows than the downsampler's per-series budget activate the path automatically. The exact threshold is the chart's pixel width (rounded up to a 1000-pixel bucket for cache friendliness) divided by the target bar-pixel-width.
+- **Viewport width.** The client tells the server how many pixels wide the chart is; the server returns at most ~one bucket per pixel.
+- **Whitespace edges.** When the visible window doesn't cover the entire table, the server returns the body of the visible range at full resolution plus single "anchor" rows at the head and tail so `fix_left_edge` / `fix_right_edge` have something to clamp against.
+
+## What it preserves
+
+For Line / Area / Baseline series, each bucket reduces to (at most) four points: first time, last time, sorted-first value, sorted-last value. That guarantees:
+
+- **The min and the max of every bucket survive.** Spikes are not averaged away.
+- **The bucket boundaries are real data points**, not interpolated midpoints: so hovering still shows actual timestamps and values.
+- **Vertical order is preserved within each bucket** by drawing the four points in time order, so the rendered polyline respects the rise/fall of the underlying data.
+
+For OHLC and histogram series, downsampling reduces each bucket via `first(open)`, `max(high)`, `min(low)`, `last(close)` (candlestick / bar) or `sum` / `count` / `avg` / `last` (histogram). See [autobin](autobin.md).
+
+## Examples
+
+### A 1M-row line chart
+
+The `tvl.data.large_prices()` fixture is a 1,000,000-row intraday price series. Plotting it with `tvl.line()` works exactly like plotting a 100-row table. TVL handles the downsampling transparently.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+chart = tvl.line(large, timestamp="Timestamp", value="Price")
+```
+
+Pan and zoom the chart: the curve refines as you zoom in. Local minima and maxima stay visible at every zoom level.
+
+### Compare a small vs. large table
+
+Plot the same series on a small (`values()`) and a large (`large_prices()`) table side by side. The small table is below the downsampler's threshold and renders every point as-is; the large table is downsampled, but visually the curve is faithful.
+
+```python order=small_chart,large_chart,values,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+large = tvl.data.large_prices()
+
+small_chart = tvl.line(values, timestamp="Timestamp", value="Value")
+large_chart = tvl.line(large, timestamp="Timestamp", value="Price")
+```
+
+The threshold is rarely the thing you tune. Chart width drives it more than row count, and the chart sizes to its container automatically.
+
+### Combine downsampling with multiple overlays
+
+Each series downsamples independently. Overlaying a fine-grained line and a coarse moving average doesn't degrade either, since each series gets its own bucket budget.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+chart = tvl.chart(
+    tvl.line(large, timestamp="Timestamp", value="Price", color="#2563eb"),
+    tvl.line(
+        large.update_view(["Price = Price + 5"]),
+        timestamp="Timestamp",
+        value="Price",
+        color="#dc2626",
+    ),
+)
+```
+
+Both lines stay smooth under interaction; each gets its own server-side aggregation.
+
+### Use bar spacing to control downsampling density
+
+`bar_spacing` (pixels per bar) and `min_bar_spacing` / `max_bar_spacing` (zoom limits) shape the downsampler's bucket size indirectly. Larger `bar_spacing` means fewer buckets per pixel, which gives the renderer more breathing room.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+chart = tvl.chart(
+    tvl.line(large, timestamp="Timestamp", value="Price"),
+    bar_spacing=4,
+    min_bar_spacing=1,
+    max_bar_spacing=20,
+)
+```
+
+These knobs matter most when the rendered bars start dropping below a single pixel. Bump `min_bar_spacing` to keep them visible.
+
+## Turning it off (and why you probably shouldn't)
+
+There is no chart-level "disable downsampling" boolean for Line / Area / Baseline series. The reason is that disabling it is almost always wrong:
+
+- **Browsers can't render 1M points in a polyline at 60fps.** Even on fast hardware, building and laying out the SVG / canvas path is bottlenecked on point count.
+- **The downsampled view is faithful.** Min and max per bucket survive: the only thing you lose is rendering every individual point, which the chart couldn't show anyway because each one is sub-pixel.
+
+If you have a table that's small enough that downsampling wouldn't help and you don't want to pay the round-trip overhead, just plot the table directly. TVL only activates the downsampling path when the chart pixel budget is smaller than the row count.
+
+For OHLC and histogram series, the equivalent toggle exists (`auto_bin=False`). See [autobin](autobin.md). The same advice applies: disable it only when the table is already small.
+
+## Tunables
+
+The downsampler is mostly automatic, but a few knobs on `chart()` and the series factories influence it:
+
+- **`width` / `height` on `chart()`**: pin the pixel budget, which sets the bucket target.
+- **`bar_spacing` / `min_bar_spacing` / `max_bar_spacing`**: pixels per bar, which drives the bucket count.
+- **`auto_bin` / `bin_width` / `bin_count`** (Candlestick / Bar / Histogram): see [autobin](autobin.md).
+- **`fix_left_edge` / `fix_right_edge`**: anchor the visible range to the data edges. The downsampler emits single-row anchors at the head and tail when the visible window is strictly inside the data range so these clamps work.
+
+For benchmarking comparisons (server-side autobin vs. client-side rendering cost), see [large-data](large-data.md).
+
+## API Reference
+
+The downsample-related options (`downsample`, `downsample_threshold`, `downsample_target_buckets`, `downsample_min_pixel_step`) live on [`tvl.chart`](chart.md#api-reference). For the line-specific surface, see [`tvl.line`](line.md#api-reference).
diff --git a/plugins/tradingview-lightweight/docs/events.md b/plugins/tradingview-lightweight/docs/events.md
new file mode 100644
index 000000000..567ecccb4
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/events.md
@@ -0,0 +1,163 @@
+<!-- coverage-seen-elsewhere:
+  on_press -> events.md
+  on_double_press -> events.md
+-->
+
+# Press Events
+
+A TVL chart can call back into Python when the user presses on it. Attach a handler with `on_press` or `on_double_press` and it runs server-side with the press details: the time and pixel location of the click, the series under the cursor, every series' data at that location, the pane, and the modifier keys that were held.
+
+The payload mirrors lightweight-charts' [`MouseEventParams`](https://tradingview.github.io/lightweight-charts/docs/api/interfaces/MouseEventParams), using the same camelCase field names that deephaven.ui's own event payloads use. Two things change for the server round-trip: the hovered series is reported as a string id rather than a chart object, and `time` arrives as a Deephaven timestamp.
+
+These follow the deephaven.ui convention. The name is "press", not "click", and the handler is a plain Python callable, exactly like a deephaven.ui event callback. The two handlers are available on `tvl.chart(...)` and on every per-type constructor (`line`, `area`, `candlestick`, `bar`, `baseline`, `histogram`), so you can wire them whether you build a chart the long way or with the per-type shorthand.
+
+## What are press events useful for?
+
+- **Drill-down**: Read the `timestamp` and `hoveredSeries`, then open a detail table or update another widget scoped to that point.
+- **Annotation capture**: Append the pressed `(timestamp, value)` to a Deephaven table so users can mark levels by clicking the chart.
+- **Selection state**: Set a variable from the press and let the rest of your app react to it.
+- **Reading every series at once**: `seriesData` carries each series' value at the press location, so you can compare overlaid series at the moment of the click.
+
+## The two handlers
+
+`on_press` fires on a single press. `on_double_press` fires on a double press. Wire either or both:
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    on_press=lambda e: print("press", e),
+    on_double_press=lambda e: print("double", e),
+)
+```
+
+The same kwargs work at the chart level when you compose series yourself:
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(data, timestamp="Timestamp", value="Value"),
+    on_press=lambda e: print("press", e),
+)
+```
+
+### Handler signature: zero or one argument
+
+A handler may take the event argument or take nothing at all. Both forms are valid, and TVL adapts to whichever you wrote:
+
+```python skip-test
+# One argument: receives the event payload.
+on_press=lambda e: print(e["timestamp"])
+
+# Zero arguments: fires, but ignores the payload.
+on_press=lambda: print("the chart was pressed")
+```
+
+Use the zero-argument form when you only care that a press happened, not where.
+
+## The event payload
+
+The event is a plain `dict` with camelCase keys (a `TvlPressEvent`) mirroring `MouseEventParams`. Read its fields with subscript access, like `e["hoveredSeries"]` and `e["seriesData"]`. It is a dict, not an object, so attribute access (`e.hoveredSeries`) does not work.
+
+| Key | Type | Meaning |
+|---|---|---|
+| `type` | `"press"` or `"doublePress"` | Which handler fired. |
+| `timestamp` | `Instant` / `ZonedDateTime` / `datetime` | Time of the data at the press location (`MouseEventParams.time`), as a Deephaven timestamp mirroring the hovered series' time-column type. Absent when the press is outside the data range. |
+| `hoveredSeries` | `str` | Friendly id of the series under the cursor. Uses the rendered title when present; `by=` charts use the partition key; falls back to `series_0`, `series_1`, etc. only when no title/key exists. This is the key into `seriesData`. Omitted when no series is hovered. |
+| `hoveredSeriesId` | `str` | TVL's stable `series_<n>` id for the hovered series, for unambiguous server-side lookup even when titles collide. Omitted when no series is hovered. |
+| `seriesData` | `dict` | Each series' data at the press location, keyed by friendly id. Values mirror the series' data shape: `{"value": ...}` for line/area/baseline/histogram, or `{"open", "high", "low", "close"}` for candlestick/bar. |
+| `point` | `dict` | Pixel location `{"x": ..., "y": ...}` of the press in the chart. Omitted when outside the chart. |
+| `logical` | `int` | Logical index at the press location (`MouseEventParams.logical`). |
+| `paneIndex` | `int` | Index of the pane the press landed in, when available. |
+| `shiftKey` | `bool` | Whether Shift was held. |
+| `ctrlKey` | `bool` | Whether Ctrl was held. |
+| `metaKey` | `bool` | Whether Meta (Cmd) was held. |
+| `altKey` | `bool` | Whether Alt was held. |
+
+Fields that cannot be resolved for a given press are left out of the dict rather than set to `None`. A press outside the data range has no `timestamp`, and a press not over a series has no `hoveredSeries`/`hoveredSeriesId`. Read optional fields with `e.get("hoveredSeries")` and `e.get("timestamp")` so a missing key does not raise `KeyError`. The always-present fields are `type`, `seriesData` (possibly empty), and the four modifier booleans.
+
+`hoveredSeries` is lightweight-charts' own hit test. The series under the cursor. To read the pressed value, look it up in `seriesData`:
+
+```python skip-test
+def on_press(e):
+    sid = e.get("hoveredSeries")
+    if sid is not None:
+        print(sid, "=>", e["seriesData"].get(sid))
+```
+
+`timestamp` mirrors the type of the hovered series' timestamp column, following the deephaven.ui convention that a callback hands back the same kind of value you gave it:
+
+- a Deephaven `Instant` when the column is an `Instant`,
+- a Deephaven `ZonedDateTime` when the column is a `ZonedDateTime`, reconstructed in the zone the chart is displaying (the press travels over the wire as a plain instant, so the column's original per-row zone is not recoverable. The displayed zone is what you saw on the axis),
+- a timezone-aware UTC `datetime` as the fallback when the column type can't be resolved.
+
+When no series is hovered, TVL uses the shared type if every series agrees, otherwise the `datetime` fallback. Either way the value is a real Deephaven timestamp you can compare against table columns directly. The chart works in shifted epoch seconds on the wire; TVL undoes the display-tz shift before building the value.
+
+## Double-press fires a press first
+
+When both handlers are registered, a double press fires one `press` followed by one `double_press`. The underlying chart library reports the first click of a double-click as a normal click and does not suppress it. This is intentional. TVL adds no debounce delay, because that would tax every single press to smooth over a rare, predictable overlap.
+
+If you need a double press to not also count as a single press, branch on it yourself, for example by recording the press time in `on_press` and ignoring a follow-up that arrives within your own window. Most apps do not need this.
+
+## Handlers run server-side
+
+A press handler runs on the server under the same execution context and liveness scope that was captured when the chart was created, exactly like a deephaven.ui callback. That means a handler can do real Deephaven work: mutate a table, set a variable, create a new table, and the objects it touches stay live for as long as the chart does.
+
+Keep handlers quick. A press fires on the data stream's dispatch path, so a slow handler holds up the chart. Do the cheap, immediate work in the handler (capture the selected values, flip a flag, enqueue) and offload anything heavy to a background table operation or a separate thread. A handler that raises is logged and swallowed, so a bug in one press will not tear down the chart, but it also will not surface to the user, so check the server log if a handler seems to do nothing.
+
+## Example: append pressed points to a table
+
+This wires a line chart so each press records the pressed `(timestamp, value, series)` into a Deephaven input table. The table ticks live as the user clicks the chart, so you can join it, snapshot it, or render it elsewhere.
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+from deephaven import dtypes
+from deephaven.stream.table_publisher import table_publisher
+
+data = tvl.data.values()
+
+clicks, publisher = table_publisher(
+    "chart clicks",
+    {
+        "Time": dtypes.Instant,
+        "Series": dtypes.string,
+        "Price": dtypes.double,
+    },
+)
+
+
+def record_press(e):
+    t = e.get("timestamp")
+    sid = e.get("hoveredSeries")
+    point = e.get("seriesData", {}).get(sid) if sid is not None else None
+    if t is None or point is None:
+        return  # pressed off the data / not over a series, nothing to record
+    from deephaven import new_table
+    from deephaven.column import datetime_col, string_col, double_col
+
+    publisher.add(
+        new_table(
+            [
+                datetime_col("Time", [t]),
+                string_col("Series", [sid]),
+                double_col("Price", [point["value"]]),
+            ]
+        )
+    )
+
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    on_press=record_press,
+)
+```
+
+Open `line`, click on the data, and watch rows land in `clicks`. The zero-or-one-arg rule means you could swap in `on_press=lambda: print("pressed")` for a quick check before wiring the full handler.
diff --git a/plugins/tradingview-lightweight/docs/example-data.md b/plugins/tradingview-lightweight/docs/example-data.md
new file mode 100644
index 000000000..11c0fbd34
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/example-data.md
@@ -0,0 +1,103 @@
+# Example data
+
+The Deephaven TradingView Lightweight package includes several built-in, deterministically generated tables for testing and example code. Each function returns a fresh `deephaven.table.Table` whose values are produced by closed-form expressions (no random data), so snapshot tests stay stable across runs.
+
+Import the module under the `tvl` alias and call any of the functions below. Every chart-type page in this documentation builds its examples on these fixtures.
+
+## ohlc
+
+A 90-row daily OHLCV table with a precomputed `Ema` column. Each row is one trading day starting 2024-01-01; Open / High / Low / Close follow a smoothed random walk around 100, Volume is correlated with the per-bar move, and `Ema` is a 20-tick EMA of `Close` for overlay examples. Designed for the `candlestick` and `bar` chart examples.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.ohlc
+```
+
+## stocks
+
+A 120-row multi-symbol trade-style table. Three symbols (`AAA`, `BBB`, `CCC`) are interleaved round-robin via `ii % 3`, each with its own sine-wave price curve so by-grouped examples produce visually distinct series. Designed for the `line` / `area` / `baseline` "by group" examples.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+stocks = tvl.data.stocks()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.stocks
+```
+
+## volume
+
+A 60-row single-column volume series. One row per day from 2024-01-01, with Volume around 1000 ± 300 via overlapping sines. Designed for the `histogram` chart examples where a single value column is plotted against time.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+volume = tvl.data.volume()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.volume
+```
+
+## yields
+
+An 11-point yield-curve snapshot. Tenors follow the canonical Treasury set (3M, 6M, 1Y, 2Y, 3Y, 5Y, 7Y, 10Y, 20Y, 30Y, 40Y) and are emitted in months (3, 6, 12, 24, 36, 60, 84, 120, 240, 360, 480). The unit LWC's yield-curve axis expects. The `Yield` column follows a smooth concave curve that rises quickly at the short end, peaks in the belly, and tapers off. Designed for the `yield_curve` chart examples.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+yields = tvl.data.yields()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.yields
+```
+
+## options_chain
+
+A 21-row symmetric options-chain snapshot. Strikes step by 5 from 50 to 150 (at-the-money = 100). Call and put prices follow a simplified intrinsic-plus-time-value shape so the typical "X" pattern of the options chart is visible. Designed for the `options_chart` examples.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+options_chain = tvl.data.options_chain()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.options_chain
+```
+
+## values
+
+A 90-row single-value time series. One row per day from 2024-01-01, with `Value` oscillating around 100 via two superimposed sines. Designed for the simplest `line` / `area` / `baseline` / `histogram` example pages where you want a single column over time.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.values
+```
+
+## large_prices
+
+A 1,000,000-row intraday price series spanning ~10 years. Timestamps step uniformly (~315 seconds per row) starting 2020-01-01; the price curve is a low-frequency sine plus a higher-frequency wiggle, giving the downsampler something visually meaningful to thin out. Designed for the [downsampling](downsampling.md) and [large-data](large-data.md) examples.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+large_prices = tvl.data.large_prices()
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.data.large_prices
+```
diff --git a/plugins/tradingview-lightweight/docs/histogram.md b/plugins/tradingview-lightweight/docs/histogram.md
new file mode 100644
index 000000000..e11af88f3
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/histogram.md
@@ -0,0 +1,163 @@
+<!-- coverage-seen-elsewhere:
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  on_press -> events.md
+  on_double_press -> events.md
+  auto_bin -> autobin.md
+  bin_width -> autobin.md
+  bin_count -> autobin.md
+  crosshair_mode -> styling.md
+  time_visible -> time-scale.md
+  watermark_text -> watermark.md
+  base -> line.md
+  last_value_visible -> titles-legends.md
+  visible -> titles-legends.md
+  price_scale_id -> price-scale.md
+  price_format -> price-formats.md
+  price_line_visible -> price-lines.md
+  price_line_source -> price-lines.md
+  price_line_width -> price-lines.md
+  price_line_color -> price-lines.md
+  price_line_style -> price-lines.md
+  base_line_visible -> price-scale.md
+  base_line_color -> price-scale.md
+  base_line_width -> price-scale.md
+  base_line_style -> price-scale.md
+  auto_scale -> price-scale.md
+  scale_margin_top -> price-scale.md
+  scale_margin_bottom -> price-scale.md
+  scale_mode -> price-scale.md
+  scale_invert -> price-scale.md
+  scale_align_labels -> price-scale.md
+  scale_border_visible -> price-scale.md
+  scale_border_color -> price-scale.md
+  scale_text_color -> price-scale.md
+  scale_entire_text_only -> price-scale.md
+  scale_visible -> price-scale.md
+  scale_ticks_visible -> price-scale.md
+  scale_minimum_width -> price-scale.md
+  scale_ensure_edge_tick_marks_visible -> price-scale.md
+  pane -> multi-pane.md
+  by -> multi-series.md
+-->
+
+# Histogram Chart
+
+A histogram in TVL is a column chart over a time axis: one vertical bar per time bucket, with the bar height set by a server-side aggregation of the rows in that bucket. The classic use is volume (sum the trade size per minute), but the same primitive renders any per-bucket quantity such as trade count, average price, or last seen value.
+
+The TVL histogram does its binning server-side. Hand the chart a million-row trade table and it picks a bin width that matches the screen resolution, computes the aggregation in Deephaven (via `agg_by`), and ships only the rendered bars to the browser. Pick the aggregation with the `agg` parameter (`"sum"`, `"count"`, `"avg"`, `"last"`). The full auto-bin pipeline is documented separately in [autobin](autobin.md).
+
+## What are histogram charts useful for?
+
+- **Volume bars below a price chart**: Render aggregated trade size as a histogram in a second pane below the price candles.
+- **Per-bucket counts**: Set `agg="count"` to plot trades-per-minute, events-per-second, or any rate quantity directly from the raw event table. The count is computed by Deephaven via `agg_by`, so the browser never sees the raw rows.
+- **Tape diagnostics**: A histogram of `last` per bucket is a quick way to see whether your binning matches the data's natural cadence.
+- **Color-coded categorical bars**: With `color_column` each bar can be tinted by a per-row category (e.g. side = buy/sell), turning the histogram into a quick categorical breakdown.
+
+## Examples
+
+### A basic volume histogram
+
+`tvl.data.volume()` is a 60-row daily volume table (columns `Timestamp` and `Volume`). Pass the value column explicitly because the chart defaults `value="Value"`; `timestamp` defaults to `"Timestamp"` which already matches.
+
+```python order=histogram,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.volume()
+
+histogram = tvl.histogram(data, timestamp="Timestamp", value="Volume")
+```
+
+A single bar rises from the baseline for each row in `data`.
+
+### Customize the bar color
+
+`color` sets a single fill color for every bar. Color kwargs accept a Deephaven theme color (e.g. `"positive"`, `"seafoam-500"`, `"accent-300"`), a hex code (`"#26a69a"`), a named CSS color (`"teal"`), or an `rgb()`/`rgba()` string for transparency. Theme colors adapt automatically when the user switches themes; hardcoded values do not.
+
+```python order=histogram,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.volume()
+
+histogram = tvl.histogram(
+    data,
+    timestamp="Timestamp",
+    value="Volume",
+    color="positive",
+)
+```
+
+All bars are now drawn in the user's theme "positive" color.
+
+### Per-bar colors with `color_column`
+
+`color_column` points at a string column in the table whose values are CSS color strings. The histogram colors each bar with the color in that row. The typical pattern is to tag each row "green" or "red" depending on whether it was a buy or a sell.
+
+```python order=histogram,volume_colored
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.volume()
+volume_colored = data.update([
+    'BarColor = (Volume > 1000) ? "positive" : "negative"',
+])
+
+histogram = tvl.histogram(
+    volume_colored,
+    timestamp="Timestamp",
+    value="Volume",
+    color_column="BarColor",
+)
+```
+
+Bars above 1000 use the theme's `positive` color, the rest use `negative`. As with the chart-level `color` argument, any Deephaven theme color, hex code, named CSS color, or `rgb()`/`rgba()` string is valid. `color` still acts as the fallback if a row has a null in `color_column`.
+
+### Change the aggregation
+
+`agg` selects the server-side reduction used when the histogram bins are larger than one row each. Deephaven runs an `agg_by` per bin so the browser only receives the reduced bars. The options are `"sum"` (default), `"count"`, `"avg"`, and `"last"`.
+
+To see each `agg` produce a visibly different chart, the input table needs *many* rows per bin and *variation* within each bin. `tvl.data.stocks()` ships one trade per day across three symbols, so a two-week bin aggregates ~14 trades.
+
+```python order=hist_sum,hist_count,hist_avg,hist_last,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.stocks()
+
+hist_sum = tvl.histogram(data, timestamp="Timestamp", value="Size", agg="sum", bin_width="P14D", auto_bin=True, title="sum (total per 14 days)")
+hist_count = tvl.histogram(data, timestamp="Timestamp", value="Size", agg="count", bin_width="P14D", auto_bin=True, title="count (trades per 14 days)")
+hist_avg = tvl.histogram(data, timestamp="Timestamp", value="Size", agg="avg", bin_width="P14D", auto_bin=True, title="avg (mean size per 14 days)")
+hist_last = tvl.histogram(data, timestamp="Timestamp", value="Size", agg="last", bin_width="P14D", auto_bin=True, title="last (final size per 14 days)")
+```
+
+- `sum` totals every trade size in the bin: the tallest bars, scaled by ~14× the per-trade size.
+- `count` is flat at ~14 because the demo trades arrive on a regular cadence.
+- `avg` smooths the per-trade noise; with `sum = count × avg` and `count` ≈ constant, `avg` traces the same shape as `sum` at 1/14th the scale.
+- `last` ignores the rest of the bin and shows whichever single trade happened to close it: a noisier point sample.
+
+See [autobin](autobin.md) for the full story on when each value is the right pick.
+
+### Set a chart title
+
+`title` is the series legend label and shows up on hover. Use it when the chart is embedded next to other content where "Volume" alone is too generic.
+
+```python order=histogram,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.volume()
+
+histogram = tvl.histogram(data, timestamp="Timestamp", value="Volume", title="Daily traded volume")
+```
+
+The legend now reads "Daily traded volume".
+
+## Auto-binning
+
+When the input table is larger than `AUTO_BIN_THRESHOLD` (5000 rows) the histogram automatically aggregates server-side: pick a bin width that maps cleanly to the screen pixel grid, reduce each bin with `agg`, and stream only the resulting bars to the client. You can override the heuristic with three knobs:
+
+- `auto_bin=True`: force auto-bin on, regardless of size.
+- `auto_bin=False`: force it off (raw rows; can be slow on big tables).
+- `bin_width="PT1M"`: set the bin width directly with an ISO-8601 duration.
+- `bin_count=500`: request a target number of bins.
+
+These knobs and the underlying pipeline are documented in detail in [autobin](autobin.md).
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.histogram
+```
diff --git a/plugins/tradingview-lightweight/docs/index.rst b/plugins/tradingview-lightweight/docs/index.rst
new file mode 100644
index 000000000..db58152d3
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/index.rst
@@ -0,0 +1,6 @@
+
+.. toctree::
+   :maxdepth: 2
+   :glob:
+
+   *
diff --git a/plugins/tradingview-lightweight/docs/large-data.md b/plugins/tradingview-lightweight/docs/large-data.md
new file mode 100644
index 000000000..648b06df6
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/large-data.md
@@ -0,0 +1,205 @@
+<!-- coverage-seen-elsewhere:
+  large_prices -> example-data.md
+  values -> example-data.md
+  auto_bin -> autobin.md
+  bin_width -> autobin.md
+-->
+
+# Large Data
+
+TVL is designed to chart tables that don't fit in the browser. This page covers multi-million-row tables: where the performance crossover lies, what each path costs, and how to pick between the two server-side strategies (min/max downsampling and aggregation autobinning).
+
+The short version: for **Line / Area / Baseline series**, use the automatic min/max [downsampling](downsampling.md) path. For **Histogram / Candlestick / Bar series**, use [autobinning](autobin.md). Both run in the Deephaven query engine and ship only the post-aggregation buckets to the browser.
+
+## What does "large" mean here?
+
+- **Small (no downsampling needed):** Roughly the chart's pixel width × 1 row per pixel. For an 1800-pixel-wide chart, that's a few thousand rows. Below this, the renderer can draw every point.
+- **Medium:** Tens of thousands to ~100k rows. Downsampling activates, but the cost is dominated by network ship time. Interactive performance is good.
+- **Large:** 100k to several million rows. Server-side aggregation reduces to ~viewport-width buckets, which is the actual data the renderer needs.
+- **Huge:** 10M+ rows. Aggregations are still fast (Deephaven's engine is column-oriented and parallel), but at this size query-engine cost matters as much as render cost.
+
+## What are the costs?
+
+| Cost                       | Where it lives                       | Driven by                                              |
+| -------------------------- | ------------------------------------ | ------------------------------------------------------ |
+| Aggregation (server-side)  | Deephaven engine                     | Row count × bin reduction complexity                   |
+| Serialization              | Server → client wire                 | Bin count (not row count after aggregation)            |
+| Client-side rendering      | Browser, lightweight-charts          | Bin count, viewport pixel width, animation frame rate  |
+| Re-aggregation on pan/zoom | Engine + wire                        | Bin count budget, range listener thresholds            |
+
+The big win of the server-side paths is that **serialization and rendering cost scale with bin count, not row count**. A 10M-row table downsampled to a 2000-pixel-wide chart serializes ~2000 buckets. The same size as a 2000-row table without downsampling.
+
+## Downsampling vs. autobinning: when to use which
+
+| Series type | Path | Why |
+|---|---|---|
+| Line, Area, Baseline | Min/max downsampling | Min/max-per-pixel preserves spikes; cheaper than full aggregation |
+| Candlestick, Bar | Autobinning (OHLC reduction) | OHLC requires first/max/min/last per bin |
+| Histogram | Autobinning (sum/count/avg/last) | Bars need a true reduction; min/max would lose meaning |
+
+You don't usually have to pick. `tvl.line()` uses downsampling, `tvl.histogram()` uses autobinning, etc. The choice is determined by the chart type.
+
+## Examples
+
+### Plot a 1M-row line with one call
+
+`tvl.data.large_prices()` is a 1M-row intraday price fixture. The chart needs no special configuration. Downsampling activates automatically.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+chart = tvl.line(large, timestamp="Timestamp", value="Price")
+```
+
+Drag-zoom into a small window: the chart refetches a finer aggregation. Click "reset zoom" (double-click an axis if `handle_scale_axis_double_click_reset` is on): the coarse view returns.
+
+### Autobin a histogram over a large table
+
+For a histogram on a large table, switch to `tvl.histogram()` and let autobinning pick the bin width. Use `bin_count=` to control density without committing to a specific duration.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+chart = tvl.histogram(
+    large,
+    timestamp="Timestamp",
+    value="Price",
+    auto_bin=True,
+    bin_count=200,
+    agg="avg",
+)
+```
+
+The engine aggregates 1M rows down to ~200 average-per-bin rows; the chart renders 200 bars.
+
+### Force a specific bin width
+
+When you want a known cadence (e.g. "daily" or "hourly") regardless of viewport width, set `bin_width` explicitly. See [autobin](autobin.md) for the supported ISO-8601 grammar.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+chart = tvl.histogram(
+    large,
+    timestamp="Timestamp",
+    value="Price",
+    auto_bin=True,
+    bin_width="P1D",
+    agg="sum",
+)
+```
+
+Daily bins on a 1M-row, 10-year intraday series give ~3650 bars. Well above the viewport budget but still cheap to ship and render.
+
+### OHLC autobinning on raw ticks
+
+For an OHLC chart over a tick-level table, autobinning reduces each bin to first/max/min/last. The four reductions happen in a single `agg_by` call in the engine.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+# Pretend large_prices() is a tick table; build candles at 1-day cadence.
+large = tvl.data.large_prices()
+large_ohlc = large.update_view([
+    "Open = Price",
+    "High = Price + 1",
+    "Low = Price - 1",
+    "Close = Price",
+])
+
+chart = tvl.candlestick(
+    large_ohlc,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    auto_bin=True,
+    bin_width="P1D",
+)
+```
+
+OHLC reduction is fixed; the only choice is the cadence.
+
+### Multiple downsampled series on one chart
+
+Each series downsamples independently. Overlaying two 1M-row series costs roughly twice as much wire bandwidth, not 1M × 1M. Bucket budgets are per-series.
+
+```python order=chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+shifted = large.update_view(["Price = Price + 10"])
+
+chart = tvl.chart(
+    tvl.line(large, timestamp="Timestamp", value="Price", color="#2563eb"),
+    tvl.line(shifted, timestamp="Timestamp", value="Price", color="#dc2626"),
+)
+```
+
+### Tune conflation precompute priority
+
+The conflation pipeline has an optional precompute step. When `precompute_conflation_on_init=True`, the chart kicks off the precomputation as a browser-scheduled task; `precompute_conflation_priority` (typed as the `PrecomputeConflationPriority` Literal alias) tells the scheduler how aggressive that task should be. The three values map directly to the browser `Scheduler.postTask` levels: `"background"` runs whenever the main thread is idle, `"user-visible"` (the default) runs in front of background work, and `"user-blocking"` preempts most other browser work.
+
+```python order=background_chart,visible_chart,blocking_chart,large
+import deephaven.plot.tradingview_lightweight as tvl
+
+large = tvl.data.large_prices()
+
+# Let precompute run in the background; cheapest, gives up some warm-up time.
+background_chart = tvl.chart(
+    tvl.line(large, timestamp="Timestamp", value="Price"),
+    enable_conflation=True,
+    precompute_conflation_on_init=True,
+    precompute_conflation_priority="background",
+)
+
+# Default tier — precompute runs ahead of background tasks.
+visible_chart = tvl.chart(
+    tvl.line(large, timestamp="Timestamp", value="Price"),
+    enable_conflation=True,
+    precompute_conflation_on_init=True,
+    precompute_conflation_priority="user-visible",
+)
+
+# Highest priority — best for first-paint latency, costs the most main-thread time.
+blocking_chart = tvl.chart(
+    tvl.line(large, timestamp="Timestamp", value="Price"),
+    enable_conflation=True,
+    precompute_conflation_on_init=True,
+    precompute_conflation_priority="user-blocking",
+)
+```
+
+`enable_conflation` and `conflation_threshold_factor` control the conflation pipeline itself; the priority kwarg only matters when `precompute_conflation_on_init=True`.
+
+## Benchmarking notes
+
+The `AGENTS.md` in this plugin has a "Downsample Benchmarking" section describing how to run isolated `dh exec` benchmarks. The headline finding: each approach must run in its own process, because JVM warmup biases later runs. The reference fixture in those benchmarks is 10M rows with three value columns (`Price`, `Volume`, `Spread`), aggregated to 1000 bins.
+
+The benchmark approach lets you compare alternatives. For example, `update_view` + `agg_by` (what TVL uses) against a hand-rolled `where` + `view` chain. For most users, the built-in path is what you want; the benchmarks are there for when you're tuning the engine layer.
+
+To run them: write each candidate as a standalone script under `notes/`, then invoke with `dh exec notes/bench_<name>.py 2>&1 | grep "^RESULT:"`. The `notes/bench_isolated.sh` script automates the run-each-in-its-own-process pattern.
+
+## Picking parameters
+
+A few rules of thumb:
+
+- **Pick `bin_count` to match what you actually want to show.** A bar chart with 200 visible bars is readable; 2000 is mush. Set `bin_count` close to your target density.
+- **Use `bin_width` for predictable cadences.** When the chart is meant to show "daily bars," set `bin_width="P1D"` explicitly so the cadence doesn't drift with zoom.
+- **Leave `auto_bin=None` on small inputs.** The default tri-state (`None` = auto-detect by size) means small tables skip aggregation, large tables get it. Explicitly setting `True` on small tables wastes a round-trip.
+
+## API Reference
+
+The per-type pages carry the full signature for each chart type that participates in large-data paths:
+
+- [`tvl.line`](line.md#api-reference). Client-side downsampling.
+- [`tvl.histogram`](histogram.md#api-reference), [`tvl.candlestick`](candlestick.md#api-reference), [`tvl.bar`](bar.md#api-reference). Server-side autobin.
+
+The chart-level options that govern downsampling live on [`tvl.chart`](chart.md#api-reference).
diff --git a/plugins/tradingview-lightweight/docs/line.md b/plugins/tradingview-lightweight/docs/line.md
new file mode 100644
index 000000000..1ec66c141
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/line.md
@@ -0,0 +1,238 @@
+<!-- coverage-seen-elsewhere:
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  on_press -> events.md
+  on_double_press -> events.md
+  crosshair_mode -> styling.md
+  time_visible -> time-scale.md
+  watermark_text -> watermark.md
+  last_value_visible -> titles-legends.md
+  visible -> titles-legends.md
+  price_scale_id -> price-scale.md
+  price_format -> price-formats.md
+  price_line_visible -> price-lines.md
+  price_line_source -> price-lines.md
+  price_line_width -> price-lines.md
+  price_line_color -> price-lines.md
+  price_line_style -> price-lines.md
+  base_line_visible -> price-scale.md
+  base_line_color -> price-scale.md
+  base_line_width -> price-scale.md
+  base_line_style -> price-scale.md
+  auto_scale -> price-scale.md
+  scale_margin_top -> price-scale.md
+  scale_margin_bottom -> price-scale.md
+  scale_mode -> price-scale.md
+  scale_invert -> price-scale.md
+  scale_align_labels -> price-scale.md
+  scale_border_visible -> price-scale.md
+  scale_border_color -> price-scale.md
+  scale_text_color -> price-scale.md
+  scale_entire_text_only -> price-scale.md
+  scale_visible -> price-scale.md
+  scale_ticks_visible -> price-scale.md
+  scale_minimum_width -> price-scale.md
+  scale_ensure_edge_tick_marks_visible -> price-scale.md
+  color_column -> histogram.md
+  pane -> multi-pane.md
+-->
+
+# Line Chart
+
+A line chart draws a single continuous line through `(timestamp, value)` points to show how one number changes over time. Use it when the value is a continuous quantity (price, yield, latency, count) sampled at ordered timestamps.
+
+Line charts work well with TVL's `by` argument, which partitions one input table into one line per unique value. That lets you overlay several symbols or strategies on the same axis without manually splitting the table.
+
+## What are line charts useful for?
+
+- **Showing trend over time**: A single line strips away everything but the trajectory, which is what you usually want for a quick "is it going up or down" read.
+- **Comparing multiple series**: With `by` you can overlay several groups on the same axis and visually compare their levels and slopes.
+- **Highlighting state changes**: With `line_type="with_steps"` you can render a series of discrete state data (regimes, flags, tiers) as a clean staircase.
+- **Annotating with markers and price lines**: A thin line leaves room to layer event markers and level lines on top. See [markers](markers.md) and [price-lines](price-lines.md).
+
+## Examples
+
+### A basic line chart
+
+Pass a table plus `timestamp` and `value` column names. With `tvl.data.values()` (columns `Timestamp` and `Value`) the defaults already match, but they are shown here explicitly for clarity.
+
+```python order=line,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+line = tvl.line(data, timestamp="Timestamp", value="Value")
+```
+
+A single line is drawn through 90 daily points.
+
+### Customize color and width
+
+`color` is a theme color or a CSS color of the line; `line_width` is an integer pixel width from 1 to 4 (the LWC default is 3). The `LineWidth` type alias formalizes that range as `Literal[1, 2, 3, 4]`. Bump width up when the chart is going on a big monitor; bump it down when you have many series overlaid.
+
+`color` accepts a Deephaven theme color (e.g. `"positive"`, `"seafoam-800"`, `"accent-300"`), a hex code (`"#1f77b4"`), a named CSS color (`"steelblue"`), or an `rgb()`/`rgba()` string for transparency. Theme colors adapt automatically when the user switches themes; hardcoded values do not.
+
+```python order=line,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    color="positive",
+    line_width=1,
+)
+```
+
+The line is drawn in the user's theme "positive" color (so the same code reads cleanly in light or dark mode) and one pixel wide.
+
+### Every `LineStyle` value
+
+`line_style` accepts five named presets that map to the LWC `LineStyle` enum: `"solid"`, `"dotted"`, `"dashed"`, `"large_dashed"`, and `"sparse_dotted"`. To compare them in one image, give each variant its own vertical offset so the lines stack rather than overlap.
+
+```python order=line_styles
+import deephaven.plot.tradingview_lightweight as tvl
+
+base = tvl.data.values()
+styles = [
+    ("solid", 40.0),
+    ("dotted", 20.0),
+    ("dashed", 0.0),
+    ("large_dashed", -20.0),
+    ("sparse_dotted", -40.0),
+]
+
+line_styles = tvl.chart(
+    *[
+        tvl.line(
+            base.update([f"Offset_{name} = Value + {offset}"]),
+            timestamp="Timestamp",
+            value=f"Offset_{name}",
+            line_style=name,
+            title=name,
+        )
+        for name, offset in styles
+    ],
+)
+```
+
+All five styles render on the same chart, vertically offset.
+
+### Every `LineType` value
+
+`line_type` controls how the line is drawn *between* points. The three options are:
+
+- `"simple"`: straight segments (the default).
+- `"with_steps"`: horizontal segment then a vertical jump at each new point, useful for state data that hold constant between samples.
+- `"curved"`: monotone-cubic interpolation for a smoothed look.
+
+```python order=line_types
+import deephaven.plot.tradingview_lightweight as tvl
+
+base = tvl.data.values()
+types = [
+    ("simple", 20.0),
+    ("with_steps", 0.0),
+    ("curved", -20.0),
+]
+
+line_types = tvl.chart(
+    *[
+        tvl.line(
+            base.update([f"Offset_{name} = Value + {offset}"]),
+            timestamp="Timestamp",
+            value=f"Offset_{name}",
+            line_type=name,
+            title=name,
+        )
+        for name, offset in types
+    ],
+)
+```
+
+All three types render on the same chart, vertically offset. `with_steps` is the right choice for non-interpolated discrete-state data; `curved` is purely cosmetic.
+
+### One line per group with `by`
+
+Set `by` to a partition column and the chart creates one line per unique value, automatically picking a distinct color for each from the user's theme palette. New partition keys that show up at runtime (in a ticking table) cause new series to be added on the fly.
+
+```python order=line,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.stocks()
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Price",
+    by="Sym",
+)
+```
+
+`tvl.data.stocks()` is a three-symbol (`AAA`, `BBB`, `CCC`) walk with enough independent variance per series that the three lines spread across the chart instead of stacking on top of each other.
+
+### Point markers on every data point
+
+`point_markers_visible=True` draws a small dot at each `(timestamp, value)` sample so individual points stand out from the connecting line. `point_markers_radius` (in pixels) sizes them. Useful when the sample rate is low enough that the points themselves carry information, not just the line through them.
+
+```python order=line,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    point_markers_visible=True,
+    point_markers_radius=3,
+)
+```
+
+Each daily sample is now marked with a small filled circle on top of the line.
+
+### Pulse the last point with `last_price_animation`
+
+`last_price_animation` controls the pulse effect on the last-price marker. `"disabled"` (the default) leaves it static, `"continuous"` pulses while the chart is visible, and `"on_data_update"` pulses only when new data arrives. Reach for it on live tickers where the most recent point should draw the eye.
+
+```python order=line,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    last_price_animation="continuous",
+)
+```
+
+The last-price marker now pulses continuously. Use `"disabled"` whenever snapshot determinism matters. The other two modes introduce time-dependent rendering.
+
+### Crosshair marker and line visibility
+
+When the user hovers, LWC draws a marker where the crosshair meets the line. `crosshair_marker_visible` toggles it, `crosshair_marker_radius` sizes it (pixels), and `crosshair_marker_border_color` / `crosshair_marker_background_color` / `crosshair_marker_border_width` style it. `line_visible=False` hides the connecting line itself, handy when you only want the point markers or the crosshair dot.
+
+```python order=line,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.values()
+
+line = tvl.line(
+    data,
+    timestamp="Timestamp",
+    value="Value",
+    line_visible=True,
+    crosshair_marker_visible=True,
+    crosshair_marker_radius=6,
+    crosshair_marker_border_color="accent-400",
+    crosshair_marker_background_color="accent-200",
+    crosshair_marker_border_width=2,
+)
+```
+
+These crosshair-marker options apply to `area` and `baseline` series too.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.line
+```
diff --git a/plugins/tradingview-lightweight/docs/markers.md b/plugins/tradingview-lightweight/docs/markers.md
new file mode 100644
index 000000000..f6d231878
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/markers.md
@@ -0,0 +1,240 @@
+# Markers
+
+Markers are small annotations (circles, squares, or arrows) attached to a series at specific points in time. Use them to flag individual events (a fill, a signal, a regime change) directly on the chart without disrupting the underlying price curve.
+
+There are three ways to put markers on a chart. Use [`tvl.marker()`](#api-reference) for static, code-defined markers; [`tvl.markers_from_table()`](#api-reference) when each row of a Deephaven table should become one marker (and tick live as the table updates); and [`tvl.up_down_markers()`](#api-reference) as a convenience for the common "buys are up arrows, sells are down arrows" pattern.
+
+<!-- coverage-seen-elsewhere:
+  size / size_column -> exercised below
+-->
+
+## What are markers useful for?
+
+- **Annotating fills**: Mark every executed order on the price line so traders can see where positions changed hands.
+- **Highlighting signals**: A strategy that generates buy/sell signals can render them as up/down arrows directly on the candlestick.
+- **Flagging events**: News releases, earnings announcements, or system events can be pinned to their timestamps as labeled circles.
+- **Picking out levels**: Price-based positions (`at_price_top`, `at_price_middle`, `at_price_bottom`) let a marker float independent of the bar: useful for marking option strikes or support/resistance touches.
+
+## Examples
+
+### Add a single static marker
+
+`tvl.marker()` builds one `Marker` object. Pass a list of them via the `markers=` keyword on any per-type constructor.
+
+```python order=single_marker_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+m = tvl.marker(
+    time="2024-01-15",
+    position="above_bar",
+    shape="arrow_down",
+    color="#d32f2f",
+    text="High",
+    size=2,
+    id="m1",
+)
+
+single_marker_chart = tvl.candlestick(ohlc, markers=[m])
+```
+
+The single marker hovers above the bar for 2024-01-15 with a downward red arrow.
+
+### Show every marker shape
+
+`MarkerShape` has four values: `"circle"`, `"square"`, `"arrow_up"`, `"arrow_down"`. The example below puts one of each on a single chart at staggered times.
+
+```python order=shapes_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+shapes = [
+    tvl.marker(time="2024-01-05", shape="circle",     color="#1976d2", text="circle"),
+    tvl.marker(time="2024-01-15", shape="square",     color="#2e7d32", text="square"),
+    tvl.marker(time="2024-01-25", shape="arrow_up",   color="#ef6c00", text="up"),
+    tvl.marker(time="2024-02-05", shape="arrow_down", color="#c62828", text="down"),
+]
+
+shapes_chart = tvl.line(ohlc, timestamp="Timestamp", value="Close", markers=shapes)
+```
+
+The four markers march across the chart, one shape per timestamp.
+
+### Show every marker position
+
+`MarkerPosition` has six values. The three bar-relative positions (`"above_bar"`, `"below_bar"`, `"in_bar"`) anchor to the bar at the given time. The three price-relative positions (`"at_price_top"`, `"at_price_bottom"`, `"at_price_middle"`) float at a specific `price` regardless of the bar.
+
+```python order=positions_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+positions = [
+    tvl.marker(time="2024-01-05", position="above_bar",
+               shape="arrow_down", text="above_bar"),
+    tvl.marker(time="2024-01-10", position="below_bar",
+               shape="arrow_up", text="below_bar"),
+    tvl.marker(time="2024-01-15", position="in_bar",
+               shape="circle", text="in_bar"),
+    # Price-based positions need a `price`.
+    tvl.marker(time="2024-01-20", position="at_price_top",
+               shape="square", price=110.0, text="at_price_top"),
+    tvl.marker(time="2024-01-25", position="at_price_middle",
+               shape="square", price=100.0, text="at_price_middle"),
+    tvl.marker(time="2024-01-30", position="at_price_bottom",
+               shape="square", price=90.0, text="at_price_bottom"),
+]
+
+positions_chart = tvl.candlestick(ohlc, markers=positions)
+```
+
+All six positions render together. The bar-relative ones move with the candle, the price-relative ones lock to their `price`.
+
+### Drive markers from a Deephaven table
+
+`tvl.markers_from_table()` builds a `MarkerSpec` instead of a list. Each row of the table becomes one marker; columns supply per-row values for any property that has a `*_column` parameter. Because the spec keeps a live reference to the table, markers tick when the table updates.
+
+```python order=table_markers_chart,signals,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+# Build a signals table off of the OHLC data: tag every 10th row alternately.
+signals = ohlc.update_view([
+    "Side = (ii % 20 < 10) ? `BUY` : `SELL`",
+    "Pos  = Side == `BUY` ? `below_bar` : `above_bar`",
+    "Sym  = Side == `BUY` ? `arrow_up` : `arrow_down`",
+    "Col  = Side == `BUY` ? `#2e7d32` : `#c62828`",
+    "Lbl  = Side",
+]).where("ii % 10 == 0")
+
+spec = tvl.markers_from_table(
+    signals, timestamp="Timestamp",
+    position_column="Pos",
+    shape_column="Sym",
+    color_column="Col",
+    text_column="Lbl",
+    size=1,
+    id_column="Side",
+)
+
+table_markers_chart = tvl.candlestick(ohlc, marker_spec=spec)
+```
+
+Pass the spec via the series' `marker_spec=` argument. As the source table ticks, new markers appear automatically.
+
+### Use fixed defaults with markers_from_table
+
+If every marker shares the same shape and color, omit the per-row column and set the fixed default directly. Mix-and-match is fine. Fixed values fill in for any property without a `*_column`.
+
+```python order=fixed_marker_chart,events,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+events = ohlc.where("ii % 7 == 0").update_view(["Note = `event ` + i"])
+
+spec = tvl.markers_from_table(
+    events, timestamp="Timestamp",
+    position="above_bar",   # fixed for every row
+    shape="circle",         # fixed for every row
+    color="#1976d2",        # fixed
+    text_column="Note",     # per-row
+    size=2,                 # fixed
+)
+
+fixed_marker_chart = tvl.candlestick(ohlc, marker_spec=spec)
+```
+
+The chart shows one blue circle per event, each labeled with its row's `Note`.
+
+### Price-driven markers from a table
+
+For `at_price_*` positions, supply a `price_column` so each row's price comes from the data.
+
+```python order=price_marker_chart,levels,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+levels = ohlc.where("ii % 12 == 0").update_view([
+    "Level = Close + 2.0",  # mark 2 above the close
+])
+
+spec = tvl.markers_from_table(
+    levels, timestamp="Timestamp",
+    position="at_price_top",
+    shape="square",
+    color="#ef6c00",
+    price_column="Level",
+    size_column=None,
+)
+
+price_marker_chart = tvl.candlestick(ohlc, marker_spec=spec)
+```
+
+The orange squares float at `Level`, independent of the candle's `High`/`Low`.
+
+### Use up_down_markers for buy/sell signals
+
+`tvl.up_down_markers()` is the shortcut for the most common pattern: a list of up timestamps and a list of down timestamps, rendered as arrows below/above the bar with theme-derived colors.
+
+```python order=updown_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+ups = ["2024-01-05", "2024-01-18", "2024-02-03"]
+downs = ["2024-01-12", "2024-01-25", "2024-02-10"]
+
+markers = tvl.up_down_markers(
+    up_times=ups,
+    down_times=downs,
+    up_color="#2e7d32",
+    down_color="#c62828",
+    up_text="BUY",
+    down_text="SELL",
+    up_size=2,
+    down_size=2,
+)
+
+updown_chart = tvl.candlestick(ohlc, markers=markers)
+```
+
+The helper returns a `list[Marker]` that drops straight into the series' `markers=` argument. The library sorts markers by time, so the order of `up_times` and `down_times` doesn't matter.
+
+### Type aliases: `MarkerSign` and `MismatchDirection`
+
+Two Literal aliases live alongside the marker API for completeness. `MarkerSign` annotates a marker's polarity (`"negative"`, `"neutral"`, `"positive"`); it threads through to the JS `SeriesMarker.sign` field and is mainly consumed by JS-side renderer hooks. `MismatchDirection` (`"nearest_left"`, `"none"`, `"nearest_right"`) selects the lookup behavior of `ISeriesApi.dataByIndex()` / `barsInLogicalRange()` on the JS runtime. It is exported for type-hint completeness and isn't accepted as a Python kwarg today.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+from typing import get_args
+
+# Sentinel snapshots of the two Literal aliases — useful when wiring
+# typed dataclasses or building marker payloads from a table.
+signs = list(get_args(tvl.MarkerSign))  # ["negative", "neutral", "positive"]
+directions = list(
+    get_args(tvl.MismatchDirection)
+)  # ["nearest_left", "none", "nearest_right"]
+
+assert signs == ["negative", "neutral", "positive"]
+assert directions == ["nearest_left", "none", "nearest_right"]
+```
+
+These constants are stable across releases; refer to them by name (e.g. `tvl.MarkerSign`) rather than re-typing the string literals.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.marker
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.markers_from_table
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.up_down_markers
+```
diff --git a/plugins/tradingview-lightweight/docs/multi-pane.md b/plugins/tradingview-lightweight/docs/multi-pane.md
new file mode 100644
index 000000000..d306e0a79
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/multi-pane.md
@@ -0,0 +1,154 @@
+# Multi-Pane Charts
+
+A multi-pane chart stacks several panes vertically inside one chart frame. Each pane has its own price scale, but they share the time axis along the bottom. Use panes when two series have incompatible value ranges (e.g. price in dollars vs. RSI in 0-100) or when you want to separate price action from indicators.
+
+The pane that a series lives in is set per series via the `pane` argument on every per-type constructor (or on the [convenience chart functions](#api-reference) like `tvl.line()`, `tvl.histogram()`). Per-chart options control how panes stretch, whether they survive when emptied, and what the separator between them looks like.
+
+<!-- coverage-seen-elsewhere:
+  price_scale_id -> multiple-axes.md
+  markers -> markers.md
+  price_lines -> price-lines.md
+  watermark_* -> watermark.md
+-->
+
+## What are multi-pane charts useful for?
+
+- **Mixing scales**: Price in dollars and RSI in [0, 100] don't fit on one axis. Stack them so each gets its own price scale without clobbering the other.
+- **Decluttering**: An indicator like MACD becomes unreadable when crammed into the price pane. A dedicated pane gives it room.
+- **Layered context**: Volume below price is a near-universal trading convention; panes encode this convention directly.
+- **Stable layouts on ticking data**: `pane_preserve_empty` keeps a pane visible even when its data hasn't arrived yet, so your dashboard layout doesn't jump around.
+
+## Examples
+
+### Stack price and volume into two panes
+
+This is the canonical pattern: price on top, volume on the bottom, sharing a time scale. Pass `pane=0` (the default) for the upper pane and `pane=1` for the lower.
+
+```python order=price_volume,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc, pane=0)
+volume = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume",
+    color="rgba(102,187,106,0.6)",
+    pane=1,
+)
+
+price_volume = tvl.chart(price, volume)
+```
+
+The two panes share the time axis but have independent price scales. The volume pane scales to its own min/max automatically.
+
+### Add a third pane for an indicator
+
+You aren't limited to two panes. Add as many as you need; each `pane=N` introduces a new pane below the previous one.
+
+```python order=three_pane,ohlc_rsi,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+# A fake "RSI-like" indicator just to fill the pane.
+ohlc_rsi = ohlc.update_view([
+    "Rsi = 50.0 + Math.sin(ii * 0.15) * 30.0",
+])
+
+price = tvl.candlestick(ohlc_rsi, pane=0)
+volume = tvl.histogram(
+    ohlc_rsi, timestamp="Timestamp", value="Volume", pane=1,
+    color="rgba(120,120,120,0.5)",
+)
+rsi = tvl.line(
+    ohlc_rsi, timestamp="Timestamp", value="Rsi", color="#ab47bc",
+    pane=2, title="RSI",
+)
+
+three_pane = tvl.chart(price, volume, rsi)
+```
+
+The three panes stack top-to-bottom in the same order as their `pane` indices.
+
+### Customize height ratios
+
+`pane_stretch_factors` is a list of weights (one per pane) that controls how vertical space is distributed. Default is equal weighting; bumping the price pane's factor gives it more room.
+
+```python order=stretched_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc, pane=0)
+volume = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume", pane=1,
+    color="rgba(120,120,120,0.5)",
+)
+
+# Price gets 3 units of vertical space; volume gets 1.
+stretched_chart = tvl.chart(price, volume, pane_stretch_factors=[3, 1])
+```
+
+A `[3, 1]` ratio makes the price pane three times as tall as the volume pane, regardless of the chart's outer height.
+
+### Preserve a pane when it's empty
+
+`pane_preserve_empty` is a list of booleans (one per pane) controlling whether a pane remains visible when its data is empty (no rows yet, or filtered away). Useful when a downstream table hasn't ticked yet but the layout should still allocate space.
+
+```python order=preserve_chart,ohlc_filter,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+# Filter the volume away to demonstrate the empty pane.
+ohlc_filter = ohlc.where("Volume > 9999999")  # always empty
+
+price = tvl.candlestick(ohlc, pane=0)
+volume = tvl.histogram(
+    ohlc_filter, timestamp="Timestamp", value="Volume", pane=1,
+    color="rgba(120,120,120,0.5)",
+)
+
+preserve_chart = tvl.chart(
+    price, volume,
+    pane_stretch_factors=[3, 1],
+    pane_preserve_empty=[False, True],  # keep the empty volume pane visible
+)
+```
+
+Without `pane_preserve_empty=[..., True]`, an empty pane collapses and the chart auto-resizes; with it, the layout is stable while you wait for the data.
+
+### Style the pane separator
+
+The thin bar between panes is styled by `pane_separator_color`, `pane_separator_hover_color`, and `pane_enable_resize`.
+
+```python order=styled_pane,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc, pane=0)
+volume = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume", pane=1,
+    color="rgba(120,120,120,0.5)",
+)
+
+styled_pane = tvl.chart(
+    price, volume,
+    pane_separator_color="#1976d2",
+    pane_separator_hover_color="#42a5f5",
+    pane_enable_resize=True,
+)
+```
+
+When `pane_enable_resize=True` (the default), the user can drag the separator to rebalance the panes; setting it to `False` locks the ratio at whatever `pane_stretch_factors` produced.
+
+## API Reference
+
+The chart entry point is `tvl.chart()`. The pane-related options it accepts are `pane_stretch_factors`, `pane_preserve_empty`, `pane_separator_color`, `pane_separator_hover_color`, and `pane_enable_resize`. Series factories all accept a `pane` keyword.
+
+For the full `tvl.chart` signature, see the [Chart container](chart.md#api-reference) page.
+
+```{eval-rst}
+```
+
+```{eval-rst}
+```
diff --git a/plugins/tradingview-lightweight/docs/multi-series.md b/plugins/tradingview-lightweight/docs/multi-series.md
new file mode 100644
index 000000000..4a133cf9e
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/multi-series.md
@@ -0,0 +1,154 @@
+# Multi-Series Charts
+
+A multi-series TradingView Lightweight chart is a single chart that hosts two or more independent series, for example a candlestick price series with a moving-average line drawn on top. Use it to overlay related data on shared axes rather than stacking it into separate panes.
+
+There are two ways to end up with multiple series. The explicit pattern, used for most of this page, is to call one per-type constructor per series to build a single-series TvlChart and pass them positionally to [`tvl.chart()`](#api-reference); use this when you mix series *types* or pull series from different tables. The shortcut, when the series share a type and a single table and differ only by a partition column, is to pass `by="Column"` to one constructor and let the chart fan it out into one series per key (see [Create one series per group with `by`](#create-one-series-per-group-with-by) below). Either way there is no `add_series()` method on `TvlChart`; series are immutable once the chart is constructed.
+
+<!-- coverage-seen-elsewhere:
+  pane_index -> multi-pane.md
+  price_scale_id -> multiple-axes.md
+  default_visible_price_scale_id -> multiple-axes.md
+  pane_stretch_factors -> multi-pane.md
+  pane_preserve_empty -> multi-pane.md
+  watermark_* -> watermark.md
+  markers -> markers.md
+  price_lines -> price-lines.md
+  marker_spec -> markers.md
+  price_format -> price-formats.md
+  *_formatter -> price-formats.md
+  base_resolution / minimum_time_range / start_time_range -> yield-curve.md
+  auto_bin / bin_width / bin_count / agg -> autobin.md
+-->
+
+## What are multi-series charts useful for?
+
+- **Overlaying indicators**: Plot a moving average, VWAP, or Bollinger band on top of a candlestick chart so traders can read price and signal together.
+- **Comparing instruments**: Show two line series on a single axis to compare prices for related symbols (e.g. an ETF and its benchmark).
+- **Mixing chart types**: Combine a candlestick body with a histogram volume series so price action and traded size share a horizontal time scale.
+- **Layering events on data**: Use markers and price lines on the same series to annotate trades or thresholds without losing the underlying price curve.
+
+## Examples
+
+### Pick the chart-type backend explicitly
+
+`tvl.chart()` accepts a `chart_type` kwarg, typed as the `ChartType` literal alias. The default value is `"standard"`, which is what every example below relies on. The other three values (`"yield_curve"`, `"options"`, and `"custom_numeric"`) are already used by the convenience factories `tvl.yield_curve()`, `tvl.options_chart()`, and `tvl.custom_numeric()`, so you rarely call `chart()` with them directly; mostly you set `chart_type="standard"` explicitly when you want to lock the backend against future default changes.
+
+```python order=chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+# chart_type defaults to "standard"; the other values ("yield_curve",
+# "options", "custom_numeric") are surfaced via tvl.yield_curve(),
+# tvl.options_chart(), and tvl.custom_numeric() respectively.
+chart = tvl.chart(
+    tvl.candlestick(ohlc),
+    chart_type="standard",
+)
+```
+
+### Build a chart from a list of series
+
+`tvl.chart()` takes one or more TvlChart objects as positional arguments. Each per-type constructor binds a Deephaven table to a series type, with no plotting until `tvl.chart()` is called.
+
+```python order=multi_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(
+    ohlc, timestamp="Timestamp", open="Open", high="High", low="Low", close="Close",
+)
+volume = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume", color="rgba(76,175,80,0.5)",
+)
+
+multi_chart = tvl.chart(price, volume)
+```
+
+Both series share one chart: they sit on the same time axis and the same price axis by default. Push the volume to a separate pane or scale using `pane` or `price_scale_id` (see [multi-pane](multi-pane.md) and [multiple-axes](multiple-axes.md)).
+
+### Overlay a moving-average line on a candlestick
+
+The "price + indicator" pattern: a candlestick series for the bars and a line series for a derived signal. The line is computed in a Deephaven `update_view` so it ticks along with the source table.
+
+```python order=overlay_chart,ohlc_with_sma,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+ohlc_with_sma = ohlc.update_view([
+    "Sma = (Close + Close_[i-1] + Close_[i-2]) / 3",
+])
+
+bars = tvl.candlestick(ohlc_with_sma)
+sma = tvl.line(
+    ohlc_with_sma, timestamp="Timestamp", value="Sma",
+    color="#ff9800", line_width=2,
+)
+
+overlay_chart = tvl.chart(bars, sma, watermark_text="Price + SMA(3)")
+```
+
+The candlestick TvlChart provides the price axis; the SMA line draws on the same scale.
+
+### Compare two line series on one axis
+
+For pure comparison, build one `line` per group and pass both to `tvl.chart()`. Each series is given an explicit `title` so the legend distinguishes them.
+
+```python order=compare_chart,aaa,bbb,stocks
+import deephaven.plot.tradingview_lightweight as tvl
+
+stocks = tvl.data.stocks()
+aaa = stocks.where("Sym = `AAA`")
+bbb = stocks.where("Sym = `BBB`")
+
+s_aaa = tvl.line(aaa, timestamp="Timestamp", value="Price",
+                       color="#1976d2", title="AAA")
+s_bbb = tvl.line(bbb, timestamp="Timestamp", value="Price",
+                       color="#d32f2f", title="BBB")
+
+compare_chart = tvl.chart(s_aaa, s_bbb)
+```
+
+Two line series share one chart, one time axis, and one price axis.
+
+### Mix a line with a histogram
+
+A line series plotted against a histogram series is useful when you need to read a continuous quantity (price) against a discrete count (volume) on a shared time axis.
+
+```python order=mix_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+closes = tvl.line(ohlc, timestamp="Timestamp", value="Close",
+                        color="#2e7d32", line_width=2)
+vols = tvl.histogram(ohlc, timestamp="Timestamp", value="Volume",
+                            color="rgba(120,120,120,0.45)",
+                            price_scale_id="vol")
+
+mix_chart = tvl.chart(closes, vols)
+```
+
+The histogram lives on an overlay scale (`price_scale_id="vol"`) so its magnitudes don't crush the line's price range. See [multiple-axes](multiple-axes.md) for the full pattern.
+
+### Create one series per group with `by`
+
+The comparisons above build each series by hand, one constructor call per symbol. When the series differ only by a partition key in a single table, set `by` to that column instead and the chart draws one series per unique value, auto-assigning each a distinct color from the user's theme palette. New keys that show up at runtime (in a ticking table) add new series on the fly.
+
+`by` is accepted by every per-type constructor (`tvl.line`, `tvl.area`, `tvl.baseline`, `tvl.candlestick`, `tvl.bar`, `tvl.histogram`), so this single-table-to-many-series shortcut works regardless of series type.
+
+```python order=by_chart,stocks
+import deephaven.plot.tradingview_lightweight as tvl
+
+stocks = tvl.data.stocks()
+
+# One line per symbol, colored automatically — no per-series construction.
+by_chart = tvl.line(stocks, timestamp="Timestamp", value="Price", by="Sym")
+```
+
+`tvl.data.stocks()` is a three-symbol (`AAA`, `BBB`, `CCC`) walk, so this single `tvl.line` call yields three independently colored series on one axis, the same result as the [two-line comparison](#compare-two-line-series-on-one-axis) above, but driven by the data rather than spelled out series by series. For per-type notes on `by`, see [line](line.md#one-line-per-group-with-by) and [area](area.md#one-area-per-group-with-by).
+
+## API Reference
+
+For the full `tvl.chart` signature, see the [Chart container](chart.md#api-reference) page. The per-type constructor signatures (`tvl.line`, `tvl.candlestick`, `tvl.area`, `tvl.bar`, `tvl.baseline`, `tvl.histogram`) live on their own pages.
diff --git a/plugins/tradingview-lightweight/docs/multiple-axes.md b/plugins/tradingview-lightweight/docs/multiple-axes.md
new file mode 100644
index 000000000..d0bfa76e7
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/multiple-axes.md
@@ -0,0 +1,199 @@
+# Multiple Price Scales
+
+A multiple-axes chart hosts more than one price scale inside a single pane. Use it when two series share a time axis but their value ranges are too different to share one price scale, for example a stock price (10-200) and trade volume (1,000-2,000,000) layered in the same pane.
+
+The mechanism is the `price_scale_id` parameter on every per-type constructor. Lightweight Charts provides two built-in scales, `"left"` and `"right"`, and treats any other string as an **overlay** scale that floats on top of the chart with no axis labels by default. The chart-level `default_visible_price_scale_id` option picks which built-in scale unbound series fall back to.
+
+<!-- coverage-seen-elsewhere:
+  pane / pane_stretch_factors / pane_preserve_empty -> multi-pane.md
+  price_format -> price-formats.md
+  *_formatter -> price-formats.md
+  markers / price_lines / marker_spec -> markers.md, price-lines.md
+  watermark_* -> watermark.md
+-->
+
+## What are multiple price scales useful for?
+
+- **Mixing magnitudes**: Price in dollars and volume in millions don't share a range. Two scales keep each readable.
+- **Comparing returns**: A `"percentage"` price scale lets you compare two instruments by relative change rather than absolute price.
+- **Hiding clutter**: Overlay scales render a series with no visible axis labels, which suits background indicators that exist to be read on hover, not on the axis.
+- **Per-scale tick density**: `*_tick_mark_density` lets a busy price scale stay readable when the chart is short.
+
+## Examples
+
+### Put one series on the left, one on the right
+
+Two series, two built-in scales. Set `price_scale_id="left"` to draw the axis on the left, and `"right"` (the default) for the right.
+
+```python order=lr_chart,stocks,aaa,bbb
+import deephaven.plot.tradingview_lightweight as tvl
+
+stocks = tvl.data.stocks()
+aaa = stocks.where("Sym = `AAA`")
+bbb = stocks.where("Sym = `BBB`")
+
+s_aaa = tvl.line(
+    aaa, timestamp="Timestamp", value="Price",
+    color="#1976d2", price_scale_id="left", title="AAA",
+)
+s_bbb = tvl.line(
+    bbb, timestamp="Timestamp", value="Price",
+    color="#d32f2f", price_scale_id="right", title="BBB",
+)
+
+lr_chart = tvl.chart(
+    s_aaa, s_bbb,
+    left_price_scale_visible=True,
+    right_price_scale_visible=True,
+)
+```
+
+The chart shows two axes: AAA's scale on the left, BBB's on the right.
+
+### Use an overlay scale to layer a series on top
+
+An overlay scale is any `price_scale_id` other than `"left"` or `"right"`. The series renders against its own y-range without taking up axis space. This is the "volume on top of price" pattern.
+
+```python order=overlay_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc, price_scale_id="right")
+vol = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume",
+    color="rgba(120,120,120,0.5)",
+    price_scale_id="volume",  # overlay scale, anything not "left"/"right"
+    scale_margin_top=0.8,     # squash volume into the bottom 20%
+    scale_margin_bottom=0.0,
+)
+
+overlay_chart = tvl.chart(
+    price, vol,
+    overlay_price_scale_margin_top=0.8,
+    overlay_price_scale_margin_bottom=0.0,
+)
+```
+
+The volume histogram sits at the bottom of the price pane with no visible axis labels.
+
+### Switch the default scale
+
+`default_visible_price_scale_id` picks which built-in scale series fall back to when they don't set their own `price_scale_id`. Default is `"right"`; flip it to `"left"` to make unbound series snap to the left.
+
+```python order=default_left,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+# Note: no price_scale_id set on the series.
+price = tvl.candlestick(ohlc)
+
+default_left = tvl.chart(
+    price,
+    default_visible_price_scale_id="left",
+    left_price_scale_visible=True,
+    right_price_scale_visible=False,
+)
+```
+
+With `default_visible_price_scale_id="left"`, the candlestick series renders against the left axis even though it didn't ask for one.
+
+### Style the left, right, and overlay scales
+
+Each scale (`left`, `right`, `overlay`) has its own block of chart-level options. They mirror each other; here we set border color, text color, and mode independently.
+
+```python order=styled_scales,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc, price_scale_id="right")
+ma = tvl.line(
+    ohlc, timestamp="Timestamp", value="Close",
+    color="#ff9800", price_scale_id="left",
+)
+vol = tvl.histogram(
+    ohlc, timestamp="Timestamp", value="Volume",
+    color="rgba(120,120,120,0.5)", price_scale_id="vol",
+)
+
+styled_scales = tvl.chart(
+    price, ma, vol,
+    # right (price) — log-scale demonstration
+    right_price_scale_visible=True,
+    right_price_scale_mode="logarithmic",
+    right_price_scale_border_color="#1976d2",
+    right_price_scale_text_color="#1976d2",
+    # left (MA) — percentage mode
+    left_price_scale_visible=True,
+    left_price_scale_mode="percentage",
+    left_price_scale_border_color="#ff9800",
+    left_price_scale_text_color="#ff9800",
+    # overlay (volume)
+    overlay_price_scale_border_color="#999",
+    overlay_price_scale_ticks_visible=False,
+)
+```
+
+Three scales, three colors. Note the modes: the right scale is log-scaled while the left runs in percentage mode (try `"normal"` or `"indexed_to_100"` as alternatives).
+
+### Tune tick mark density per scale
+
+`*_price_scale_tick_mark_density` controls how aggressively each scale draws tick labels. Higher values pack more ticks; lower values thin them out.
+
+```python order=density_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc, price_scale_id="right")
+ma = tvl.line(
+    ohlc, timestamp="Timestamp", value="Close",
+    color="#ff9800", price_scale_id="left",
+)
+
+density_chart = tvl.chart(
+    price, ma,
+    left_price_scale_visible=True,
+    right_price_scale_visible=True,
+    right_price_scale_tick_mark_density=2.0,   # extra ticks
+    left_price_scale_tick_mark_density=0.5,    # half as many ticks
+)
+```
+
+The right scale gets more tick labels; the left gets fewer. Use this to balance readability across scales that have different value ranges.
+
+### Auto-scale and invert per scale
+
+Each scale exposes `*_auto_scale` and `*_invert_scale` for fine control. Invert flips the axis upside-down, which helps with bid-spread or option-greek charts where lower values are "higher" conceptually.
+
+```python order=invert_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(
+    ohlc, price_scale_id="right",
+    scale_invert=True,        # per-series shortcut
+    auto_scale=True,
+)
+
+invert_chart = tvl.chart(
+    price,
+    right_price_scale_invert_scale=True,  # same effect at the chart level
+    right_price_scale_auto_scale=True,
+)
+```
+
+`scale_invert` on the series and `right_price_scale_invert_scale` on the chart are equivalent ways to flip the right axis.
+
+## API Reference
+
+For the full `tvl.chart` signature (including all `left_price_scale_*`, `right_price_scale_*`, and `overlay_price_scales` options), see the [Chart container](chart.md#api-reference) page.
+
+```{eval-rst}
+```
+
+```{eval-rst}
+```
diff --git a/plugins/tradingview-lightweight/docs/options-chart.md b/plugins/tradingview-lightweight/docs/options-chart.md
new file mode 100644
index 000000000..b6d1b78c9
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/options-chart.md
@@ -0,0 +1,113 @@
+<!-- coverage-seen-elsewhere:
+  crosshair_mode -> styling.md
+  watermark_text -> watermark.md
+  background_color -> styling.md
+  text_color -> styling.md
+-->
+
+# Options Chart
+
+An options chart plots a quantity against *strike price* on a numeric horizontal axis, not against time. The renderer is TVL's `createOptionsChart`, which is designed for cross-sectional snapshots indexed by strike: option bid/ask curves, implied-vol smiles, open-interest profiles, and gamma exposure.
+
+`tvl.options_chart` supports three series types: `"line"` (default), `"area"`, and `"histogram"`. They share the same axis behavior; only the rendering changes.
+
+## What are options charts useful for?
+
+- **Option price curves**: Plot CallBid/CallAsk across strikes to see the price structure across the chain.
+- **Volatility smiles**: Implied vol vs. strike is the "smile" or "skew" chart this rendering is built for.
+- **Open interest / volume profiles**: Histogram mode turns the same chart into a strike-indexed bar chart of open interest or daily volume.
+- **Gamma exposure**: Net gamma by strike (positive bars above zero, negative below) reads cleanly as a histogram or signed line.
+
+## Examples
+
+### A basic options curve
+
+`tvl.data.options_chain()` is a 21-strike snapshot with columns `Strike`, `CallBid`, `CallAsk`, `PutBid`, `PutAsk`. Point `strike` and `value` at the right columns; defaults pick `series_type="line"`.
+
+```python order=options_chart,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.options_chain()
+
+options_chart = tvl.options_chart(data, strike="Strike", value="CallBid")
+```
+
+A single line traces call bids from the 50 strike to the 150 strike.
+
+### Switch to an area rendering
+
+`series_type="area"` fills the area under the curve. Useful for "stacked" reads of a single quantity (e.g. notional gamma) where the magnitude under each strike matters.
+
+```python order=options_chart,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.options_chain()
+
+options_chart = tvl.options_chart(
+    data,
+    strike="Strike",
+    value="CallBid",
+    series_type="area",
+    top_color="rgba(214, 39, 40, 0.5)",
+    bottom_color="rgba(214, 39, 40, 0.0)",
+    line_color="#d62728",
+)
+```
+
+The filled area fades to transparent at the bottom; the rim is solid red.
+
+### Switch to a histogram rendering
+
+`series_type="histogram"` renders one bar per strike. Pair it with the `color` parameter and a stronger contrast so the bars register clearly.
+
+```python order=options_chart,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.options_chain()
+
+options_chart = tvl.options_chart(
+    data,
+    strike="Strike",
+    value="CallBid",
+    series_type="histogram",
+    color="#9467bd",
+)
+```
+
+One purple bar rises at each of the 21 strikes.
+
+### Customize color and width (line mode)
+
+`color` is the line CSS color; `line_width` is the integer pixel width (1-4); `title` is the legend label.
+
+```python order=options_chart,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.options_chain()
+
+options_chart = tvl.options_chart(
+    data,
+    strike="Strike",
+    value="CallBid",
+    color="#2ca02c",
+    line_width=2,
+    title="Call bid curve",
+)
+```
+
+The line is green, two pixels wide, with a custom legend entry.
+
+### Plot a different value column
+
+The y-axis can be any numeric column. Swap `CallBid` for `PutAsk` (or implied vol, open interest, gamma, whatever your table has) without touching the rest of the call.
+
+```python order=options_chart,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.options_chain()
+
+options_chart = tvl.options_chart(data, strike="Strike", value="PutAsk")
+```
+
+The chart now traces the put-ask curve instead of the call-bid curve.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.options_chart
+```
diff --git a/plugins/tradingview-lightweight/docs/price-formats.md b/plugins/tradingview-lightweight/docs/price-formats.md
new file mode 100644
index 000000000..bf47da2ec
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/price-formats.md
@@ -0,0 +1,262 @@
+<!-- coverage-seen-elsewhere:
+  price_format on series -> candlestick.md, line.md, area.md
+  watermark_text -> watermark.md
+-->
+
+# Price Formats
+
+Price formatters control how numeric values appear on price-axis tick labels, crosshair labels, and last-value labels. TVL provides five typed surfaces: `PriceFormat` (per-series), and four chart-level named-preset enums (`PriceFormatter`, `TickmarksPriceFormatter`, `PercentageFormatter`, `TickmarksPercentageFormatter`). They cover the common currency, percent, volume, and scientific notation cases without writing a JavaScript formatter.
+
+Reach for `PriceFormat` when you need precision-level control on one series; reach for the chart-level named presets when you want every label across the chart to share a single format.
+
+## What are price formats useful for?
+
+- **Matching market conventions**: USD equities want two decimals, JPY pairs want zero, FX wants four. Pick the right preset and the crosshair label matches the venue you trade on.
+- **Volume formatting**: Render volume axes as `1.2M` instead of `1,234,567` by using `type="volume"` on the histogram series.
+- **Percent overlays**: A percentage-mode price scale needs a percent formatter; pair it with `scale_mode="percentage"` for relative-return overlays.
+- **Tick density and label width**: A compact formatter (`"compact"`) keeps long-number axes from pushing the plot area narrow.
+
+## Examples
+
+### Set per-series price format with `PriceFormat`
+
+`PriceFormat` is a `TypedDict` you build inline and pass to the `price_format=` parameter of any series factory. `type` selects the kind (`"price"`, `"volume"`, `"percent"`), `precision` is the number of decimal places, and `minMove` is the smallest representable step (note the camelCase; it's a passthrough to the JS layer).
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.line(
+    values,
+    timestamp="Timestamp",
+    value="Value",
+    price_format={"type": "price", "precision": 4, "minMove": 0.0001},
+)
+```
+
+Use this when your data is denominated in a unit that doesn't match the chart-level locale or formatter.
+
+### Format volume with `PriceFormat`
+
+For volume axes (and any large-number axis), `type="volume"` tells lightweight-charts to render large values in a human-readable form. Combine it with the histogram chart for the canonical price + volume pane stack.
+
+```python order=chart,volume
+import deephaven.plot.tradingview_lightweight as tvl
+
+volume = tvl.data.volume()
+
+chart = tvl.histogram(
+    volume,
+    timestamp="Timestamp",
+    value="Volume",
+    price_format={"type": "volume", "precision": 0},
+)
+```
+
+Set `precision=0` for whole-share volume; use `precision=2` if you're plotting dollar volume.
+
+### Format a percent series with `PriceFormat`
+
+`type="percent"` renders raw percentage values (e.g. `42.5` as `42.5%`) on the price axis. Use this for return overlays where the underlying series already holds percentages.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+returns = values.update_view(["Value = (Value - 100.0) / 100.0 * 100.0"])
+
+chart = tvl.line(
+    returns,
+    timestamp="Timestamp",
+    value="Value",
+    price_format={"type": "percent", "precision": 2},
+)
+```
+
+If you actually want the price scale to be in percent mode (not just the labels), pair this with `scale_mode="percentage"` on the series; see [price-scale](price-scale.md).
+
+### Pick a named price formatter for crosshair labels
+
+`PriceFormatter` is the chart-level named preset for the crosshair price label and last-value label. Set `price_formatter="currency_usd"` and every numeric label gets the `$1,234.56` shape. Pair it with `locale="en-US"` to lock down thousands separators and decimal punctuation.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    price_formatter="currency_usd",
+    locale="en-US",
+)
+```
+
+The `PriceFormatter` enum values are `"currency_usd"`, `"currency_eur"`, `"currency_gbp"`, `"currency_jpy"`, `"percent"`, `"compact"`, and `"scientific"`.
+
+### Switch between USD, EUR, GBP, and JPY presets
+
+The `PriceFormatter` and `TickmarksPriceFormatter` aliases both accept the same four currency presets plus `"percent"`, `"compact"`, and `"scientific"`. Pick whichever matches your data and locale.
+
+```python order=usd,eur,gbp,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+usd = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    price_formatter="currency_usd",
+    tickmarks_price_formatter="currency_usd",
+    locale="en-US",
+)
+eur = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    price_formatter="currency_eur",
+    tickmarks_price_formatter="currency_eur",
+    locale="de-DE",
+)
+gbp = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    price_formatter="currency_gbp",
+    tickmarks_price_formatter="currency_gbp",
+    locale="en-GB",
+)
+```
+
+Each currency preset wraps numbers in the right symbol; the `locale` kwarg controls the thousands separator and decimal mark.
+
+### Use the JPY currency preset
+
+`"currency_jpy"` is the only preset that defaults to zero decimal places, matching how yen pairs are conventionally quoted. Pair it with `locale="ja-JP"` for fully-localized thousands separators.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    price_formatter="currency_jpy",
+    locale="ja-JP",
+)
+```
+
+If you need a different decimal count, drop down to `PriceFormat` and set `precision` explicitly.
+
+### Use the compact preset for high-volume axes
+
+`"compact"` renders 1234 as `1.23K`, 12,345,678 as `12.35M`, and so on. Useful for axes that span many orders of magnitude.
+
+```python order=chart,volume
+import deephaven.plot.tradingview_lightweight as tvl
+
+volume = tvl.data.volume()
+big_volume = volume.update_view(["Volume = Volume * 1_000_000"])
+
+chart = tvl.chart(
+    tvl.histogram(big_volume, timestamp="Timestamp", value="Volume"),
+    price_formatter="compact",
+)
+```
+
+This is the simplest answer to "I want my axis to show K/M/B suffixes."
+
+### Scientific notation for wide-range axes
+
+`"scientific"` renders values as `1.23e+5`. Reach for it when the axis spans many orders of magnitude (latency in nanoseconds vs seconds, etc.) and you want exponents instead of compact suffixes.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+scientific_values = values.update_view(["Value = Value * 1e-9"])
+
+chart = tvl.chart(
+    tvl.line(scientific_values, timestamp="Timestamp", value="Value"),
+    price_formatter="scientific",
+)
+```
+
+### Format axis tick labels separately
+
+`TickmarksPriceFormatter` controls the *tick label* on the price axis, while `PriceFormatter` controls the *crosshair* label. The enum values are identical but the two parameters are independent: you can render `$1,234.56` on the crosshair while showing a compact `1.2K` on the axis ticks.
+
+```python order=chart,volume
+import deephaven.plot.tradingview_lightweight as tvl
+
+volume = tvl.data.volume().update_view(["Volume = Volume * 1_000_000"])
+
+chart = tvl.chart(
+    tvl.histogram(volume, timestamp="Timestamp", value="Volume"),
+    price_formatter="currency_usd",
+    tickmarks_price_formatter="compact",
+)
+```
+
+This split keeps detailed values in the crosshair without blowing out the axis width.
+
+### Format percentages with `PercentageFormatter`
+
+`PercentageFormatter` is the named-preset enum for the crosshair *percentage* label, used when a price scale is in percentage mode. Its four values trade precision for compactness: `"percent"` shows two decimals, `"percent_1dp"` one, `"percent_0dp"` zero, and `"decimal"` falls back to the raw ratio.
+
+```python order=chart,decimal,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", scale_mode="percentage"),
+    percentage_formatter="percent_1dp",
+)
+
+# Use the raw-ratio fall-back when your audience reads `0.42` instead of `42%`.
+decimal = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", scale_mode="percentage"),
+    percentage_formatter="decimal",
+    tickmarks_percentage_formatter="decimal",
+)
+```
+
+Switch to `"percent_0dp"` for a tighter dashboard layout or to `"decimal"` if your audience reads raw ratios.
+
+### Format percentage tick marks
+
+`TickmarksPercentageFormatter` mirrors `PercentageFormatter` but controls the axis ticks themselves. Use it together with a percentage price scale to render ticks like `42%` while the crosshair shows `42.5%`.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", scale_mode="percentage"),
+    percentage_formatter="percent",
+    tickmarks_percentage_formatter="percent_0dp",
+)
+```
+
+The four `TickmarksPercentageFormatter` values match `PercentageFormatter`: `"percent"`, `"percent_1dp"`, `"percent_0dp"`, `"decimal"`.
+
+### Custom precision for tiny-tick instruments
+
+For instruments quoted in tiny increments (FX 4-pip, low-priced crypto), build a `PriceFormat` with the right `precision` and `minMove` rather than reaching for a preset. The chart formatter respects the precision exactly.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+fx = values.update_view(["Value = Value * 0.0001"])
+
+chart = tvl.line(
+    fx,
+    timestamp="Timestamp",
+    value="Value",
+    price_format={"type": "price", "precision": 5, "minMove": 0.00001},
+)
+```
+
+The JS API supports a `'custom'` `type` for arbitrary formatter callbacks, but that's not available from Python, since it requires a JavaScript function. Stick with the built-in `"price"`, `"volume"`, and `"percent"` types or use the chart-level named presets.
+
+## API Reference
+
+For the full `tvl.chart` signature, see the [Chart container](chart.md#api-reference) page.
diff --git a/plugins/tradingview-lightweight/docs/price-lines.md b/plugins/tradingview-lightweight/docs/price-lines.md
new file mode 100644
index 000000000..a98d3c497
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/price-lines.md
@@ -0,0 +1,193 @@
+# Price Lines
+
+A price line is a horizontal line drawn across a series at a specific price, the visual equivalent of "draw a line at $100 across the chart". Use price lines when you need to annotate fixed levels (entry, stop, target, strike) or track a live, table-driven value such as a moving threshold.
+
+There are two ways to build a price line. Use [`tvl.price_line()`](#api-reference) for a static level (`price=100`) or for a Deephaven-extension column-driven level (`column="ThresholdCol"`) where the line tracks the last row of a named column as the table ticks. The returned `PriceLine` object goes onto a series via the `price_lines=` argument.
+
+## What are price lines useful for?
+
+- **Marking levels**: Entry, stop, and target levels on a trade can be drawn as static price lines so they sit alongside the candlestick body.
+- **Showing thresholds**: A risk threshold or alert level becomes a single horizontal line on the chart pane.
+- **Following live values**: A column-driven price line tracks the most recent row of a table, which works well for "current best bid" or "current VWAP" on a ticking stream.
+- **Annotating with labels**: Each price line carries a `title` (drawn on the pane) and an axis label with its own colors, so the level can describe itself.
+
+## Examples
+
+### Add a simple horizontal line at a price
+
+The minimal price line. Pass it to a series via `price_lines=[...]`.
+
+```python order=simple_line,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+target = tvl.price_line(price=104.0, color="#2e7d32")
+
+simple_line = tvl.candlestick(ohlc, price_lines=[target])
+```
+
+A green horizontal line sits at 104.0 across the entire chart.
+
+### Style a price line
+
+Most visual properties of a `PriceLine` are independent: color, width, dashing, and whether the line itself is drawn. The supported widths are `1`, `2`, `3`, `4`; styles come from `LineStyle` (`"solid"`, `"dotted"`, `"dashed"`, `"large_dashed"`, `"sparse_dotted"`).
+
+```python order=styled_line,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+styled = tvl.price_line(
+    price=104.0,
+    color="#d32f2f",
+    line_width=3,
+    line_style="dashed",
+    line_visible=True,
+    id="stop-loss",
+)
+
+styled_line = tvl.candlestick(ohlc, price_lines=[styled])
+```
+
+A dashed red line at 104.0, three pixels wide.
+
+### Add a title and an axis label
+
+The `title` is drawn next to the line on the chart pane. The axis label (which sits on the price scale) is controlled by `axis_label_visible`, `axis_label_color`, and `axis_label_text_color`.
+
+```python order=labeled_line,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+labeled = tvl.price_line(
+    price=98.0,
+    color="#1976d2",
+    line_width=2,
+    line_style="solid",
+    title="Support",
+    axis_label_visible=True,
+    axis_label_color="#1976d2",
+    axis_label_text_color="#ffffff",
+)
+
+labeled_line = tvl.candlestick(ohlc, price_lines=[labeled])
+```
+
+The line is labeled `Support` on the chart and `98.00` on the axis (with a blue background).
+
+### Draw many price lines at once
+
+A list of price lines can be attached to one series. This is the natural way to show a set of strikes, ladder levels, or stop placements.
+
+```python order=ladder_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+ladder = [
+    tvl.price_line(price=p, color=c, line_style=style, title=label)
+    for p, c, style, label in [
+        (104.0, "#2e7d32", "solid",       "Target"),
+        (102.0, "#558b2f", "dotted",      "Trim"),
+        (100.0, "#1976d2", "dashed",      "Entry"),
+        ( 98.0, "#ef6c00", "large_dashed","Trail stop"),
+        ( 96.0, "#c62828", "sparse_dotted","Hard stop"),
+    ]
+]
+
+ladder_chart = tvl.candlestick(ohlc, price_lines=ladder)
+```
+
+Five horizontal lines, each using a different `LineStyle` value, label the trading ladder. Notice the loop covers all five styles in `LineStyle`.
+
+### Hide the line, keep the axis label
+
+`line_visible=False` removes the horizontal stroke from the pane but keeps the axis label on the price scale. This is useful when you want a value annotation without cluttering the chart body.
+
+```python order=labelonly_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+invisible = tvl.price_line(
+    price=100.0,
+    line_visible=False,
+    axis_label_visible=True,
+    axis_label_color="#1976d2",
+    axis_label_text_color="#ffffff",
+    title="Par",
+    id="par-level",
+)
+
+labelonly_chart = tvl.candlestick(ohlc, price_lines=[invisible])
+```
+
+The chart shows the axis tag for 100.00 with no line drawn through the pane.
+
+### Track a live column value
+
+This is the Deephaven extension to `price_line()`. Pass `column=` instead of `price=` and the line tracks the last row of that column. When the source table ticks, the price line moves automatically.
+
+```python order=live_line,ohlc_w_avg,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+# Running mean — last row is the current value.
+ohlc_w_avg = ohlc.update_view(["AvgClose = avg(Close)"])
+
+live = tvl.price_line(
+    column="AvgClose",
+    color="#ef6c00",
+    line_width=2,
+    line_style="solid",
+    title="avg(Close)",
+)
+
+live_line = tvl.candlestick(ohlc_w_avg, price_lines=[live])
+```
+
+The orange line tracks the running mean of `Close`. It is mutually exclusive with `price=`; setting both, or neither, raises `ValueError`.
+
+### Pick the source for the built-in last-price line
+
+Separate from user-added price lines, every series has an automatic "last price" horizontal line. The `price_line_source` argument (a `PriceLineSource` enum value) picks whether it follows the last bar or the last visible bar. Set it on the series factory.
+
+```python order=source_chart,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+# Follow the last bar in the data, regardless of scroll position.
+last_bar = tvl.line(
+    ohlc, timestamp="Timestamp", value="Close",
+    color="#1976d2",
+    price_line_visible=True,
+    price_line_source="last_bar",
+    price_line_color="#1976d2",
+    price_line_width=2,
+    price_line_style="dotted",
+)
+
+# Follow the last visible bar — moves as you scroll.
+last_visible = tvl.line(
+    ohlc, timestamp="Timestamp", value="Open",
+    color="#d32f2f",
+    price_line_visible=True,
+    price_line_source="last_visible",
+    price_line_color="#d32f2f",
+    price_line_width=2,
+    price_line_style="dashed",
+)
+
+source_chart = tvl.chart(last_bar, last_visible)
+```
+
+Two series with different `price_line_source` values demonstrate both members of the `PriceLineSource` enum (`"last_bar"`, `"last_visible"`).
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.price_line
+```
diff --git a/plugins/tradingview-lightweight/docs/price-scale.md b/plugins/tradingview-lightweight/docs/price-scale.md
new file mode 100644
index 000000000..b3171d2a0
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/price-scale.md
@@ -0,0 +1,260 @@
+<!-- coverage-seen-elsewhere:
+  default_visible_price_scale_id -> multiple-axes.md
+  price_scale_id (per-series) -> multiple-axes.md
+  scale_mode (per-series) -> multiple-axes.md
+  watermark_text -> watermark.md
+-->
+
+# Price Scale
+
+The price scale is the vertical axis. Most charts have one, the right scale by default, but TVL also supports a left scale, any number of overlay scales, and per-series scale binding. Each scale has its own mode (`"normal"`, `"logarithmic"`, `"percentage"`, `"indexed_to_100"`), auto-scale toggle, margins, and tick density.
+
+Use this page when you want to plot two series with different units, render returns instead of prices, leave room at the top of the chart for annotations, or just hide a scale.
+
+## What are the price-scale options useful for?
+
+- **Multi-unit overlays**: Plot price on the right scale and volume on the left; each scale auto-fits its own series.
+- **Return analysis**: Switch the scale mode to `"percentage"` or `"indexed_to_100"` to compare instruments with different absolute prices.
+- **Log-scale charts**: Use `"logarithmic"` mode for assets that move in percentage terms across multiple decades.
+- **Annotation room**: Increase `margin_top` to leave whitespace above the data for markers and price-line labels.
+
+## Examples
+
+### Pick a scale mode: all four `PriceScaleMode` values
+
+`PriceScaleMode` accepts `"normal"`, `"logarithmic"`, `"percentage"`, and `"indexed_to_100"`. `"normal"` is linear; `"logarithmic"` plots log of the value; `"percentage"` renders each point as a percent change from the first visible value; `"indexed_to_100"` renormalizes so the first visible point is exactly 100.
+
+```python order=normal,logarithmic,percentage,indexed_to_100,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+normal = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_mode="normal",
+)
+
+logarithmic = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_mode="logarithmic",
+)
+
+percentage = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_mode="percentage",
+)
+
+indexed_to_100 = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_mode="indexed_to_100",
+)
+```
+
+`"percentage"` and `"indexed_to_100"` are relative to the visible window: pan the chart and the reference point updates.
+
+### Set margins to leave headroom
+
+`right_price_scale_margin_top` and `right_price_scale_margin_bottom` are fractions in `[0, 1]` reserving whitespace at the top and bottom of the plot area. The defaults are around 0.2 / 0.1; bump `margin_top` higher to leave room for marker labels.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_margin_top=0.3,
+    right_price_scale_margin_bottom=0.1,
+)
+```
+
+The same `margin_top` / `margin_bottom` exist on `left_price_scale_*` and `overlay_price_scale_*`.
+
+### Turn off auto-scale to lock the visible range
+
+By default the scale auto-fits to the visible data. Set `right_price_scale_auto_scale=False` to freeze it; the user can still pan, but the axis numbers don't shift on zoom.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_auto_scale=False,
+)
+```
+
+This is useful for dashboards where a stable axis matters more than maximizing visible variation.
+
+### Default the visible scale to the left
+
+`default_visible_price_scale_id` accepts `"left"` or `"right"`. It sets the scale every new series binds to *unless* the series explicitly sets `price_scale_id`. The default is `"right"`; set it to `"left"` to flip the convention.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    default_visible_price_scale_id="left",
+    left_price_scale_visible=True,
+    right_price_scale_visible=False,
+)
+```
+
+For multi-axis layouts where some series have explicit `price_scale_id` and others don't, this kwarg sets the default fallback. See [multiple-axes](multiple-axes.md) for full multi-axis patterns.
+
+### Style the left price scale independently
+
+Every `right_price_scale_*` parameter has a `left_price_scale_*` twin. Style each axis independently, with its own text colors, borders, and tick visibility.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", price_scale_id="left"),
+    left_price_scale_visible=True,
+    left_price_scale_border_visible=True,
+    left_price_scale_border_color="#888",
+    left_price_scale_text_color="#444",
+    left_price_scale_ticks_visible=True,
+    left_price_scale_minimum_width=60,
+    left_price_scale_align_labels=True,
+    left_price_scale_invert_scale=False,
+    left_price_scale_entire_text_only=True,
+    left_price_scale_ensure_edge_tick_marks_visible=True,
+    right_price_scale_visible=False,
+)
+```
+
+`entire_text_only=True` is handy when tick labels would otherwise be clipped at the chart edge.
+
+### Tune tick-mark density
+
+`right_price_scale_tick_mark_density` controls how many ticks the scale tries to render; higher values mean more ticks. The default is around 2.5. The same parameter exists for `left_price_scale_*` and `overlay_price_scale_*`.
+
+```python order=sparse,dense,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+sparse = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_tick_mark_density=1.5,
+)
+
+dense = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_tick_mark_density=4.0,
+)
+```
+
+Use sparse density on narrow dashboard tiles, dense on full-screen analytical charts.
+
+### Apply overlay-scale defaults
+
+When a series binds to a numeric overlay scale (e.g. `price_scale_id="vol"`), TVL falls back to the `overlay_price_scale_*` defaults. These set styling that applies to every overlay scale unless the series overrides it.
+
+```python order=chart,volume
+import deephaven.plot.tradingview_lightweight as tvl
+
+volume = tvl.data.volume()
+
+chart = tvl.chart(
+    tvl.histogram(volume, timestamp="Timestamp", value="Volume", price_scale_id="vol", scale_margin_top=0.7),
+    overlay_price_scale_border_visible=True,
+    overlay_price_scale_border_color="#aaa",
+    overlay_price_scale_text_color="#666",
+    overlay_price_scale_ticks_visible=True,
+    overlay_price_scale_minimum_width=40,
+    overlay_price_scale_margin_top=0.7,
+    overlay_price_scale_margin_bottom=0.0,
+    overlay_price_scale_auto_scale=True,
+    overlay_price_scale_mode="normal",
+    overlay_price_scale_invert_scale=False,
+    overlay_price_scale_align_labels=True,
+    overlay_price_scale_entire_text_only=True,
+    overlay_price_scale_ensure_edge_tick_marks_visible=True,
+    overlay_price_scale_tick_mark_density=2.0,
+)
+```
+
+This is the standard "price + volume" pattern, where the histogram lives on a stub overlay scale at the bottom.
+
+### Invert the price scale
+
+`right_price_scale_invert_scale=True` flips the axis top-to-bottom. Useful when plotting interest rate spreads where convention is "low rate at top, high rate at bottom" (or for some yield analytics).
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_price_scale_invert_scale=True,
+)
+```
+
+### Per-series scale options vs. chart-level
+
+Each per-type constructor also accepts `scale_margin_top`, `scale_margin_bottom`, `scale_mode`, `scale_invert`, etc. Series-level options take precedence over chart-level for the scale that series binds to, which helps when you want one overlay scale styled differently from another.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.line(
+    values,
+    timestamp="Timestamp",
+    value="Value",
+    scale_mode="logarithmic",
+    scale_margin_top=0.25,
+    scale_margin_bottom=0.15,
+    auto_scale=True,
+    scale_invert=False,
+    scale_align_labels=True,
+    scale_border_visible=True,
+    scale_border_color="#888",
+    scale_text_color="#444",
+    scale_entire_text_only=True,
+    scale_visible=True,
+    scale_ticks_visible=True,
+    scale_minimum_width=60,
+    scale_ensure_edge_tick_marks_visible=True,
+)
+```
+
+If you set `scale_mode` per-series and `right_price_scale_mode` at the chart, the per-series mode wins. The remaining `scale_*` options mirror their `right_price_scale_*` twins but bind to whichever scale the series uses.
+
+### Style the baseline reference line
+
+In `"percentage"` and `"indexed_to_100"` modes the scale draws a horizontal reference line at the base value. `base_line_visible`, `base_line_color`, `base_line_width`, and `base_line_style` style that line (these are per-series options).
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(
+        values,
+        timestamp="Timestamp",
+        value="Value",
+        base_line_visible=True,
+        base_line_color="#888",
+        base_line_width=2,
+        base_line_style="dashed",
+    ),
+    right_price_scale_mode="indexed_to_100",
+)
+```
+
+## API Reference
+
+For the full `tvl.chart` signature, see the [Chart container](chart.md#api-reference) page.
diff --git a/plugins/tradingview-lightweight/docs/sidebar.json b/plugins/tradingview-lightweight/docs/sidebar.json
new file mode 100644
index 000000000..5ba02b009
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/sidebar.json
@@ -0,0 +1,159 @@
+{
+  "$schema": "https://raw.githubusercontent.com/deephaven/salmon-sync/refs/heads/main/sidebar.schema.json",
+  "config": {
+    "name": "Deephaven TradingView Lightweight Docs"
+  },
+  "sidebars": {
+    "main": [
+      {
+        "label": "Introduction",
+        "path": "README.md"
+      },
+      {
+        "label": "Chart Types",
+        "collapsible": false,
+        "items": [
+          {
+            "label": "Area",
+            "path": "area.md"
+          },
+          {
+            "label": "Bar",
+            "path": "bar.md"
+          },
+          {
+            "label": "Baseline",
+            "path": "baseline.md"
+          },
+          {
+            "label": "Candlestick",
+            "path": "candlestick.md"
+          },
+          {
+            "label": "Custom Numeric",
+            "path": "custom-numeric.md"
+          },
+          {
+            "label": "Histogram",
+            "path": "histogram.md"
+          },
+          {
+            "label": "Line",
+            "path": "line.md"
+          },
+          {
+            "label": "Options Chart",
+            "path": "options-chart.md"
+          },
+          {
+            "label": "Yield Curve",
+            "path": "yield-curve.md"
+          }
+        ]
+      },
+      {
+        "label": "Configuration",
+        "collapsible": false,
+        "items": [
+          {
+            "label": "Chart container",
+            "path": "chart.md"
+          },
+          {
+            "label": "Compose",
+            "items": [
+              {
+                "label": "Multiple series",
+                "path": "multi-series.md"
+              },
+              {
+                "label": "Multiple panes",
+                "path": "multi-pane.md"
+              },
+              {
+                "label": "Multiple axes",
+                "path": "multiple-axes.md"
+              }
+            ]
+          },
+          {
+            "label": "Annotate",
+            "items": [
+              {
+                "label": "Titles and legends",
+                "path": "titles-legends.md"
+              },
+              {
+                "label": "Markers",
+                "path": "markers.md"
+              },
+              {
+                "label": "Price lines",
+                "path": "price-lines.md"
+              },
+              {
+                "label": "Watermark",
+                "path": "watermark.md"
+              }
+            ]
+          },
+          {
+            "label": "Style",
+            "items": [
+              {
+                "label": "Styling",
+                "path": "styling.md"
+              },
+              {
+                "label": "Time scale",
+                "path": "time-scale.md"
+              },
+              {
+                "label": "Price scale",
+                "path": "price-scale.md"
+              },
+              {
+                "label": "Price formats",
+                "path": "price-formats.md"
+              }
+            ]
+          },
+          {
+            "label": "Interact",
+            "items": [
+              {
+                "label": "Press events",
+                "path": "events.md"
+              },
+              {
+                "label": "Tracking tooltip",
+                "path": "tooltip.md"
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "label": "Concepts",
+        "items": [
+          {
+            "label": "Downsampling",
+            "path": "downsampling.md"
+          },
+          {
+            "label": "Autobin",
+            "path": "autobin.md"
+          },
+          {
+            "label": "Large Data",
+            "path": "large-data.md"
+          }
+        ]
+      },
+      {
+        "label": "Example Data",
+        "path": "example-data.md"
+      }
+    ]
+  }
+}
diff --git a/plugins/tradingview-lightweight/docs/snapshots/01ee418a2f1013bf1cc59e628234664a.json b/plugins/tradingview-lightweight/docs/snapshots/01ee418a2f1013bf1cc59e628234664a.json
new file mode 100644
index 000000000..476f30230
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/01ee418a2f1013bf1cc59e628234664a.json
@@ -0,0 +1,1466 @@
+{
+  "file": "histogram.md",
+  "objects": {
+    "data": {
+      "type": "Table",
+      "data": {
+        "columns": [
+          {
+            "name": "Timestamp",
+            "type": "java.time.Instant"
+          },
+          {
+            "name": "Sym",
+            "type": "java.lang.String"
+          },
+          {
+            "name": "Price",
+            "type": "double"
+          },
+          {
+            "name": "Size",
+            "type": "long"
+          }
+        ],
+        "rows": [
+          [
+            {
+              "value": "2024-01-01 09:30:00.000"
+            },
+            {
+              "value": "AAA"
+            },
+            {
+              "value": "89.4969"
+            },
+            {
+              "value": "61"
+            }
+          ],
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new file mode 100644
index 000000000..9e298e68d
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/03b8b53774ec48347cb070f40292ca32.json b/plugins/tradingview-lightweight/docs/snapshots/03b8b53774ec48347cb070f40292ca32.json
new file mode 100644
index 000000000..a581a338c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/03b8b53774ec48347cb070f40292ca32.json
@@ -0,0 +1,400 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/0481161cd5f8e7e1992dcbb836e1de24.json b/plugins/tradingview-lightweight/docs/snapshots/0481161cd5f8e7e1992dcbb836e1de24.json
new file mode 100644
index 000000000..cd69b2c9a
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/0481161cd5f8e7e1992dcbb836e1de24.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/0483b48336bb2f9e919c3a1fc04969e3.json b/plugins/tradingview-lightweight/docs/snapshots/0483b48336bb2f9e919c3a1fc04969e3.json
new file mode 100644
index 000000000..0bd51bd12
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/0529860bb5e5c4305b8d60c6b83586ad.json b/plugins/tradingview-lightweight/docs/snapshots/0529860bb5e5c4305b8d60c6b83586ad.json
new file mode 100644
index 000000000..85fe17af5
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/0529860bb5e5c4305b8d60c6b83586ad.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/0c721d0f8a2cf27939e77e2d97b33da6.json b/plugins/tradingview-lightweight/docs/snapshots/0c721d0f8a2cf27939e77e2d97b33da6.json
new file mode 100644
index 000000000..049ce106e
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+++ b/plugins/tradingview-lightweight/docs/snapshots/0c721d0f8a2cf27939e77e2d97b33da6.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/17e8464cc200cc4bb987b8da722b0e6c.json b/plugins/tradingview-lightweight/docs/snapshots/17e8464cc200cc4bb987b8da722b0e6c.json
new file mode 100644
index 000000000..4fbb3cc60
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/17e8464cc200cc4bb987b8da722b0e6c.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/17ee63f4304ba386236ac2513ec0bbed.json b/plugins/tradingview-lightweight/docs/snapshots/17ee63f4304ba386236ac2513ec0bbed.json
new file mode 100644
index 000000000..6157111f8
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/17ee63f4304ba386236ac2513ec0bbed.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/17f5e080ac02f3de914c15ef01ee3b2c.json b/plugins/tradingview-lightweight/docs/snapshots/17f5e080ac02f3de914c15ef01ee3b2c.json
new file mode 100644
index 000000000..7cd26722d
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/17f5e080ac02f3de914c15ef01ee3b2c.json
@@ -0,0 +1,2121 @@
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+++ b/plugins/tradingview-lightweight/docs/snapshots/1a7a0fd86d2f97ecc3c4867f5bd8556b.json
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new file mode 100644
index 000000000..010792f01
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/1a889cc7580e2ac4b042595d08866741.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/22d0e7a550a28fa2bd69a2bdb13dc06d.json b/plugins/tradingview-lightweight/docs/snapshots/22d0e7a550a28fa2bd69a2bdb13dc06d.json
new file mode 100644
index 000000000..516a2ef74
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/22d0e7a550a28fa2bd69a2bdb13dc06d.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/2411df22a26796a9633822f1e12f39fa.json b/plugins/tradingview-lightweight/docs/snapshots/2411df22a26796a9633822f1e12f39fa.json
new file mode 100644
index 000000000..990b65653
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/2411df22a26796a9633822f1e12f39fa.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/274d0dc6c2e5669ba21e75f922091ef6.json b/plugins/tradingview-lightweight/docs/snapshots/274d0dc6c2e5669ba21e75f922091ef6.json
new file mode 100644
index 000000000..32ce1b157
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/274d0dc6c2e5669ba21e75f922091ef6.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/2859122d1f9164e855b7da358b5d627b.json b/plugins/tradingview-lightweight/docs/snapshots/2859122d1f9164e855b7da358b5d627b.json
new file mode 100644
index 000000000..cfb84f235
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/2859122d1f9164e855b7da358b5d627b.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/2cdf15a0d030ac85bce6167572af32d2.json b/plugins/tradingview-lightweight/docs/snapshots/2cdf15a0d030ac85bce6167572af32d2.json
new file mode 100644
index 000000000..18cc638ce
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/2cdf15a0d030ac85bce6167572af32d2.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/2d9f0552781f35043144361fdd4c41d1.json b/plugins/tradingview-lightweight/docs/snapshots/2d9f0552781f35043144361fdd4c41d1.json
new file mode 100644
index 000000000..5af6fdcd8
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/2d9f0552781f35043144361fdd4c41d1.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/2ea864e1606973dc8d3a8505b380a4d4.json b/plugins/tradingview-lightweight/docs/snapshots/2ea864e1606973dc8d3a8505b380a4d4.json
new file mode 100644
index 000000000..e827e123f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/2ea864e1606973dc8d3a8505b380a4d4.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/2f6e630310d0f7bd76bf74e0615ba324.json b/plugins/tradingview-lightweight/docs/snapshots/2f6e630310d0f7bd76bf74e0615ba324.json
new file mode 100644
index 000000000..8f53aca42
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/2f6e630310d0f7bd76bf74e0615ba324.json
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new file mode 100644
index 000000000..2fef13b2e
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/316085e0dc5a0d256be6b922edc43ca6.json b/plugins/tradingview-lightweight/docs/snapshots/316085e0dc5a0d256be6b922edc43ca6.json
new file mode 100644
index 000000000..b8b0144b5
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/316085e0dc5a0d256be6b922edc43ca6.json
@@ -0,0 +1,751 @@
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new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/333eb889332869648acfc8ce31d959e4.json b/plugins/tradingview-lightweight/docs/snapshots/333eb889332869648acfc8ce31d959e4.json
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+}
diff --git a/plugins/tradingview-lightweight/docs/snapshots/344372eb7dad3c32098f4c7999a4f871.json b/plugins/tradingview-lightweight/docs/snapshots/344372eb7dad3c32098f4c7999a4f871.json
new file mode 100644
index 000000000..0a83927e3
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/344372eb7dad3c32098f4c7999a4f871.json
@@ -0,0 +1,1008 @@
+{
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/34ce7dad3536c494b6f611950e1fae22.json b/plugins/tradingview-lightweight/docs/snapshots/34ce7dad3536c494b6f611950e1fae22.json
new file mode 100644
index 000000000..d796d7e61
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/34ce7dad3536c494b6f611950e1fae22.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/354b942ec11eccc20bfdb0e05204da7d.json b/plugins/tradingview-lightweight/docs/snapshots/354b942ec11eccc20bfdb0e05204da7d.json
new file mode 100644
index 000000000..bcb42c461
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/354b942ec11eccc20bfdb0e05204da7d.json
@@ -0,0 +1,2500 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/38b82bfe1d903720014151e7bd829801.json b/plugins/tradingview-lightweight/docs/snapshots/38b82bfe1d903720014151e7bd829801.json
new file mode 100644
index 000000000..227152f9f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/38b82bfe1d903720014151e7bd829801.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/3a35965bea5dd531f4cdbdc68a531a45.json b/plugins/tradingview-lightweight/docs/snapshots/3a35965bea5dd531f4cdbdc68a531a45.json
new file mode 100644
index 000000000..4b4fd027d
--- /dev/null
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/3b259d12a34ee385ac27cd734cc4767b.json b/plugins/tradingview-lightweight/docs/snapshots/3b259d12a34ee385ac27cd734cc4767b.json
new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/3b2ae01b444ca6cfdad15dca63e923c4.json b/plugins/tradingview-lightweight/docs/snapshots/3b2ae01b444ca6cfdad15dca63e923c4.json
new file mode 100644
index 000000000..9ead3b1ae
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/3b2ae01b444ca6cfdad15dca63e923c4.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/3c05d74d0dc80f81a86de227ef5fb75a.json b/plugins/tradingview-lightweight/docs/snapshots/3c05d74d0dc80f81a86de227ef5fb75a.json
new file mode 100644
index 000000000..763f3993a
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/3c05d74d0dc80f81a86de227ef5fb75a.json
@@ -0,0 +1,4289 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/3d23fc921a3aaa0ab9039124fa22282e.json b/plugins/tradingview-lightweight/docs/snapshots/3d23fc921a3aaa0ab9039124fa22282e.json
new file mode 100644
index 000000000..7bdccd24c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/3d23fc921a3aaa0ab9039124fa22282e.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/3f584daf84872ac8fe931262afa14049.json b/plugins/tradingview-lightweight/docs/snapshots/3f584daf84872ac8fe931262afa14049.json
new file mode 100644
index 000000000..1f26f23ce
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/3f584daf84872ac8fe931262afa14049.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/40a24b2c4a3c8a20856fef52d2602b7b.json b/plugins/tradingview-lightweight/docs/snapshots/40a24b2c4a3c8a20856fef52d2602b7b.json
new file mode 100644
index 000000000..3e2dad5f6
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/40a24b2c4a3c8a20856fef52d2602b7b.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/416cd58f26c1ca0cbb86fc4de77283dc.json b/plugins/tradingview-lightweight/docs/snapshots/416cd58f26c1ca0cbb86fc4de77283dc.json
new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/4568cd0684f7b1585c34fa4b1c3e986b.json b/plugins/tradingview-lightweight/docs/snapshots/4568cd0684f7b1585c34fa4b1c3e986b.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/463eb504a3ea64bc1965fb69601e9234.json b/plugins/tradingview-lightweight/docs/snapshots/463eb504a3ea64bc1965fb69601e9234.json
new file mode 100644
index 000000000..48e845bfa
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/463eb504a3ea64bc1965fb69601e9234.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/46eba615dfefac9fc24374cb8fee9f07.json b/plugins/tradingview-lightweight/docs/snapshots/46eba615dfefac9fc24374cb8fee9f07.json
new file mode 100644
index 000000000..610f0055b
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/46eba615dfefac9fc24374cb8fee9f07.json
@@ -0,0 +1,778 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/4701152810f682ba8242f2e7aba1ad99.json b/plugins/tradingview-lightweight/docs/snapshots/4701152810f682ba8242f2e7aba1ad99.json
new file mode 100644
index 000000000..2686e7e28
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/485eb4cd367fb71cd94b61cc6c49384c.json b/plugins/tradingview-lightweight/docs/snapshots/485eb4cd367fb71cd94b61cc6c49384c.json
new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/49af5a98e500a7ff853d559c49b69a74.json b/plugins/tradingview-lightweight/docs/snapshots/49af5a98e500a7ff853d559c49b69a74.json
new file mode 100644
index 000000000..41ec3cd42
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/49af5a98e500a7ff853d559c49b69a74.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/4abdba311662304b5a690719bfa25c04.json b/plugins/tradingview-lightweight/docs/snapshots/4abdba311662304b5a690719bfa25c04.json
new file mode 100644
index 000000000..497bba9b4
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/4abdba311662304b5a690719bfa25c04.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/4b5fec57dfc3dcde3b6e2f753bd4fc80.json b/plugins/tradingview-lightweight/docs/snapshots/4b5fec57dfc3dcde3b6e2f753bd4fc80.json
new file mode 100644
index 000000000..ff2ad9dbe
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/4b5fec57dfc3dcde3b6e2f753bd4fc80.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/4c77e081f2484b70ba5d3c8fe568c91c.json b/plugins/tradingview-lightweight/docs/snapshots/4c77e081f2484b70ba5d3c8fe568c91c.json
new file mode 100644
index 000000000..4da773b50
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/4c77e081f2484b70ba5d3c8fe568c91c.json
@@ -0,0 +1,2121 @@
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index 000000000..2c5e1d1b0
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/4d4ca57f87c842c16be9f75bbfe32589.json b/plugins/tradingview-lightweight/docs/snapshots/4d4ca57f87c842c16be9f75bbfe32589.json
new file mode 100644
index 000000000..ca5051be7
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/4d4ca57f87c842c16be9f75bbfe32589.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/51821ae9cbe56709bb2acd27ad8c78c8.json b/plugins/tradingview-lightweight/docs/snapshots/51821ae9cbe56709bb2acd27ad8c78c8.json
new file mode 100644
index 000000000..6e6d33c6f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/51821ae9cbe56709bb2acd27ad8c78c8.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/520a34b5e24362809a80709e2348ad8c.json b/plugins/tradingview-lightweight/docs/snapshots/520a34b5e24362809a80709e2348ad8c.json
new file mode 100644
index 000000000..8d6a067cc
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/520a34b5e24362809a80709e2348ad8c.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/52b2e046d05038c94dd64d76cd966a5f.json b/plugins/tradingview-lightweight/docs/snapshots/52b2e046d05038c94dd64d76cd966a5f.json
new file mode 100644
index 000000000..94a7e3fc8
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/52b2e046d05038c94dd64d76cd966a5f.json
@@ -0,0 +1,1025 @@
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+}
diff --git a/plugins/tradingview-lightweight/docs/snapshots/566eae059ea1edb43d223c37aa5d1e50.json b/plugins/tradingview-lightweight/docs/snapshots/566eae059ea1edb43d223c37aa5d1e50.json
new file mode 100644
index 000000000..9d625a1ee
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/566eae059ea1edb43d223c37aa5d1e50.json
@@ -0,0 +1 @@
+{"file":"time-scale.md","objects":{":log":{"type":"Log","data":"{'year': 2024, 'month': 1, 'day': 2}\n"}}}
\ No newline at end of file
diff --git a/plugins/tradingview-lightweight/docs/snapshots/56a0cde213a50143580ef2947e71e7bf.json b/plugins/tradingview-lightweight/docs/snapshots/56a0cde213a50143580ef2947e71e7bf.json
new file mode 100644
index 000000000..c0fd67454
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/56a0cde213a50143580ef2947e71e7bf.json
@@ -0,0 +1,2395 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/57489a55449e612fe9a74dd0258273ed.json b/plugins/tradingview-lightweight/docs/snapshots/57489a55449e612fe9a74dd0258273ed.json
new file mode 100644
index 000000000..d3dee06c0
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/57489a55449e612fe9a74dd0258273ed.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/575411cda81f1afb81880536a5ee4b30.json b/plugins/tradingview-lightweight/docs/snapshots/575411cda81f1afb81880536a5ee4b30.json
new file mode 100644
index 000000000..c31d4dd70
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/575411cda81f1afb81880536a5ee4b30.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/61bbbb996b666e366b2b17c7dbe1a15c.json b/plugins/tradingview-lightweight/docs/snapshots/61bbbb996b666e366b2b17c7dbe1a15c.json
new file mode 100644
index 000000000..11f8b4329
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/61bbbb996b666e366b2b17c7dbe1a15c.json
@@ -0,0 +1,2121 @@
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new file mode 100644
index 000000000..56d73f17e
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/634b487bcd673d058124bd40d0b7751a.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/652b46c469d4e4f88e8cc78c82156c7d.json b/plugins/tradingview-lightweight/docs/snapshots/652b46c469d4e4f88e8cc78c82156c7d.json
new file mode 100644
index 000000000..8c0c002da
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/652b46c469d4e4f88e8cc78c82156c7d.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/65bd85aa1db7e1dfa75e5da528ed81f8.json b/plugins/tradingview-lightweight/docs/snapshots/65bd85aa1db7e1dfa75e5da528ed81f8.json
new file mode 100644
index 000000000..639d9f945
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/65bd85aa1db7e1dfa75e5da528ed81f8.json
@@ -0,0 +1,760 @@
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+}
diff --git a/plugins/tradingview-lightweight/docs/snapshots/687a600fcde280e4769a8371846ac855.json b/plugins/tradingview-lightweight/docs/snapshots/687a600fcde280e4769a8371846ac855.json
new file mode 100644
index 000000000..d0d2154fe
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/687a600fcde280e4769a8371846ac855.json
@@ -0,0 +1 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/6a1d29764bb0761e1e9a7d5f284f3f2d.json b/plugins/tradingview-lightweight/docs/snapshots/6a1d29764bb0761e1e9a7d5f284f3f2d.json
new file mode 100644
index 000000000..9d5ee9c0f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/6a1d29764bb0761e1e9a7d5f284f3f2d.json
@@ -0,0 +1,511 @@
+{
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new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/6e7846204b01376062bf766fc4d05665.json b/plugins/tradingview-lightweight/docs/snapshots/6e7846204b01376062bf766fc4d05665.json
new file mode 100644
index 000000000..c103c793b
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/6e7846204b01376062bf766fc4d05665.json
@@ -0,0 +1 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/6f525e751b0265c6b14e362ceb979977.json b/plugins/tradingview-lightweight/docs/snapshots/6f525e751b0265c6b14e362ceb979977.json
new file mode 100644
index 000000000..d89923d74
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/6f525e751b0265c6b14e362ceb979977.json
@@ -0,0 +1,769 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/7205cc6fc187cc2ffad5b1acb8fad884.json b/plugins/tradingview-lightweight/docs/snapshots/7205cc6fc187cc2ffad5b1acb8fad884.json
new file mode 100644
index 000000000..9aac3d6f9
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/7205cc6fc187cc2ffad5b1acb8fad884.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/76ee7ba36549f5af1e1604efe016087e.json b/plugins/tradingview-lightweight/docs/snapshots/76ee7ba36549f5af1e1604efe016087e.json
new file mode 100644
index 000000000..8b7a51920
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/76ee7ba36549f5af1e1604efe016087e.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/7890f4ddbe913a0fd83c1a351fab4e50.json b/plugins/tradingview-lightweight/docs/snapshots/7890f4ddbe913a0fd83c1a351fab4e50.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/7ef819a33ad6f3622609c6df46337deb.json b/plugins/tradingview-lightweight/docs/snapshots/7ef819a33ad6f3622609c6df46337deb.json
new file mode 100644
index 000000000..79afb2b4d
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/7ef819a33ad6f3622609c6df46337deb.json
@@ -0,0 +1 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/7f111b312f60c993356f7fac528168d6.json b/plugins/tradingview-lightweight/docs/snapshots/7f111b312f60c993356f7fac528168d6.json
new file mode 100644
index 000000000..56d73f17e
--- /dev/null
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new file mode 100644
index 000000000..ed9d9b2ce
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/80aeb632a902daeb2ef31e90eff6ad14.json b/plugins/tradingview-lightweight/docs/snapshots/80aeb632a902daeb2ef31e90eff6ad14.json
new file mode 100644
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+++ b/plugins/tradingview-lightweight/docs/snapshots/80aeb632a902daeb2ef31e90eff6ad14.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/82683b5f0e5cfcf70d779ab0e040e4df.json b/plugins/tradingview-lightweight/docs/snapshots/82683b5f0e5cfcf70d779ab0e040e4df.json
new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/82c67ee703b9d3ef22b63b37aefe4da6.json b/plugins/tradingview-lightweight/docs/snapshots/82c67ee703b9d3ef22b63b37aefe4da6.json
new file mode 100644
index 000000000..3834af542
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/82c67ee703b9d3ef22b63b37aefe4da6.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/82fc6a494deb4e1f1f54f29381206658.json b/plugins/tradingview-lightweight/docs/snapshots/82fc6a494deb4e1f1f54f29381206658.json
new file mode 100644
index 000000000..8616abddb
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/82fc6a494deb4e1f1f54f29381206658.json
@@ -0,0 +1,831 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/83e9b6887c4b24204640bb89fe453724.json b/plugins/tradingview-lightweight/docs/snapshots/83e9b6887c4b24204640bb89fe453724.json
new file mode 100644
index 000000000..ef1f43aea
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/83e9b6887c4b24204640bb89fe453724.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/86521aed5541959b1baec3e56c6fbf1a.json b/plugins/tradingview-lightweight/docs/snapshots/86521aed5541959b1baec3e56c6fbf1a.json
new file mode 100644
index 000000000..dc50cfef2
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/86521aed5541959b1baec3e56c6fbf1a.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/86bc8e8933adf9dd24424051982f516b.json b/plugins/tradingview-lightweight/docs/snapshots/86bc8e8933adf9dd24424051982f516b.json
new file mode 100644
index 000000000..3e8d9119b
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/86bc8e8933adf9dd24424051982f516b.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/86e45c0c1b6813bb49dd7ecbc2c37b54.json b/plugins/tradingview-lightweight/docs/snapshots/86e45c0c1b6813bb49dd7ecbc2c37b54.json
new file mode 100644
index 000000000..dfc314091
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/86e45c0c1b6813bb49dd7ecbc2c37b54.json
@@ -0,0 +1,1488 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/8addd9e2d59d9c4f66cd8813434b7dc7.json b/plugins/tradingview-lightweight/docs/snapshots/8addd9e2d59d9c4f66cd8813434b7dc7.json
new file mode 100644
index 000000000..797ab5a10
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/8addd9e2d59d9c4f66cd8813434b7dc7.json
@@ -0,0 +1,511 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/8af17ef37a991b3b65aac5fcd6624cb1.json b/plugins/tradingview-lightweight/docs/snapshots/8af17ef37a991b3b65aac5fcd6624cb1.json
new file mode 100644
index 000000000..f743c791a
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/8af17ef37a991b3b65aac5fcd6624cb1.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/8c0cbf48eaf1f4d20b0d511da12c42b2.json b/plugins/tradingview-lightweight/docs/snapshots/8c0cbf48eaf1f4d20b0d511da12c42b2.json
new file mode 100644
index 000000000..91b44b9ee
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/8c0cbf48eaf1f4d20b0d511da12c42b2.json
@@ -0,0 +1,1488 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/8c6b31b81fda0de2b9e1968fd2f0d1d3.json b/plugins/tradingview-lightweight/docs/snapshots/8c6b31b81fda0de2b9e1968fd2f0d1d3.json
new file mode 100644
index 000000000..f381157d6
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/8c6b31b81fda0de2b9e1968fd2f0d1d3.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/8cdd3eff7fa34a25fd83eb12810a866c.json b/plugins/tradingview-lightweight/docs/snapshots/8cdd3eff7fa34a25fd83eb12810a866c.json
new file mode 100644
index 000000000..9b642a6cd
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/8cdd3eff7fa34a25fd83eb12810a866c.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/8e08b37434d668d397f53047f2a0ba8c.json b/plugins/tradingview-lightweight/docs/snapshots/8e08b37434d668d397f53047f2a0ba8c.json
new file mode 100644
index 000000000..5e08f8da0
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/8e08b37434d668d397f53047f2a0ba8c.json
@@ -0,0 +1,831 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/90483e603623945b2574cb0074a21078.json b/plugins/tradingview-lightweight/docs/snapshots/90483e603623945b2574cb0074a21078.json
new file mode 100644
index 000000000..15810b177
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/90483e603623945b2574cb0074a21078.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/91c5d853a8644c301bbfc43addc7e37b.json b/plugins/tradingview-lightweight/docs/snapshots/91c5d853a8644c301bbfc43addc7e37b.json
new file mode 100644
index 000000000..c8e660cc3
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/91c5d853a8644c301bbfc43addc7e37b.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/92a74ab19630d845b839adc33480e2d8.json b/plugins/tradingview-lightweight/docs/snapshots/92a74ab19630d845b839adc33480e2d8.json
new file mode 100644
index 000000000..f34e48714
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/92a74ab19630d845b839adc33480e2d8.json
@@ -0,0 +1,760 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/92d80a22c367388f4d8defa5b7df62d7.json b/plugins/tradingview-lightweight/docs/snapshots/92d80a22c367388f4d8defa5b7df62d7.json
new file mode 100644
index 000000000..e3169220c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/92d80a22c367388f4d8defa5b7df62d7.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/97426abfdbe3e59f41afd07b4ef06640.json b/plugins/tradingview-lightweight/docs/snapshots/97426abfdbe3e59f41afd07b4ef06640.json
new file mode 100644
index 000000000..43ecb6282
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/97426abfdbe3e59f41afd07b4ef06640.json
@@ -0,0 +1,1192 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/9c25cf3a65465ad970d6ff0b61baf885.json b/plugins/tradingview-lightweight/docs/snapshots/9c25cf3a65465ad970d6ff0b61baf885.json
new file mode 100644
index 000000000..caf2b87fc
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/9c25cf3a65465ad970d6ff0b61baf885.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/9d061adb57d05e4a9acd812b598ef2f2.json b/plugins/tradingview-lightweight/docs/snapshots/9d061adb57d05e4a9acd812b598ef2f2.json
new file mode 100644
index 000000000..5a2cc4480
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/9d061adb57d05e4a9acd812b598ef2f2.json
@@ -0,0 +1,831 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/a1e900abb9ca02f741cc1c15c86b2c06.json b/plugins/tradingview-lightweight/docs/snapshots/a1e900abb9ca02f741cc1c15c86b2c06.json
new file mode 100644
index 000000000..285336b9a
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/a500f3799bd2183bd5a6850a316689c9.json b/plugins/tradingview-lightweight/docs/snapshots/a500f3799bd2183bd5a6850a316689c9.json
new file mode 100644
index 000000000..0fcdfb67d
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/a500f3799bd2183bd5a6850a316689c9.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/a6782ce397b7f2cd1cc2d0b20049e91a.json b/plugins/tradingview-lightweight/docs/snapshots/a6782ce397b7f2cd1cc2d0b20049e91a.json
new file mode 100644
index 000000000..17852ea52
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/a6782ce397b7f2cd1cc2d0b20049e91a.json
@@ -0,0 +1,511 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/a8508196e734e262c38021d429c86963.json b/plugins/tradingview-lightweight/docs/snapshots/a8508196e734e262c38021d429c86963.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/ab23b6be7719bfc2a753e11985f6c118.json b/plugins/tradingview-lightweight/docs/snapshots/ab23b6be7719bfc2a753e11985f6c118.json
new file mode 100644
index 000000000..e81c259df
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/ab23b6be7719bfc2a753e11985f6c118.json
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--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/ac2f021d4070753edf178d68b8fa0806.json
@@ -0,0 +1,119 @@
+{
+  "file": "yield-curve.md",
+  "objects": {
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+      "data": {
+        "columns": [
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+            "name": "Tenor",
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+          [
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+            }
+          ],
+          [
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+              "value": "480.0000"
+            },
+            {
+              "value": "4.0430"
+            }
+          ]
+        ]
+      }
+    },
+    "yield_curve": {
+      "type": "deephaven.plot.tradingview_lightweight.TvlChart",
+      "data": {
+        "image": "assets/4799e21fe73db2d471161d78cf0bc39da20605526b9efa894407991f533dbc0c.png",
+        "width": 860,
+        "height": 573,
+        "alt": "yield_curve"
+      }
+    }
+  }
+}
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b1a102dca59b5c6103138faff0cf04f4.json b/plugins/tradingview-lightweight/docs/snapshots/b1a102dca59b5c6103138faff0cf04f4.json
new file mode 100644
index 000000000..dcb4adb60
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b1a102dca59b5c6103138faff0cf04f4.json
@@ -0,0 +1,400 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b1e542b80521e03fc13567b29921638d.json b/plugins/tradingview-lightweight/docs/snapshots/b1e542b80521e03fc13567b29921638d.json
new file mode 100644
index 000000000..2ac1f94df
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b1e542b80521e03fc13567b29921638d.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b4930f65793729ef98519982fcc0b376.json b/plugins/tradingview-lightweight/docs/snapshots/b4930f65793729ef98519982fcc0b376.json
new file mode 100644
index 000000000..823e2734c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b4930f65793729ef98519982fcc0b376.json
@@ -0,0 +1,1573 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b54a18eb9d87a64b8e56cf7a68ecd058.json b/plugins/tradingview-lightweight/docs/snapshots/b54a18eb9d87a64b8e56cf7a68ecd058.json
new file mode 100644
index 000000000..6965c4408
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b54a18eb9d87a64b8e56cf7a68ecd058.json
@@ -0,0 +1,511 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b5557684b5a3bcd459da032dbf11bfc9.json b/plugins/tradingview-lightweight/docs/snapshots/b5557684b5a3bcd459da032dbf11bfc9.json
new file mode 100644
index 000000000..cba302af6
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b5557684b5a3bcd459da032dbf11bfc9.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b5b7c3d7338a45682a2bc832319c7f04.json b/plugins/tradingview-lightweight/docs/snapshots/b5b7c3d7338a45682a2bc832319c7f04.json
new file mode 100644
index 000000000..f113c0a84
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b5b7c3d7338a45682a2bc832319c7f04.json
@@ -0,0 +1,2157 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b7a349cb9179b8540d479b63694a5e53.json b/plugins/tradingview-lightweight/docs/snapshots/b7a349cb9179b8540d479b63694a5e53.json
new file mode 100644
index 000000000..33053d979
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b7a349cb9179b8540d479b63694a5e53.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b8fffbd205a5c1d0a5da2072e03a01f0.json b/plugins/tradingview-lightweight/docs/snapshots/b8fffbd205a5c1d0a5da2072e03a01f0.json
new file mode 100644
index 000000000..c0bebd46a
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b8fffbd205a5c1d0a5da2072e03a01f0.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/b93f31618bac7631691d97e5ba6715e7.json b/plugins/tradingview-lightweight/docs/snapshots/b93f31618bac7631691d97e5ba6715e7.json
new file mode 100644
index 000000000..66ad1bdc4
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/b93f31618bac7631691d97e5ba6715e7.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/ba3ceaba8882c57d2ef63d88891e0371.json b/plugins/tradingview-lightweight/docs/snapshots/ba3ceaba8882c57d2ef63d88891e0371.json
new file mode 100644
index 000000000..317674f06
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/ba3ceaba8882c57d2ef63d88891e0371.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/bc84e9de2119d5df37cd1358f1028449.json b/plugins/tradingview-lightweight/docs/snapshots/bc84e9de2119d5df37cd1358f1028449.json
new file mode 100644
index 000000000..4e9a00fed
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/bc84e9de2119d5df37cd1358f1028449.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/bf09a5cdafd6d1c0b9c8c28136ca1a42.json b/plugins/tradingview-lightweight/docs/snapshots/bf09a5cdafd6d1c0b9c8c28136ca1a42.json
new file mode 100644
index 000000000..07b26e602
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/bf09a5cdafd6d1c0b9c8c28136ca1a42.json
@@ -0,0 +1,119 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/bfd6bb8ba041cf5e0ed1611229879aa7.json b/plugins/tradingview-lightweight/docs/snapshots/bfd6bb8ba041cf5e0ed1611229879aa7.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/c22919c62d6c2767603a5b1ff5aa5288.json b/plugins/tradingview-lightweight/docs/snapshots/c22919c62d6c2767603a5b1ff5aa5288.json
new file mode 100644
index 000000000..c7ca85ebf
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/c22919c62d6c2767603a5b1ff5aa5288.json
@@ -0,0 +1,2193 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/c626e1639227fb585f8e5e2ccd8bacee.json b/plugins/tradingview-lightweight/docs/snapshots/c626e1639227fb585f8e5e2ccd8bacee.json
new file mode 100644
index 000000000..6b62776b6
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/c626e1639227fb585f8e5e2ccd8bacee.json
@@ -0,0 +1,4502 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/c6c87990dc590043a3599292a69275d2.json b/plugins/tradingview-lightweight/docs/snapshots/c6c87990dc590043a3599292a69275d2.json
new file mode 100644
index 000000000..efe0feb15
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/c6c87990dc590043a3599292a69275d2.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/c80b073491698df04be955ec6fc0e482.json b/plugins/tradingview-lightweight/docs/snapshots/c80b073491698df04be955ec6fc0e482.json
new file mode 100644
index 000000000..79037ec87
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/cbdbd2f8e429faff3131f89aeb63aa05.json b/plugins/tradingview-lightweight/docs/snapshots/cbdbd2f8e429faff3131f89aeb63aa05.json
new file mode 100644
index 000000000..96625857e
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/cbdbd2f8e429faff3131f89aeb63aa05.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/cc5a0fbdc28cea7594a7cdbd8debe706.json b/plugins/tradingview-lightweight/docs/snapshots/cc5a0fbdc28cea7594a7cdbd8debe706.json
new file mode 100644
index 000000000..a29be5d29
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/cc5a0fbdc28cea7594a7cdbd8debe706.json
@@ -0,0 +1,751 @@
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+}
diff --git a/plugins/tradingview-lightweight/docs/snapshots/cf622118bfe41044d09826efe06fb66c.json b/plugins/tradingview-lightweight/docs/snapshots/cf622118bfe41044d09826efe06fb66c.json
new file mode 100644
index 000000000..297a9e021
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/cf622118bfe41044d09826efe06fb66c.json
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\ No newline at end of file
diff --git a/plugins/tradingview-lightweight/docs/snapshots/d47b3669c0a2cdd3b5c16dab17b52c4d.json b/plugins/tradingview-lightweight/docs/snapshots/d47b3669c0a2cdd3b5c16dab17b52c4d.json
new file mode 100644
index 000000000..ccff11b45
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/d47b3669c0a2cdd3b5c16dab17b52c4d.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/d4c8872c2e1b4e2be6181c23034a1f13.json b/plugins/tradingview-lightweight/docs/snapshots/d4c8872c2e1b4e2be6181c23034a1f13.json
new file mode 100644
index 000000000..88be4bfc9
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/d4c8872c2e1b4e2be6181c23034a1f13.json
@@ -0,0 +1,4502 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/d591f09a7a4260d4951a1cd9c419ef7c.json b/plugins/tradingview-lightweight/docs/snapshots/d591f09a7a4260d4951a1cd9c419ef7c.json
new file mode 100644
index 000000000..b29581baf
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/d6cdc8a3d5816da1656139a7d32179cb.json b/plugins/tradingview-lightweight/docs/snapshots/d6cdc8a3d5816da1656139a7d32179cb.json
new file mode 100644
index 000000000..b7b993f7b
--- /dev/null
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/d9b324026868c97ddce578a2c775a116.json b/plugins/tradingview-lightweight/docs/snapshots/d9b324026868c97ddce578a2c775a116.json
new file mode 100644
index 000000000..d417a7b07
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/d9b324026868c97ddce578a2c775a116.json
@@ -0,0 +1,400 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/da54062501547a7adf82b3df20d9ec6e.json b/plugins/tradingview-lightweight/docs/snapshots/da54062501547a7adf82b3df20d9ec6e.json
new file mode 100644
index 000000000..bb1c5815b
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/da54062501547a7adf82b3df20d9ec6e.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/dc6b414557fe3b7cb166f0f2fc865316.json b/plugins/tradingview-lightweight/docs/snapshots/dc6b414557fe3b7cb166f0f2fc865316.json
new file mode 100644
index 000000000..b98f0cffa
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/dc6b414557fe3b7cb166f0f2fc865316.json
@@ -0,0 +1,2395 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/dd5b255e9b62f41aa5c4ef5dec6c3d14.json b/plugins/tradingview-lightweight/docs/snapshots/dd5b255e9b62f41aa5c4ef5dec6c3d14.json
new file mode 100644
index 000000000..e922ea7c9
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/dd5b255e9b62f41aa5c4ef5dec6c3d14.json
@@ -0,0 +1,1025 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/df1c22e6bf62323f226cf24ac02ab20e.json b/plugins/tradingview-lightweight/docs/snapshots/df1c22e6bf62323f226cf24ac02ab20e.json
new file mode 100644
index 000000000..8ae9d63ad
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/df1c22e6bf62323f226cf24ac02ab20e.json
@@ -0,0 +1,778 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/e0745a832e04414dc99da234f24f50df.json b/plugins/tradingview-lightweight/docs/snapshots/e0745a832e04414dc99da234f24f50df.json
new file mode 100644
index 000000000..cec2fc6a7
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/e0745a832e04414dc99da234f24f50df.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/e1584ea9162f246aa47d7e4b1fbb4283.json b/plugins/tradingview-lightweight/docs/snapshots/e1584ea9162f246aa47d7e4b1fbb4283.json
new file mode 100644
index 000000000..dcf866f0e
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/e1584ea9162f246aa47d7e4b1fbb4283.json
@@ -0,0 +1,760 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/e47b822656433de5ec1ad4f2394f406c.json b/plugins/tradingview-lightweight/docs/snapshots/e47b822656433de5ec1ad4f2394f406c.json
new file mode 100644
index 000000000..8883c358c
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/e47b822656433de5ec1ad4f2394f406c.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/e5564cac84e8382429f73e975247d144.json b/plugins/tradingview-lightweight/docs/snapshots/e5564cac84e8382429f73e975247d144.json
new file mode 100644
index 000000000..8af3b25f5
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/e5564cac84e8382429f73e975247d144.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/e6978c1d9af0d9e4ed1eddc88c921bd2.json b/plugins/tradingview-lightweight/docs/snapshots/e6978c1d9af0d9e4ed1eddc88c921bd2.json
new file mode 100644
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/e7c4b226aa4415f2e5e518783354af53.json b/plugins/tradingview-lightweight/docs/snapshots/e7c4b226aa4415f2e5e518783354af53.json
new file mode 100644
index 000000000..b536b39d6
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/e7c4b226aa4415f2e5e518783354af53.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/ead40dadc3ec7f55a2705ca60444ff83.json b/plugins/tradingview-lightweight/docs/snapshots/ead40dadc3ec7f55a2705ca60444ff83.json
new file mode 100644
index 000000000..de6b67411
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/ead40dadc3ec7f55a2705ca60444ff83.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/ec51913910395c40704581d41b39a3bc.json b/plugins/tradingview-lightweight/docs/snapshots/ec51913910395c40704581d41b39a3bc.json
new file mode 100644
index 000000000..706e66656
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/ec51913910395c40704581d41b39a3bc.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/ec70d4617f7dfd1498506f01806b9e6f.json b/plugins/tradingview-lightweight/docs/snapshots/ec70d4617f7dfd1498506f01806b9e6f.json
new file mode 100644
index 000000000..962992c29
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/ec70d4617f7dfd1498506f01806b9e6f.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f0bb34beb04d953ff394d57878d6ccc8.json b/plugins/tradingview-lightweight/docs/snapshots/f0bb34beb04d953ff394d57878d6ccc8.json
new file mode 100644
index 000000000..dd3da7731
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f0bb34beb04d953ff394d57878d6ccc8.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f1c9124ce1f23c165439fd40457b0744.json b/plugins/tradingview-lightweight/docs/snapshots/f1c9124ce1f23c165439fd40457b0744.json
new file mode 100644
index 000000000..f0b0648c5
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f1c9124ce1f23c165439fd40457b0744.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f32c688a3f1020dbb6acc132e03803b5.json b/plugins/tradingview-lightweight/docs/snapshots/f32c688a3f1020dbb6acc132e03803b5.json
new file mode 100644
index 000000000..6ff9b74c9
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f32c688a3f1020dbb6acc132e03803b5.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f4467b5765fff7afce313bee25cf725a.json b/plugins/tradingview-lightweight/docs/snapshots/f4467b5765fff7afce313bee25cf725a.json
new file mode 100644
index 000000000..2fb5665b4
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f4467b5765fff7afce313bee25cf725a.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f5c9ddce32f50441e16d0dbcd6272659.json b/plugins/tradingview-lightweight/docs/snapshots/f5c9ddce32f50441e16d0dbcd6272659.json
new file mode 100644
index 000000000..44d7bd57f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f5c9ddce32f50441e16d0dbcd6272659.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f6fb2db517ab307b993050c5d38cd955.json b/plugins/tradingview-lightweight/docs/snapshots/f6fb2db517ab307b993050c5d38cd955.json
new file mode 100644
index 000000000..423a6bb02
--- /dev/null
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f996e648b92b6a0d0486e2bd87f9674d.json b/plugins/tradingview-lightweight/docs/snapshots/f996e648b92b6a0d0486e2bd87f9674d.json
new file mode 100644
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--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f996e648b92b6a0d0486e2bd87f9674d.json
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/f997e3f193300eb5dbebf3e5d1daaef0.json b/plugins/tradingview-lightweight/docs/snapshots/f997e3f193300eb5dbebf3e5d1daaef0.json
new file mode 100644
index 000000000..d88431d43
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/f997e3f193300eb5dbebf3e5d1daaef0.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/fa8d2568827e1e859fb89f29a045560f.json b/plugins/tradingview-lightweight/docs/snapshots/fa8d2568827e1e859fb89f29a045560f.json
new file mode 100644
index 000000000..200986637
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/fa8d2568827e1e859fb89f29a045560f.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/fae4076b7c9673678ff807c7bccf741a.json b/plugins/tradingview-lightweight/docs/snapshots/fae4076b7c9673678ff807c7bccf741a.json
new file mode 100644
index 000000000..917b22cd9
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/fae4076b7c9673678ff807c7bccf741a.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/fb8fc82f8d3ff88f3446a86c494ec818.json b/plugins/tradingview-lightweight/docs/snapshots/fb8fc82f8d3ff88f3446a86c494ec818.json
new file mode 100644
index 000000000..a9c70f58e
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/fb8fc82f8d3ff88f3446a86c494ec818.json
@@ -0,0 +1,751 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/fccd3fe1384a9b38c62e2802857c973c.json b/plugins/tradingview-lightweight/docs/snapshots/fccd3fe1384a9b38c62e2802857c973c.json
new file mode 100644
index 000000000..530aec243
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/fccd3fe1384a9b38c62e2802857c973c.json
@@ -0,0 +1,1439 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/fd92481143888466ae9a66508375504c.json b/plugins/tradingview-lightweight/docs/snapshots/fd92481143888466ae9a66508375504c.json
new file mode 100644
index 000000000..992623d6f
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/fd92481143888466ae9a66508375504c.json
@@ -0,0 +1,2121 @@
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diff --git a/plugins/tradingview-lightweight/docs/snapshots/fe5ddc77e2d7d0a9eaa2b36d8d250f81.json b/plugins/tradingview-lightweight/docs/snapshots/fe5ddc77e2d7d0a9eaa2b36d8d250f81.json
new file mode 100644
index 000000000..044b3c81a
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/snapshots/fe5ddc77e2d7d0a9eaa2b36d8d250f81.json
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+      "type": "deephaven.plot.tradingview_lightweight.TvlChart",
+      "data": {
+        "image": "assets/adc27ba348b207cbf1f27005dca2afcbd0177aeef30d59a8b76148fd9a862a52.png",
+        "width": 860,
+        "height": 573,
+        "alt": "price_marker_chart"
+      }
+    }
+  }
+}
diff --git a/plugins/tradingview-lightweight/docs/styling.md b/plugins/tradingview-lightweight/docs/styling.md
new file mode 100644
index 000000000..62931c2ce
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/styling.md
@@ -0,0 +1,269 @@
+<!-- coverage-seen-elsewhere:
+  price_formatter -> price-formats.md
+  tickmarks_price_formatter -> price-formats.md
+  percentage_formatter -> price-formats.md
+  tickmarks_percentage_formatter -> price-formats.md
+  watermark_text -> watermark.md
+  watermark_lines -> watermark.md
+  watermark_image_url -> watermark.md
+  right_price_scale_mode -> price-scale.md
+  left_price_scale_mode -> price-scale.md
+  default_visible_price_scale_id -> multiple-axes.md
+  time_visible -> time-scale.md
+  seconds_visible -> time-scale.md
+  right_offset -> time-scale.md
+  bar_spacing -> time-scale.md
+  pane_stretch_factors -> multi-pane.md
+  pane_preserve_empty -> multi-pane.md
+  pane_separator_color -> multi-pane.md
+-->
+
+# Styling and Layout
+
+The TVL chart accepts dozens of chart-level keyword arguments that control how the chart looks before any series is drawn: background colors, grid lines, crosshair behavior, fonts, and pane separators. Use this page when you want to match a brand palette, build a light/dark theme, or restyle the cursor and grid for a denser dashboard.
+
+All styling kwargs in this guide live on `chart()` and on every convenience factory (`candlestick()`, `line()`, etc.). The chart wrapper accepts a compact subset of the styling parameters (background, text color, crosshair, watermark); the full surface lives on `chart()`.
+
+## What are the styling options useful for?
+
+- **Theming**: Build a light and dark palette by toggling background, text, and grid colors; the same chart code renders against either theme.
+- **Matching a brand**: Override gradients, grid lines, and crosshair color to keep charts on-brand inside an existing UI.
+- **Dense dashboards**: Tune font size, grid visibility, and pane separators so several charts can sit side by side without visual clutter.
+- **Accessibility**: Adjust contrast and crosshair visibility for users who need higher-contrast or focus-style cues.
+
+## Examples
+
+### Apply a dark theme
+
+The simplest theme switch is three colors: background, text, and grid. Pass them to `chart()` and the whole surface re-renders against the new palette. The grid uses the `vert_lines_*` / `horz_lines_*` families so you can color and style the two axes independently.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    background_color="#1e1e1e",
+    text_color="#e0e0e0",
+    vert_lines_color="#2a2a2a",
+    horz_lines_color="#2a2a2a",
+)
+```
+
+Pair `background_color` with `text_color` so axis labels stay legible against the new background.
+
+### Build a vertical gradient background
+
+To render a gradient, swap `background_color` for the `background_top_color` / `background_bottom_color` pair. TVL renders a vertical gradient between the two stops. The two arguments must be used together; supplying only one falls back to the solid background path.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.area(values, timestamp="Timestamp", value="Value"),
+    background_top_color="#0d1b2a",
+    background_bottom_color="#1b263b",
+    text_color="#e0e1dd",
+    vert_lines_color="#22304a",
+    horz_lines_color="#22304a",
+)
+```
+
+The `ColorType` enum values (`"solid"`, `"gradient"`) are inferred from which background arguments you set; there is no explicit `color_type` kwarg. The example above selects the gradient path:
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+# ColorType is inferred — the constants are shown here only for reference.
+color_type = "gradient"  # vs. "solid"
+chart = tvl.chart(
+    tvl.area(values, timestamp="Timestamp", value="Value"),
+    background_top_color="#0d1b2a",
+    background_bottom_color="#1b263b",
+)
+```
+
+### Customize grid lines
+
+The grid is two independent sets of lines: vertical (time-axis grid) and horizontal (price-axis grid). Each has visibility, color, and `LineStyle` controls. Use `horz_lines_visible=False` to hide one set while keeping the other.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    vert_lines_visible=True,
+    vert_lines_color="#3a3a3a",
+    vert_lines_style="dashed",
+    horz_lines_visible=True,
+    horz_lines_color="#3a3a3a",
+    horz_lines_style="dotted",
+)
+```
+
+`LineStyle` accepts `"solid"`, `"dotted"`, `"dashed"`, `"large_dashed"`, and `"sparse_dotted"`.
+
+### Switch crosshair mode: normal, magnet, or hidden
+
+The `CrosshairMode` enum controls how the cursor crosshair behaves on hover. `"normal"` follows the pointer freely; `"magnet"` snaps to the nearest data point; `"hidden"` removes the crosshair entirely. The fourth value, `"magnet_ohlc"`, snaps to the nearest OHLC point on candlestick / bar charts.
+
+```python order=normal,magnet,magnet_ohlc,hidden,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+normal = tvl.chart(tvl.line(values, timestamp="Timestamp", value="Value"), crosshair_mode="normal")
+magnet = tvl.chart(tvl.line(values, timestamp="Timestamp", value="Value"), crosshair_mode="magnet")
+magnet_ohlc = tvl.chart(tvl.line(values, timestamp="Timestamp", value="Value"), crosshair_mode="magnet_ohlc")
+hidden = tvl.chart(tvl.line(values, timestamp="Timestamp", value="Value"), crosshair_mode="hidden")
+```
+
+Use `"magnet"` for sparse data where exact-point readouts matter; `"normal"` for continuous-feeling cursor tracking on dense data.
+
+### Tune the crosshair line and label
+
+Beyond the mode, every crosshair line and label has its own color, width, style, and visibility kwargs. The vertical (`crosshair_vert_line_*`) line crosses the time axis and the horizontal (`crosshair_horz_line_*`) line crosses the price axis.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    crosshair_mode="normal",
+    crosshair_vert_line_color="#ffc857",
+    crosshair_vert_line_width=2,
+    crosshair_vert_line_style="dashed",
+    crosshair_vert_line_label_visible=True,
+    crosshair_vert_line_label_background_color="#ffc857",
+    crosshair_horz_line_color="#ffc857",
+    crosshair_horz_line_width=2,
+    crosshair_horz_line_style="dotted",
+    crosshair_horz_line_label_background_color="#ffc857",
+)
+```
+
+`crosshair_do_not_snap_to_hidden_series` is helpful in magnet mode when you want the crosshair to ignore series the user has toggled off.
+
+### Hover the active series on top
+
+`hovered_series_on_top` re-orders the z-stack so the series the cursor is currently over draws above its siblings. The default is `True`, but you can disable it for fixed-layer charts where draw order needs to be deterministic.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", color="#ef4444"),
+    tvl.line(values.update(["Value = Value + 10"]), timestamp="Timestamp", value="Value", color="#3b82f6"),
+    hovered_series_on_top=True,
+)
+```
+
+This pairs well with crosshair `"magnet"` mode, since the snapped-to series moves to the top automatically.
+
+### Set the chart font
+
+`font_size` controls the base axis-label font size in pixels. The font family is inherited from the host page; TVL does not expose a per-chart font-family override, since chart text is rendered to canvas and uses the closest available system stack.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    font_size=14,
+    text_color="positive",
+)
+```
+
+Increase `font_size` for dashboard tiles viewed from a distance, or shrink it to fit dense small-multiples layouts.
+
+### TradingView attribution logo
+
+This plugin hides the lightweight-charts attribution logo by default. Upstream says users should include the NOTICE attribution and a TradingView link on a page available to users; the built-in logo is one way to satisfy the link requirement. Set `attribution_logo=True` to show it.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    attribution_logo=True,
+)
+```
+
+### Pick a wide-gamut color space
+
+`color_space` selects the underlying canvas color space. The default `"srgb"` matches what every browser ships; `"display-p3"` opts in to the wide-gamut P3 space on capable displays, which gives richer reds and greens. Use it when your design system specifies P3 colors.
+
+```python order=chart,standard,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    color_space="display-p3",
+    background_color="#0a0a0a",
+)
+
+# Pin sRGB explicitly when you want predictable cross-display output.
+standard = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    color_space="srgb",
+    background_color="#0a0a0a",
+)
+```
+
+The two `ColorSpace` enum values are `"srgb"` and `"display-p3"`.
+
+### Control scroll and zoom interactions
+
+The `handle_scroll_*` and `handle_scale_*` families enable or disable specific input gestures, such as mouse wheel zoom, touch drag, and double-click reset. The top-level `handle_scroll` and `handle_scale` booleans short-circuit all sub-options.
+
+```python order=chart,tap_exit,values
+import deephaven.plot.tradingview_lightweight as tvl
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    handle_scroll_mouse_wheel=True,
+    handle_scroll_pressed_mouse_move=True,
+    handle_scale_pinch=True,
+    handle_scale_axis_double_click_reset=True,
+    kinetic_scroll_mouse=False,
+    tracking_mode_exit_mode="on_touch_end",
+)
+
+# Alternative: exit tracking mode on the next tap anywhere on the chart.
+tap_exit = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    tracking_mode_exit_mode="on_next_tap",
+)
+```
+
+`TrackingModeExitMode` accepts `"on_touch_end"` and `"on_next_tap"`.
+
+### Switch last-price animation modes
+
+`LastPriceAnimationMode` controls the pulse animation on the last-price marker for line / area / baseline series (candlestick / bar / histogram don't have it). Use `"disabled"` for static snapshots, `"continuous"` to make the marker pulse continuously while the chart is visible, and `"on_data_update"` to pulse only when new data arrives.
+
+The kwarg lives on the series factory, not on the chart-styling wrapper, so set it directly on `tvl.line` (or `area` / `baseline`):
+
+```python order=disabled_chart,pulsing_chart,on_update_chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+disabled_chart = tvl.line(values, timestamp="Timestamp", value="Value", last_price_animation="disabled")
+pulsing_chart = tvl.line(values, timestamp="Timestamp", value="Value", last_price_animation="continuous")
+on_update_chart = tvl.line(values, timestamp="Timestamp", value="Value", last_price_animation="on_data_update")
+```
+
+The three values map directly to the `LastPriceAnimationMode` Literal alias. Use `"disabled"` wherever snapshot determinism matters; the other two introduce time-dependent rendering.
+
+## API Reference
+
+For the full `tvl.chart` signature, see the [Chart container](chart.md#api-reference) page.
diff --git a/plugins/tradingview-lightweight/docs/time-scale.md b/plugins/tradingview-lightweight/docs/time-scale.md
new file mode 100644
index 000000000..748260cc8
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/time-scale.md
@@ -0,0 +1,233 @@
+<!-- coverage-seen-elsewhere:
+  watermark_text -> watermark.md
+  crosshair_mode -> styling.md
+  background_color -> styling.md
+-->
+
+# Time Scale
+
+The time scale is the horizontal axis at the bottom of a chart. TVL exposes its visibility, label density, border, tick formatting, scroll offset, and the underlying time-value model (UTC timestamps vs. business days) through a family of `chart()` kwargs. This page covers the most common ones, plus the helper types (`BusinessDay`, `business_day()`, `is_business_day()`, `is_utc_timestamp()`) for when you need to work outside numeric timestamps.
+
+Use this page when you want to hide weekends and holidays, push the most recent bar away from the right edge to make room for annotations, hide seconds, or stop tick labels from overlapping on a narrow chart.
+
+## What are the time-scale options useful for?
+
+- **Trading-day charts**: Skip non-business days so a five-day work week and ten holidays per year stop pushing data off-screen.
+- **Aligning multiple charts**: Pin the right edge with `fix_right_edge` so two charts stacked vertically share a consistent time anchor.
+- **Live tail UX**: `right_offset` reserves whitespace on the right so the freshest bar isn't glued to the price scale.
+- **Dense time axes**: `tick_mark_max_character_length` and `uniform_distribution` keep labels readable on narrow charts.
+
+## Examples
+
+### Show time and seconds on the axis
+
+The two most common toggles are `time_visible` (show time-of-day on intra-day data) and `seconds_visible` (show seconds when zoomed in tight enough). Set both for high-frequency data.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    time_visible=True,
+    seconds_visible=True,
+)
+```
+
+When `time_visible=False`, the axis shows only the date, which suits daily-bar charts.
+
+### Hide the time scale entirely
+
+Set `time_scale_visible=False` to hide the bottom axis when you have several stacked panes and only need the axis on the outermost one.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    time_scale_visible=False,
+)
+```
+
+Combine with `pane_index` (see [multi-pane](multi-pane.md)) to hide the per-pane axis on all but the bottom pane.
+
+### Right-offset whitespace for live charts
+
+`right_offset` adds bars of empty space to the right of the latest data point, keeping the live tip visually separated from the price scale. Use `right_offset_pixels` for a fixed pixel inset instead.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    right_offset=12,
+    bar_spacing=8,
+)
+```
+
+`bar_spacing` (initial pixels per bar) plus `min_bar_spacing` / `max_bar_spacing` (zoom limits) let you set the zoom envelope.
+
+### Pin the visible range edges
+
+`fix_left_edge` and `fix_right_edge` lock the visible range to the data boundaries, so scrolling stops at the first and last bar respectively. `lock_visible_time_range_on_resize` keeps the same logical window when the widget is resized, and `right_bar_stays_on_scroll` keeps the latest bar parked at the right.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    fix_left_edge=True,
+    fix_right_edge=True,
+    lock_visible_time_range_on_resize=True,
+    right_bar_stays_on_scroll=True,
+    shift_visible_range_on_new_bar=False,
+)
+```
+
+For live charts you usually want `right_bar_stays_on_scroll=True` and `shift_visible_range_on_new_bar=True` so each new bar slides the viewport.
+
+### Tune tick density
+
+`tick_mark_max_character_length` caps how many characters each tick label can use; the chart will drop ticks until the labels fit. `uniform_distribution` enforces a uniform tick spacing rather than the default "snap to nice intervals" behavior. `time_scale_minimum_height` reserves vertical space so the time scale doesn't shrink below a usable height.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    tick_mark_max_character_length=10,
+    uniform_distribution=True,
+    time_scale_minimum_height=32,
+    time_scale_ticks_visible=True,
+    allow_bold_labels=True,
+)
+```
+
+`allow_bold_labels` lets the chart render bold weight at major boundaries (year, month) for emphasis.
+
+### Style the time-scale border
+
+The border between the time scale and the plot area is its own layer. Toggle visibility with `time_scale_border_visible` and color with `time_scale_border_color`.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    time_scale_border_visible=True,
+    time_scale_border_color="#888",
+)
+```
+
+Hide the border for borderless dashboard tiles.
+
+### Tick mark types: what TVL labels at each boundary
+
+The `TickMarkType` enum (`"year"`, `"month"`, `"day_of_month"`, `"time"`, `"time_with_seconds"`) is the set of label kinds the time scale renders at different zoom levels. TVL picks the right type per tick automatically based on the visible range. The enum is exposed for parity with the upstream JS API but has no current Python consumer (it would require a JavaScript `tickMarkFormatter` callback, which TVL does not allow).
+
+| `TickMarkType` value | rendered at |
+|---|---|
+| `"year"` | a year boundary, e.g. `2024` |
+| `"month"` | a month boundary, e.g. `Mar` or `Mar '24` |
+| `"day_of_month"` | a day boundary, e.g. `15` |
+| `"time"` | intra-day, e.g. `14:30` |
+| `"time_with_seconds"` | intra-day with seconds, e.g. `14:30:05` |
+
+When the chart spans years you'll see `"year"` and `"month"` ticks; zoomed in to a single day, you'll see `"day_of_month"` and `"time"`; zoomed in to a few minutes, `"time_with_seconds"`.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+from typing import get_args
+
+# Snapshot of the full TickMarkType alias — handy when wiring a JS-side
+# tickMarkFormatter callback or building a legend on top of the chart.
+tick_kinds = list(get_args(tvl.TickMarkType))
+assert tick_kinds == [
+    "year",
+    "month",
+    "day_of_month",
+    "time",
+    "time_with_seconds",
+]
+```
+
+### Business-day timestamps for trading-hours charts
+
+The `BusinessDay` TypedDict lets you label points without weekends and holidays; the time scale plots business days as equally-spaced ticks regardless of calendar gaps. Use `business_day(year, month, day)` to construct them.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+# Build a few business-day points
+b1 = tvl.business_day(2024, 1, 2)  # Tuesday
+b2 = tvl.business_day(2024, 1, 3)  # Wednesday
+b3 = tvl.business_day(2024, 1, 4)  # Thursday
+
+print(b1)  # {'year': 2024, 'month': 1, 'day': 2}
+```
+
+`BusinessDay` instances are dicts, so they round-trip cleanly through tables and JSON. The companion type-guard helpers, `is_business_day()` and `is_utc_timestamp()`, let you tell business-day points apart from numeric UTC timestamps:
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+bd = tvl.business_day(2024, 1, 2)
+ts = 1_704_153_600  # seconds since epoch, UTC
+
+assert tvl.is_business_day(bd)
+assert not tvl.is_business_day(ts)
+assert tvl.is_utc_timestamp(ts)
+assert not tvl.is_utc_timestamp(bd)
+```
+
+The two predicates mirror the JS API's `isBusinessDay()` / `isUTCTimestamp()` type guards.
+
+### UTC vs. local timestamps
+
+TVL's underlying renderer treats numeric time values as **seconds since the Unix epoch, UTC**. Deephaven `Instant` columns are encoded with nanosecond precision; the plugin converts them to UTC seconds when serializing. Use `is_utc_timestamp()` to tell raw numeric times apart from `BusinessDay` dicts when writing helpers that accept either.
+
+```python
+import deephaven.plot.tradingview_lightweight as tvl
+
+
+def label_kind(t):
+    if tvl.is_business_day(t):
+        return "business_day"
+    if tvl.is_utc_timestamp(t):
+        return "utc_timestamp"
+    return "other"
+
+
+print(label_kind(tvl.business_day(2024, 1, 2)))  # business_day
+print(label_kind(1_704_153_600))  # utc_timestamp
+print(label_kind("2024-01-02"))  # other
+```
+
+Display timezone is a UI concern: the chart renders the same UTC second the same way regardless of the viewer's locale. For "show in NY time", use a chart-level locale or pre-shift the data.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.business_day
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.is_business_day
+```
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.is_utc_timestamp
+```
+
+For the full `tvl.chart` signature (including all `time_*`, `right_offset`, `bar_spacing`, etc. options), see the [Chart container](chart.md#api-reference) page.
diff --git a/plugins/tradingview-lightweight/docs/titles-legends.md b/plugins/tradingview-lightweight/docs/titles-legends.md
new file mode 100644
index 000000000..c19a6f166
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/titles-legends.md
@@ -0,0 +1,216 @@
+<!-- coverage-seen-elsewhere:
+  watermark_text -> watermark.md
+  watermark_lines -> watermark.md
+  watermark_image_url -> watermark.md
+  watermark_color -> watermark.md
+  watermark_font_size -> watermark.md
+  watermark_font_style -> watermark.md
+  watermark_horz_align -> watermark.md
+  watermark_vert_align -> watermark.md
+  background_color -> styling.md
+  crosshair_mode -> styling.md
+-->
+
+# Titles, Legends, and Watermarks
+
+TVL doesn't have a separate "title" widget the way Plotly does. Instead, the chart title lives on the watermark, and per-series titles drive the in-chart legend that appears in the top-left corner. This page covers titles and legends and gives a brief tour of the watermark options; for the full watermark treatment (multi-line, image watermarks, alignment) see [watermark](watermark.md).
+
+Use this page when you want to label a chart for a dashboard tile, show or hide the legend on individual series, or pick a corner for a single-line watermark.
+
+## What are titles and legends useful for?
+
+- **Identifying a chart in a dashboard**: A watermark title tells viewers what they're looking at: symbol, instrument, or scenario.
+- **Per-series labels**: Each series can carry a `title=`, which appears in the chart's legend overlay along with the live last-value readout.
+- **Brand and context**: Watermarks can include disclaimers, environment names ("staging"), or "as of" timestamps without taking up screen space.
+- **Selective legend**: Hide the last-value badge on noisy overlay series with `last_value_visible=False` while keeping the title.
+
+## Examples
+
+### Add a chart title via watermark
+
+The simplest title is a single-line watermark. `watermark_text` is the text; `watermark_visible=True` enables it; `watermark_color` and `watermark_font_size` style it.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    watermark_visible=True,
+    watermark_text="Reference Index",
+    watermark_color="rgba(0, 0, 0, 0.35)",
+    watermark_font_size=24,
+)
+```
+
+The watermark sits centered behind the data by default. See [watermark](watermark.md) for alignment options.
+
+### Position the watermark in a corner
+
+`watermark_horz_align` (`"left"` / `"center"` / `"right"`) and `watermark_vert_align` (`"top"` / `"center"` / `"bottom"`) place the watermark in any of nine positions. Use a corner placement when the watermark serves as a chart title rather than a centered background label.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    watermark_visible=True,
+    watermark_text="USD / EUR",
+    watermark_horz_align="left",
+    watermark_vert_align="top",
+    watermark_font_size=18,
+    watermark_color="rgba(0, 0, 0, 0.55)",
+)
+```
+
+For a "title bar" effect, anchor top-left and increase the color opacity.
+
+### Show series titles in the legend
+
+Each series factory accepts a `title=` parameter, and the value appears in the legend overlay in the top-left of the chart. Setting `title` on multiple series gives each a labeled badge.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+shifted = values.update_view(["Value = Value + 10"])
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", title="Index", color="#2563eb"),
+    tvl.line(shifted, timestamp="Timestamp", value="Value", title="Index +10", color="#dc2626"),
+)
+```
+
+Without `title`, the series shows a colored marker with the live value but no name. That's fine for single-series charts, but awkward when you have several overlays.
+
+### Hide the last-value badge on noisy series
+
+`last_value_visible=False` hides the price-axis pill that follows each series. Use this for noisy reference overlays where the live value isn't useful (e.g. a moving-average line above a candlestick).
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+shifted = values.update_view(["Value = Value + 10"])
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", title="Main", color="#2563eb"),
+    tvl.line(
+        shifted,
+        timestamp="Timestamp",
+        value="Value",
+        title="Reference",
+        color="#94a3b8",
+        last_value_visible=False,
+    ),
+)
+```
+
+The series remains in the legend overlay; only the right-edge price label disappears.
+
+### Toggle series visibility from the start
+
+`visible=False` starts the series hidden. Useful for "click to enable" legend interactions handled outside Python, or for setting up a chart where most series are off by default.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value", title="Primary"),
+    tvl.line(
+        values.update_view(["Value = Value + 5"]),
+        timestamp="Timestamp",
+        value="Value",
+        title="Optional overlay",
+        visible=False,
+    ),
+)
+```
+
+The legend entry still shows; the line doesn't render until something toggles `visible` back on.
+
+### Multi-line watermark for richer titles
+
+For a two-line title (instrument + tagline, "as of" timestamps, etc.) pass a list of `WatermarkLine` dataclasses to `watermark_lines`. Each line can carry its own color, font size, line height, and font style. See [watermark](watermark.md) for details.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    watermark_visible=True,
+    watermark_horz_align="center",
+    watermark_vert_align="center",
+    watermark_lines=[
+        tvl.WatermarkLine(
+            text="USD / EUR",
+            color="rgba(0, 0, 0, 0.5)",
+            font_size=32,
+        ),
+        tvl.WatermarkLine(
+            text="Daily close, 2024",
+            color="rgba(0, 0, 0, 0.3)",
+            font_size=14,
+            font_style="italic",
+        ),
+    ],
+)
+```
+
+Single-line shortcuts (`watermark_text` / `watermark_color` / `watermark_font_*`) and `watermark_lines` are mutually exclusive, so pick one path.
+
+### Image watermark as a "brand mark"
+
+`watermark_image_url` is the third watermark path, rendering a logo or seal in the chart. Combine with `watermark_image_alpha` for a subtle background mark.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    watermark_image_visible=True,
+    watermark_image_url="https://example.com/brand.png",
+    watermark_image_max_width=120,
+    watermark_image_max_height=120,
+    watermark_image_padding=16,
+    watermark_image_alpha=0.15,
+)
+```
+
+See [watermark](watermark.md) for the full image-watermark surface.
+
+### Compact dashboard-tile titles
+
+For dense small-multiples layouts, use a small corner-anchored watermark as a tile label. Pair with `font_size` on the chart so the axis labels stay legible in a tile.
+
+```python order=chart,values
+import deephaven.plot.tradingview_lightweight as tvl
+
+values = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(values, timestamp="Timestamp", value="Value"),
+    font_size=10,
+    watermark_visible=True,
+    watermark_text="AAA",
+    watermark_horz_align="left",
+    watermark_vert_align="top",
+    watermark_font_size=12,
+    watermark_color="rgba(0, 0, 0, 0.55)",
+)
+```
+
+This works well for tiled overview screens: title in the corner, data filling the rest.
+
+## API Reference
+
+For the full `tvl.chart` signature, see the [Chart container](chart.md#api-reference) page.
diff --git a/plugins/tradingview-lightweight/docs/tooltip.md b/plugins/tradingview-lightweight/docs/tooltip.md
new file mode 100644
index 000000000..c41986315
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/tooltip.md
@@ -0,0 +1,81 @@
+# Tracking Tooltip
+
+A tracking tooltip is a small overlay that follows the cursor and shows the value under it. Turn it on with `tooltip_visible=True` on `tvl.chart(...)`:
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+
+data = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(data, timestamp="Timestamp", value="Value", title="Price"),
+    tooltip_visible=True,
+)
+```
+
+The tooltip box appears near the cursor as you move across the chart, showing the series title, its value at that time, and the time itself. It hides automatically when the cursor leaves the plot area.
+
+## A single focused series
+
+The tooltip always shows exactly one series: the one in focus. In a single-series chart that is the series you plotted. In a multi-series chart the focused series is whichever line is vertically nearest the cursor within the time slice under it: the chart reads each series' value at that time and picks the one closest to the cursor's height. As you move the cursor up and down between overlaid lines, the tooltip switches to track whichever line is nearest.
+
+This keeps the tooltip readable no matter how many series you overlay: it is a single, compact box, not a growing legend. The title line is tinted with the focused series' own color, so you can tell which series the value belongs to.
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+chart = tvl.chart(
+    tvl.line(ohlc, timestamp="Timestamp", value="Close", title="Close"),
+    tvl.line(ohlc, timestamp="Timestamp", value="Ema", title="EMA"),
+    tooltip_visible=True,
+)
+```
+
+## What the tooltip shows
+
+`tooltip_visible` is the master switch. The remaining options refine what each tooltip displays, and only take effect when the tooltip is visible:
+
+| Option | Default | Effect |
+|---|---|---|
+| `tooltip_visible` | off | Enable the tracking tooltip. |
+| `tooltip_show_title` | `True` | Show the series title line (the series `title`, or its id when untitled), tinted with the series color. |
+| `tooltip_show_value` | `True` | Show the series value at the cursor. For candlestick and bar series this is the close. |
+| `tooltip_show_date` | `True` | Show the time/date line, formatted the same way as the time axis. |
+| `tooltip_value_precision` | series price format | Override the number of decimal places shown for the value. |
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+
+data = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(data, timestamp="Timestamp", value="Value", title="Price"),
+    tooltip_visible=True,
+    tooltip_show_date=False,     # value only, no time line
+    tooltip_value_precision=2,   # always two decimals
+)
+```
+
+Setting any of the detail options without `tooltip_visible=True` raises a `ValueError`, so a tooltip that is configured but never shown is caught early rather than silently doing nothing.
+
+## Colors come from the theme
+
+The tooltip has no color options. Its background, text, and border are drawn from the active Deephaven theme so it always matches the rest of the UI, in light and dark themes alike. The one piece of per-series color is the title line, which is tinted automatically with the focused series' color. If you restyle a series' color, its tooltip title follows.
+
+## Tooltip and crosshair
+
+The tooltip tracks the chart's crosshair, so it works together with `crosshair_mode`. With the default magnet crosshair the reported value snaps to the nearest data point; with `crosshair_mode="normal"` it follows the cursor freely. The tooltip works with any crosshair mode; the mode only changes which point the value is read from.
+
+```python skip-test
+import deephaven.plot.tradingview_lightweight as tvl
+
+data = tvl.data.values()
+
+chart = tvl.chart(
+    tvl.line(data, timestamp="Timestamp", value="Value", title="Price"),
+    tooltip_visible=True,
+    crosshair_mode="magnet",
+)
+```
diff --git a/plugins/tradingview-lightweight/docs/watermark.md b/plugins/tradingview-lightweight/docs/watermark.md
new file mode 100644
index 000000000..16d364530
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/watermark.md
@@ -0,0 +1,173 @@
+# Watermark
+
+A watermark is a faint label drawn behind the data of a chart, typically the ticker symbol, the dataset name, or the chart title. Use one when you want chart context that doesn't compete with the price action for attention.
+
+There are two ways to add a watermark. The single-line shortcut uses `tvl.chart(watermark_text=..., watermark_color=..., ...)`. The multi-line form takes a list of [`tvl.watermark_line(...)`](#api-reference) entries via `watermark_lines=[...]`, one per row of text, each with its own color, font size, line height, and font style.
+
+<!-- coverage-seen-elsewhere:
+  watermark_visible -> exercised below
+  watermark_image_* -> not yet exercised; covered by docstring on chart()
+-->
+
+## What watermarks are useful for?
+
+- **Branding the chart**: A ticker symbol or dataset name in the background tells the viewer what they're looking at without occupying a corner.
+- **Stating context**: A two-line watermark can show, for example, `AAPL` above and `Daily` below: instrument plus timeframe.
+- **Styling for theme**: Adjusting color and font-style lets a watermark blend with light or dark themes.
+- **Positioning to taste**: `watermark_horz_align` and `watermark_vert_align` cover the nine canonical anchor points on the chart.
+
+## Examples
+
+### Add a simple single-line watermark
+
+The shortest watermark: just `watermark_text`. Defaults take care of color, font size, and alignment.
+
+```python order=basic_watermark,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc)
+basic_watermark = tvl.chart(price, watermark_text="AAPL")
+```
+
+The chart shows `AAPL` faintly centered behind the price.
+
+### Style the single-line watermark
+
+The single-line path bundles the styling options directly on `tvl.chart()`: color, font size, font style (italic/normal/etc.), line height, and visibility.
+
+```python order=styled_watermark,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc)
+
+styled_watermark = tvl.chart(
+    price,
+    watermark_text="AAPL",
+    watermark_color="rgba(25,118,210,0.25)",
+    watermark_font_size=80,
+    watermark_font_style="italic",
+    watermark_line_height=1.0,
+    watermark_visible=True,
+)
+```
+
+The watermark is now a large, semi-transparent, italicized blue label.
+
+### Multi-line watermark
+
+For two or more lines, switch to `watermark_lines=[...]`. Each entry is built with `tvl.watermark_line(...)` and renders as its own line of text with optional per-line styling: color, font size, line height, and font style.
+
+```python order=multi_watermark,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc)
+
+lines = [
+    tvl.watermark_line(
+        "AAPL",
+        color="rgba(25,118,210,0.35)",
+        font_size=72,
+        line_height=80.0,
+    ),
+    tvl.watermark_line(
+        "Daily",
+        color="rgba(120,120,120,0.45)",
+        font_size=32,
+        line_height=40.0,
+        font_style="italic",
+    ),
+]
+
+multi_watermark = tvl.chart(price, watermark_lines=lines)
+```
+
+Two lines, two styles. The single-line shortcut and `watermark_lines` are mutually exclusive, so pick one.
+
+### Position the watermark
+
+`watermark_horz_align` accepts `"left"`, `"center"`, `"right"` (the values of `HorzAlign`). `watermark_vert_align` accepts `"top"`, `"center"`, `"bottom"` (the values of `VertAlign`). Together they give nine anchor positions; here we cover every value of each enum across three charts.
+
+```python order=top_left,top_center,top_right,middle_left,middle_center,middle_right,bottom_left,bottom_center,bottom_right,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+def _wm(horz, vert):
+    return tvl.chart(
+        tvl.candlestick(ohlc),
+        watermark_text=f"{horz}/{vert}",
+        watermark_color="rgba(25,118,210,0.35)",
+        watermark_font_size=40,
+        watermark_horz_align=horz,
+        watermark_vert_align=vert,
+    )
+
+top_left      = _wm("left",   "top")
+top_center    = _wm("center", "top")
+top_right     = _wm("right",  "top")
+middle_left   = _wm("left",   "center")
+middle_center = _wm("center", "center")
+middle_right  = _wm("right",  "center")
+bottom_left   = _wm("left",   "bottom")
+bottom_center = _wm("center", "bottom")
+bottom_right  = _wm("right",  "bottom")
+```
+
+Nine variants, one for each combination of `HorzAlign` and `VertAlign`.
+
+### Hide the watermark
+
+`watermark_visible=False` keeps the configuration but skips drawing. Useful when toggling a watermark on and off without rebuilding the chart configuration.
+
+```python order=hidden_watermark,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc)
+hidden_watermark = tvl.chart(
+    price,
+    watermark_text="AAPL",
+    watermark_color="rgba(25,118,210,0.35)",
+    watermark_visible=False,
+)
+```
+
+The chart shows no watermark even though `watermark_text` is set.
+
+### Image watermark
+
+In addition to text, the chart accepts an image watermark (logo or background graphic). Set `watermark_image_url` and tune `watermark_image_max_width`, `watermark_image_max_height`, `watermark_image_padding`, and `watermark_image_alpha`. The image-watermark path is independent from the text-watermark path; both can coexist.
+
+```python order=image_watermark,ohlc
+import deephaven.plot.tradingview_lightweight as tvl
+
+ohlc = tvl.data.ohlc()
+
+price = tvl.candlestick(ohlc)
+image_watermark = tvl.chart(
+    price,
+    watermark_image_url="https://www.deephaven.io/img/dh-community-logo.svg",
+    watermark_image_max_width=200,
+    watermark_image_max_height=80,
+    watermark_image_padding=12,
+    watermark_image_alpha=0.2,
+    watermark_image_visible=True,
+)
+```
+
+The Deephaven logo appears behind the data at 20% opacity.
+
+## API Reference
+
+The watermark options live on `tvl.chart()` (single-line shortcut + image options). See the [Chart container](chart.md) page for the full `tvl.chart` API. `tvl.watermark_line(...)` builds each entry of the multi-line form.
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.watermark_line
+```
diff --git a/plugins/tradingview-lightweight/docs/yield-curve.md b/plugins/tradingview-lightweight/docs/yield-curve.md
new file mode 100644
index 000000000..0703b1f38
--- /dev/null
+++ b/plugins/tradingview-lightweight/docs/yield-curve.md
@@ -0,0 +1,112 @@
+<!-- coverage-seen-elsewhere:
+  crosshair_mode -> styling.md
+  watermark_text -> watermark.md
+  background_color -> styling.md
+  text_color -> styling.md
+-->
+
+# Yield Curve Chart
+
+A yield-curve chart plots yield against maturity (in months) rather than against time. It uses TVL's `createYieldCurveChart` renderer, which puts a numeric maturity axis on the horizontal, so the x-coordinates are *durations*, not timestamps. Use it when the x-axis is "how far out" rather than "when".
+
+The chart supports two series shapes: `"line"` (default) and `"area"`. Other series types are rejected at construction time, so passing `"histogram"` or anything else raises a `ValueError`.
+
+## What are yield-curve charts useful for?
+
+- **Treasury / sovereign curves**: The canonical use. Render the on-the-run curve and watch its shape evolve from a normal upward slope to inversion.
+- **Swap and forward curves**: Any term structure indexed by maturity rather than time fits naturally on this chart.
+- **Volatility term structure**: Implied vol by tenor reads the same way as yield by tenor.
+- **Cross-section snapshots**: Anything indexed by "horizon" (forward returns, expected payout) where comparing across maturities matters more than time evolution.
+
+## Examples
+
+### A basic yield curve
+
+`tvl.data.yields()` is an 11-tenor snapshot with columns `Tenor` and `Yield`. `Tenor` is the maturity **in months** (3, 6, 12, 24, ... 480), the unit LWC's yield-curve axis expects. Pass `maturity="Tenor"` and `value="Yield"`, and set `start_time_range=480` so the initial viewport actually contains the long-end tenors (the LWC default is 120 months, which would clip everything past 10y to the right margin).
+
+```python order=yield_curve,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.yields()
+
+yield_curve = tvl.yield_curve(
+    data,
+    maturity="Tenor",
+    value="Yield",
+    start_time_range=480,
+)
+```
+
+A single line traces the data from the short end (3m) to the long end (40y). The x-axis tick formatter renders the tenor values as `Xm` / `Xy` durations.
+
+### Switch to an area rendering
+
+`series_type="area"` swaps the line for a filled area. Pair it with `top_color`/`bottom_color` for a custom gradient, or leave the colors at their defaults.
+
+```python order=yield_curve,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.yields()
+
+yield_curve = tvl.yield_curve(
+    data,
+    maturity="Tenor",
+    value="Yield",
+    series_type="area",
+    top_color="rgba(31, 119, 180, 0.45)",
+    bottom_color="rgba(31, 119, 180, 0.0)",
+    line_color="#1f77b4",
+    start_time_range=480,
+)
+```
+
+The gradient fades down to transparent so the area looks like a "rising tide" shape. Color kwargs accept a Deephaven theme color (e.g. `"positive"`, `"accent-300"`), a hex code, a named CSS color, or an `rgb()`/`rgba()` string. Theme colors adapt automatically when the user switches themes.
+
+### Customize color and width (line mode)
+
+In line mode, `color` is the line CSS color and `line_width` is the integer pixel width (1-4, default 3). `title` is the legend label.
+
+```python order=yield_curve,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.yields()
+
+yield_curve = tvl.yield_curve(
+    data,
+    maturity="Tenor",
+    value="Yield",
+    color="#d62728",
+    line_width=1,
+    title="UST par yield",
+    start_time_range=480,
+)
+```
+
+The line is now red, one pixel wide, with a custom legend entry.
+
+### Tune the maturity axis
+
+Three integer parameters control the maturity axis. They are all expressed in *months*, regardless of how your `maturity` column is labeled.
+
+- `base_resolution`: the number of months represented by one base unit on the axis. Increase it to widen tick spacing on long-dated curves.
+- `minimum_time_range`: the smallest axis span the chart will ever zoom to (in months). Stops zoom from going below this.
+- `start_time_range`: the initial visible span in months.
+
+```python order=yield_curve,data
+import deephaven.plot.tradingview_lightweight as tvl
+data = tvl.data.yields()
+
+yield_curve = tvl.yield_curve(
+    data,
+    maturity="Tenor",
+    value="Yield",
+    base_resolution=12,
+    minimum_time_range=24,
+    start_time_range=480,
+)
+```
+
+The chart opens showing 40 years of curve and won't zoom in past a 2-year window.
+
+## API Reference
+
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.tradingview_lightweight.yield_curve
+```
diff --git a/plugins/tradingview-lightweight/make_docs.py b/plugins/tradingview-lightweight/make_docs.py
new file mode 100644
index 000000000..cd5f144ac
--- /dev/null
+++ b/plugins/tradingview-lightweight/make_docs.py
@@ -0,0 +1,18 @@
+from __future__ import annotations
+
+import os, sys
+
+# Get the directory of the current file
+current_dir = os.path.dirname(os.path.abspath(__file__))
+
+# Construct the path to the utilities module
+utilities_path = os.path.join(current_dir, "../../sphinx_ext/")
+sys.path.append(utilities_path)
+
+from make_docs_utilities import build_documents, pushd
+
+with pushd(__file__):
+    code = build_documents()
+
+if code != 0:
+    sys.exit(1)
diff --git a/plugins/tradingview-lightweight/pyproject.toml b/plugins/tradingview-lightweight/pyproject.toml
new file mode 100644
index 000000000..54e217464
--- /dev/null
+++ b/plugins/tradingview-lightweight/pyproject.toml
@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools>=43.0.0", "wheel", "deephaven-plugin-packaging"]
+build-backend = "setuptools.build_meta"
diff --git a/plugins/tradingview-lightweight/setup.cfg b/plugins/tradingview-lightweight/setup.cfg
new file mode 100644
index 000000000..d7849c22b
--- /dev/null
+++ b/plugins/tradingview-lightweight/setup.cfg
@@ -0,0 +1,37 @@
+[metadata]
+name = deephaven-plugin-tradingview-lightweight
+description = Deephaven TradingView Lightweight Charts Plugin
+long_description = file: README.md
+long_description_content_type = text/markdown
+version = 0.1.0.dev0
+url = https://github.com/deephaven/deephaven-plugins
+project_urls =
+    Source Code = https://github.com/deephaven/deephaven-plugins
+    Bug Tracker = https://github.com/deephaven/deephaven-plugins/issues
+classifiers =
+    Programming Language :: Python :: 3
+    License :: OSI Approved :: Apache Software License
+    Operating System :: OS Independent
+    Environment :: Plugins
+    Topic :: Scientific/Engineering :: Visualization
+    Development Status :: 3 - Alpha
+keywords = deephaven, plugin, tradingview, lightweight-charts, financial
+author = Deephaven Data Labs LLC
+platforms = any
+
+[options]
+package_dir=
+    =src
+packages=find_namespace:
+install_requires =
+    deephaven-core>=0.41.1
+    deephaven-plugin>=0.6.0
+    deephaven-plugin-utilities>=0.0.2
+include_package_data = True
+
+[options.packages.find]
+where=src
+
+[options.entry_points]
+deephaven.plugin =
+    registration_cls = deephaven.plot.tradingview_lightweight._register:TvlRegistration
diff --git a/plugins/tradingview-lightweight/setup.py b/plugins/tradingview-lightweight/setup.py
new file mode 100644
index 000000000..1e324d509
--- /dev/null
+++ b/plugins/tradingview-lightweight/setup.py
@@ -0,0 +1,10 @@
+from setuptools import setup
+import os
+from deephaven.plugin.packaging import package_js
+
+js_dir = "src/js/"
+dest_dir = os.path.join("src/deephaven/plot/tradingview_lightweight/_js")
+
+package_js(js_dir, dest_dir)
+
+setup(package_data={"deephaven.plot.tradingview_lightweight._js": ["**"]})
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/__init__.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/__init__.py
new file mode 100644
index 000000000..ac1d157fe
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/__init__.py
@@ -0,0 +1,144 @@
+"""TradingView Lightweight Charts plugin for Deephaven."""
+
+from __future__ import annotations
+
+import json
+from typing import Any
+
+from deephaven.plugin.object_type import BidirectionalObjectType, MessageStream
+
+from .chart import (
+    TvlChart,
+    chart,
+    candlestick,
+    line,
+    area,
+    bar,
+    baseline,
+    histogram,
+    yield_curve,
+    options_chart,
+    custom_numeric,
+)
+from .markers import (
+    Marker,
+    PriceLine,
+    MarkerSpec,
+    marker,
+    price_line,
+    markers_from_table,
+    up_down_markers,
+)
+from .options import (
+    ChartType,
+    ColorSpace,
+    ColorType,
+    PriceFormat,
+    PriceFormatter,
+    TickmarksPriceFormatter,
+    PercentageFormatter,
+    TickmarksPercentageFormatter,
+    PrecomputeConflationPriority,
+    LineStyle,
+    LineType,
+    LineWidth,
+    CrosshairMode,
+    HorzAlign,
+    PriceScaleMode,
+    MarkerShape,
+    MarkerPosition,
+    LastPriceAnimationMode,
+    MarkerSign,
+    MismatchDirection,
+    PriceLineSource,
+    TickMarkType,
+    TrackingModeExitMode,
+    VertAlign,
+    WatermarkLine,
+    watermark_line,
+)
+from ._types import BusinessDay, business_day
+from .utils import is_business_day, is_utc_timestamp
+from .communication.connection import TvlChartConnection
+from . import data
+
+NAME = "deephaven.plot.tradingview_lightweight.TvlChart"
+
+
+class TvlChartType(BidirectionalObjectType):
+    """TvlChartType for plugin registration."""
+
+    @property
+    def name(self) -> str:
+        return NAME
+
+    def is_type(self, obj: Any) -> bool:
+        return isinstance(obj, TvlChart)
+
+    def create_client_connection(
+        self, obj: TvlChart, connection: MessageStream
+    ) -> MessageStream:
+        chart_connection = TvlChartConnection(obj, connection)
+        initial_message = json.dumps({"type": "RETRIEVE"}).encode()
+        payload, references = chart_connection.on_data(initial_message, [])
+        connection.on_data(payload, references)
+        return chart_connection
+
+
+__all__ = [
+    # Core
+    "TvlChart",
+    # Chart creation
+    "chart",
+    "candlestick",
+    "line",
+    "area",
+    "bar",
+    "baseline",
+    "histogram",
+    "yield_curve",
+    "options_chart",
+    "custom_numeric",
+    # Annotations
+    "Marker",
+    "PriceLine",
+    "MarkerSpec",
+    "marker",
+    "price_line",
+    "markers_from_table",
+    "up_down_markers",
+    # Types
+    "BusinessDay",
+    "business_day",
+    "ChartType",
+    "ColorSpace",
+    "ColorType",
+    "PriceFormat",
+    "PriceFormatter",
+    "TickmarksPriceFormatter",
+    "PercentageFormatter",
+    "TickmarksPercentageFormatter",
+    "PrecomputeConflationPriority",
+    "LineStyle",
+    "LineType",
+    "LineWidth",
+    "CrosshairMode",
+    "HorzAlign",
+    "PriceScaleMode",
+    "MarkerShape",
+    "MarkerPosition",
+    "LastPriceAnimationMode",
+    "MarkerSign",
+    "MismatchDirection",
+    "PriceLineSource",
+    "TickMarkType",
+    "TrackingModeExitMode",
+    "VertAlign",
+    "WatermarkLine",
+    "watermark_line",
+    # Utility functions
+    "is_business_day",
+    "is_utc_timestamp",
+    # Submodules
+    "data",
+]
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_colors.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_colors.py
new file mode 100644
index 000000000..59284e806
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_colors.py
@@ -0,0 +1,240 @@
+"""TVL color type aliases.
+
+The ``DeephavenColor`` Literal is copied verbatim from
+``deephaven.ui.types.types`` (the ``Color``/``DeephavenColor`` aliases used
+by ``deephaven.ui.view`` and friends). Copied rather than imported so this
+plugin has no runtime dependency on the ``deephaven.ui`` package; if the
+upstream list grows, resync this file.
+
+Last sync: 2026-06-03.
+"""
+
+from __future__ import annotations
+
+from typing import Literal, Union
+
+
+DeephavenColor = Literal[
+    "gray-50",
+    "gray-75",
+    "gray-100",
+    "gray-200",
+    "gray-300",
+    "gray-400",
+    "gray-500",
+    "gray-600",
+    "gray-700",
+    "gray-800",
+    "gray-900",
+    "red-100",
+    "red-200",
+    "red-300",
+    "red-400",
+    "red-500",
+    "red-600",
+    "red-700",
+    "red-800",
+    "red-900",
+    "red-1000",
+    "red-1100",
+    "red-1200",
+    "red-1300",
+    "red-1400",
+    "orange-100",
+    "orange-200",
+    "orange-300",
+    "orange-400",
+    "orange-500",
+    "orange-600",
+    "orange-700",
+    "orange-800",
+    "orange-900",
+    "orange-1000",
+    "orange-1100",
+    "orange-1200",
+    "orange-1300",
+    "orange-1400",
+    "yellow-100",
+    "yellow-200",
+    "yellow-300",
+    "yellow-400",
+    "yellow-500",
+    "yellow-600",
+    "yellow-700",
+    "yellow-800",
+    "yellow-900",
+    "yellow-1000",
+    "yellow-1100",
+    "yellow-1200",
+    "yellow-1300",
+    "yellow-1400",
+    "chartreuse-100",
+    "chartreuse-200",
+    "chartreuse-300",
+    "chartreuse-400",
+    "chartreuse-500",
+    "chartreuse-600",
+    "chartreuse-700",
+    "chartreuse-800",
+    "chartreuse-900",
+    "chartreuse-1000",
+    "chartreuse-1100",
+    "chartreuse-1200",
+    "chartreuse-1300",
+    "chartreuse-1400",
+    "celery-100",
+    "celery-200",
+    "celery-300",
+    "celery-400",
+    "celery-500",
+    "celery-600",
+    "celery-700",
+    "celery-800",
+    "celery-900",
+    "celery-1000",
+    "celery-1100",
+    "celery-1200",
+    "celery-1300",
+    "celery-1400",
+    "green-100",
+    "green-200",
+    "green-300",
+    "green-400",
+    "green-500",
+    "green-600",
+    "green-700",
+    "green-800",
+    "green-900",
+    "green-1000",
+    "green-1100",
+    "green-1200",
+    "green-1300",
+    "green-1400",
+    "seafoam-100",
+    "seafoam-200",
+    "seafoam-300",
+    "seafoam-400",
+    "seafoam-500",
+    "seafoam-600",
+    "seafoam-700",
+    "seafoam-800",
+    "seafoam-900",
+    "seafoam-1000",
+    "seafoam-1100",
+    "seafoam-1200",
+    "seafoam-1300",
+    "seafoam-1400",
+    "cyan-100",
+    "cyan-200",
+    "cyan-300",
+    "cyan-400",
+    "cyan-500",
+    "cyan-600",
+    "cyan-700",
+    "cyan-800",
+    "cyan-900",
+    "cyan-1000",
+    "cyan-1100",
+    "cyan-1200",
+    "cyan-1300",
+    "cyan-1400",
+    "blue-100",
+    "blue-200",
+    "blue-300",
+    "blue-400",
+    "blue-500",
+    "blue-600",
+    "blue-700",
+    "blue-800",
+    "blue-900",
+    "blue-1000",
+    "blue-1100",
+    "blue-1200",
+    "blue-1300",
+    "blue-1400",
+    "indigo-100",
+    "indigo-200",
+    "indigo-300",
+    "indigo-400",
+    "indigo-500",
+    "indigo-600",
+    "indigo-700",
+    "indigo-800",
+    "indigo-900",
+    "indigo-1000",
+    "indigo-1100",
+    "indigo-1200",
+    "indigo-1300",
+    "indigo-1400",
+    "purple-100",
+    "purple-200",
+    "purple-300",
+    "purple-400",
+    "purple-500",
+    "purple-600",
+    "purple-700",
+    "purple-800",
+    "purple-900",
+    "purple-1000",
+    "purple-1100",
+    "purple-1200",
+    "purple-1300",
+    "purple-1400",
+    "fuchsia-100",
+    "fuchsia-200",
+    "fuchsia-300",
+    "fuchsia-400",
+    "fuchsia-500",
+    "fuchsia-600",
+    "fuchsia-700",
+    "fuchsia-800",
+    "fuchsia-900",
+    "fuchsia-1000",
+    "fuchsia-1100",
+    "fuchsia-1200",
+    "fuchsia-1300",
+    "fuchsia-1400",
+    "magenta-100",
+    "magenta-200",
+    "magenta-300",
+    "magenta-400",
+    "magenta-500",
+    "magenta-600",
+    "magenta-700",
+    "magenta-800",
+    "magenta-900",
+    "magenta-1000",
+    "magenta-1100",
+    "magenta-1200",
+    "magenta-1300",
+    "magenta-1400",
+    "negative",
+    "notice",
+    "positive",
+    "info",
+    "accent",
+    "accent-100",
+    "accent-200",
+    "accent-300",
+    "accent-400",
+    "accent-500",
+    "accent-600",
+    "accent-700",
+    "accent-800",
+    "accent-900",
+    "accent-1000",
+    "accent-1100",
+    "accent-1200",
+    "accent-1300",
+    "accent-1400",
+    "bg",
+    "content-bg",
+    "subdued-content-bg",
+    "surface-bg",
+    "fg",
+]
+
+# A user-supplied color. Accepts a Deephaven theme color name from the
+# ``DeephavenColor`` Literal, or any CSS color string (hex, named CSS color,
+# ``rgb()`` / ``rgba()``).
+Color = Union[DeephavenColor, str]
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_js/package.json b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_js/package.json
new file mode 100644
index 000000000..27238f159
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_js/package.json
@@ -0,0 +1,74 @@
+{
+  "name": "@deephaven/js-plugin-tradingview-lightweight",
+  "version": "0.1.0",
+  "description": "Deephaven TradingView Lightweight Charts plugin",
+  "keywords": [
+    "Deephaven",
+    "plugin",
+    "deephaven-js-plugin",
+    "tradingview",
+    "lightweight-charts"
+  ],
+  "author": "Deephaven Data Labs LLC",
+  "license": "Apache-2.0",
+  "main": "dist/bundle/index.js",
+  "type": "module",
+  "exports": {
+    ".": {
+      "import": "./dist/index.js",
+      "require": "./dist/bundle/index.js",
+      "default": "./dist/bundle/index.js"
+    },
+    "./*.js": "./dist/*.js",
+    "./*": "./dist/*.js"
+  },
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/deephaven/deephaven-plugins"
+  },
+  "bugs": {
+    "url": "https://github.com/deephaven/deephaven-plugins/issues"
+  },
+  "homepage": "https://github.com/deephaven/deephaven-plugins",
+  "scripts": {
+    "start": "vite build --watch",
+    "build": "run-s build:*",
+    "build:transpile": "tsc",
+    "build:bundle": "vite build",
+    "test:e2e": "run-s build test:e2e:run",
+    "test:e2e:run": "playwright test -c e2e/playwright.config.ts",
+    "test:e2e:setup": "bash e2e/setup-venv.sh",
+    "update-dh-packages": "node ../../../../tools/update-dh-packages.mjs"
+  },
+  "devDependencies": {
+    "@deephaven/dashboard-core-plugins": "^0.85.42",
+    "@deephaven/jsapi-types": "^1.0.0-dev0.39.5",
+    "@deephaven/test-utils": "0.105.0",
+    "@types/react": "^17.0.2",
+    "react": "^17.0.2",
+    "react-dom": "^17.0.2",
+    "typescript": "^5.9.3"
+  },
+  "peerDependencies": {
+    "react": "^17.0.2",
+    "react-dom": "^17.0.2"
+  },
+  "dependencies": {
+    "@deephaven/components": "^1.2.0",
+    "@deephaven/dashboard": "^1.2.0",
+    "@deephaven/icons": "^1.2.0",
+    "@deephaven/jsapi-bootstrap": "1.2.0",
+    "@deephaven/log": "1.1.0",
+    "@deephaven/plugin": "^1.2.0",
+    "@deephaven/redux": "^1.2.0",
+    "@deephaven/utils": "^1.1.0",
+    "lightweight-charts": "^5.2.0",
+    "react-redux": "^7.2.9"
+  },
+  "publishConfig": {
+    "access": "public"
+  },
+  "files": [
+    "dist"
+  ]
+}
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_register.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_register.py
new file mode 100644
index 000000000..8921fbe15
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_register.py
@@ -0,0 +1,21 @@
+"""Plugin registration for TradingView Lightweight Charts."""
+
+from deephaven.plugin import Registration, Callback
+from deephaven.plugin.utilities import create_js_plugin, DheSafeCallbackWrapper
+
+PACKAGE_NAMESPACE = "deephaven.plot.tradingview_lightweight"
+JS_NAME = "_js"
+
+
+class TvlRegistration(Registration):
+    """Register the TvlChartType and a JsPlugin."""
+
+    @classmethod
+    def register_into(cls, callback: Callback) -> None:
+        from . import TvlChartType
+
+        callback = DheSafeCallbackWrapper(callback)
+        callback.register(TvlChartType)
+
+        js_plugin = create_js_plugin(PACKAGE_NAMESPACE, JS_NAME)
+        callback.register(js_plugin)
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_types.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_types.py
new file mode 100644
index 000000000..ef6f67a43
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/_types.py
@@ -0,0 +1,58 @@
+"""Internal type aliases."""
+
+from __future__ import annotations
+
+from typing import Any, TypedDict, Union
+
+try:
+    from deephaven.table import Table, PartitionedTable
+
+    TableLike = Union[Table, PartitionedTable]
+except ImportError:
+    TableLike = Any
+
+
+class BusinessDay(TypedDict):
+    """A date specified as a business day with year, month, and day components.
+
+    Used as a ``time`` value in series data for TradingView Lightweight Charts.
+    BusinessDay keys are used instead of UNIX timestamps to chart data that
+    excludes non-trading days (weekends, holidays) — the chart renders them
+    with equal bar spacing regardless of calendar gaps.
+
+    Example::
+
+        from deephaven.plot.tradingview_lightweight import business_day
+        row = {"time": business_day(2024, 1, 15), "value": 150.25}
+
+    See: https://tradingview.github.io/lightweight-charts/docs/api#businessday
+    """
+
+    year: int
+    month: int
+    day: int
+
+
+def business_day(year: int, month: int, day: int) -> BusinessDay:
+    """Create a BusinessDay dict for use as a ``time`` value in series data.
+
+    Args:
+        year: Four-digit year (e.g. 2024).
+        month: Month number, 1-12.
+        day: Day of month, 1-31.
+
+    Returns:
+        A dict ``{"year": year, "month": month, "day": day}`` suitable for
+        use as the ``time`` field in TradingView Lightweight Charts data rows.
+
+    Example::
+
+        from deephaven.plot.tradingview_lightweight import business_day
+
+        data = [
+            {"time": business_day(2024, 1, 15), "value": 150.25},
+            {"time": business_day(2024, 1, 16), "value": 152.10},
+            {"time": business_day(2024, 1, 17), "value": 149.80},
+        ]
+    """
+    return BusinessDay(year=year, month=month, day=day)
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/auto_bin.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/auto_bin.py
new file mode 100644
index 000000000..97e1e28b3
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/auto_bin.py
@@ -0,0 +1,410 @@
+"""Server-side auto time-bin aggregation for Histogram, Candlestick, and Bar series.
+
+Histogram / OHLC charts cannot be downsampled by min/max-per-bin (the JS-side
+``runChartDownsample`` path used for Line / Area / Baseline). For raw tick
+input the natural primitive is server-side time-bin aggregation:
+
+    table.update_view(["Bin = upperBin(time, w)"])
+         .agg_by([sum(value)], by=["Bin"])
+
+Bin widths are chosen automatically from the visible time range and snapped to
+"nice" durations. On zoom, the listener swaps in a finer-grained aggregation.
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+from typing import Any, Optional
+
+try:
+    from deephaven import agg, merge as dh_merge
+except ImportError:  # test envs without DH server
+    agg = None  # type: ignore[assignment]
+    dh_merge = None  # type: ignore[assignment]
+
+logger = logging.getLogger(__name__)
+
+# Approximate pixels per bar at "fat, visually distinct" density.
+# Used to derive target_bins from the chart's pixel width: target_bins = width_px / BAR_PX.
+#
+# LWC v5's histogram bar width is `round(barSpacing) - 1`, plus a secondary
+# adjustment loop that shrinks bars by 1 when accumulated rounding pushes
+# neighbors closer than expected. In practice barSpacing ~5-6 yields bars
+# in the 2-3 px range; targeting 8 px per bar keeps the rendered width
+# comfortably above 4 across panel sizes after the snap-to-nice-duration
+# rounding in nice_bin_width().
+BAR_PX = 8
+
+# Hard floor on bar pixel width. The client rounds widthPx up to the nearest
+# 1000 for engine cache friendliness, so the rounded width can overshoot the
+# actual chart by up to ~1000 px. Clamping target_bins by
+# actualWidthPx / MIN_BAR_PX guarantees bars stay above the visible-bar
+# threshold even with that overshoot.
+MIN_BAR_PX = 5
+
+# Default chart width assumed when widthPx isn't available (e.g., the initial
+# RETRIEVE that runs before the client tells us how big the chart is).
+DEFAULT_WIDTH_PX = 2000
+
+# Target number of bins when widthPx isn't supplied. Calibrated as
+# DEFAULT_WIDTH_PX / BAR_PX so the constant-default initial render and the
+# width-aware zoom path agree on what "fat bar" means.
+TARGET_BINS = DEFAULT_WIDTH_PX // BAR_PX
+
+# Re-aggregate when fewer than this many of the current bins are visible
+# (zoom-in trigger: bins are too coarse for the visible window).
+MIN_VISIBLE_BINS = 80
+
+# Re-aggregate when more than ``target_bins * MAX_VISIBLE_BINS_RATIO`` of the
+# current bins are visible (zoom-out trigger: bins are too fine — leaves
+# sub-pixel hash bars on the chart). The current width should give roughly
+# target_bins; allow up to 2x before coarsening.
+MAX_VISIBLE_BINS_RATIO = 2
+
+
+def target_bins_for_width(
+    width_px: Optional[int],
+    actual_width_px: Optional[int] = None,
+    fallback: int = TARGET_BINS,
+) -> int:
+    """Return target_bins for a chart pixel width.
+
+    ``width_px`` is the cache-friendly rounded width (rounded up to a 1000-px
+    bucket on the client). ``actual_width_px`` is the chart's real pixel width
+    when known; if supplied, the result is clamped so that
+    ``actual_width_px / target_bins >= MIN_BAR_PX`` — i.e. each bar is at
+    least ``MIN_BAR_PX`` pixels even when the rounded width overshoots.
+    """
+    if width_px is None or width_px <= 0:
+        return fallback
+    base = max(1, int(width_px) // BAR_PX)
+    if actual_width_px is not None and actual_width_px > 0:
+        floor = max(1, int(actual_width_px) // MIN_BAR_PX)
+        return min(base, floor)
+    return base
+
+
+NS_PER_US = 1_000
+NS_PER_MS = 1_000_000
+NS_PER_S = 1_000_000_000
+NS_PER_MIN = 60 * NS_PER_S
+NS_PER_HOUR = 60 * NS_PER_MIN
+NS_PER_DAY = 24 * NS_PER_HOUR
+
+# Allowed "nice" bin widths in nanoseconds. The first value >= the requested
+# width is selected.
+NICE_BIN_WIDTHS_NS: list[int] = [
+    1,  # 1 ns
+    100,  # 100 ns
+    NS_PER_US,  # 1 µs
+    100 * NS_PER_US,  # 100 µs
+    NS_PER_MS,  # 1 ms
+    10 * NS_PER_MS,  # 10 ms
+    100 * NS_PER_MS,  # 100 ms
+    NS_PER_S,  # 1 s
+    5 * NS_PER_S,  # 5 s
+    15 * NS_PER_S,  # 15 s
+    30 * NS_PER_S,  # 30 s
+    NS_PER_MIN,  # 1 m
+    5 * NS_PER_MIN,  # 5 m
+    15 * NS_PER_MIN,  # 15 m
+    30 * NS_PER_MIN,  # 30 m
+    NS_PER_HOUR,  # 1 h
+    4 * NS_PER_HOUR,  # 4 h
+    12 * NS_PER_HOUR,  # 12 h
+    NS_PER_DAY,  # 1 d
+    7 * NS_PER_DAY,  # 7 d
+    30 * NS_PER_DAY,  # 30 d
+    90 * NS_PER_DAY,  # 90 d (~1 quarter)
+    365 * NS_PER_DAY,  # 1 y
+]
+
+# Histogram aggregation modes.
+HIST_AGGS = {"sum", "count", "avg", "last"}
+
+
+def nice_bin_width(range_ns: int, target_bins: int = TARGET_BINS) -> int:
+    """Round ``range_ns / target_bins`` up to the nearest nice duration.
+
+    Always returns at least 1ns; never larger than the largest nice value.
+    """
+    if range_ns <= 0 or target_bins <= 0:
+        return 1
+    raw = max(1, range_ns // target_bins)
+    for w in NICE_BIN_WIDTHS_NS:
+        if w >= raw:
+            return w
+    return NICE_BIN_WIDTHS_NS[-1]
+
+
+# ISO 8601 duration: PnDTnHnMnS (we accept floats on seconds too)
+_ISO_DURATION_RE = re.compile(
+    r"^P(?:(?P<days>\d+)D)?(?:T(?:(?P<hours>\d+)H)?"
+    r"(?:(?P<minutes>\d+)M)?(?:(?P<seconds>\d+(?:\.\d+)?)S)?)?$"
+)
+
+
+def parse_bin_width(spec: Any) -> int:
+    """Parse an ISO 8601 duration string or numeric ns value to nanoseconds.
+
+    Examples: ``'PT1S'``, ``'PT5M'``, ``'PT1H'``, ``'P1D'``.
+    Numeric ints are passed through (mostly used by tests).
+    """
+    if spec is None:
+        raise ValueError("bin_width must be provided")
+    if isinstance(spec, int):
+        if spec <= 0:
+            raise ValueError(f"bin_width must be > 0, got {spec}")
+        return spec
+    if not isinstance(spec, str):
+        raise ValueError(
+            f"bin_width must be an ISO 8601 duration string or int ns, got {type(spec).__name__}"
+        )
+
+    m = _ISO_DURATION_RE.match(spec)
+    if not m or all(g is None for g in m.groupdict().values()):
+        raise ValueError(
+            f"Invalid ISO 8601 duration {spec!r}. Examples: 'PT1S', 'PT5M', 'PT1H', 'P1D'"
+        )
+    days = int(m.group("days") or 0)
+    hours = int(m.group("hours") or 0)
+    minutes = int(m.group("minutes") or 0)
+    seconds = float(m.group("seconds") or 0)
+    total_ns = (
+        days * NS_PER_DAY
+        + hours * NS_PER_HOUR
+        + minutes * NS_PER_MIN
+        + int(seconds * NS_PER_S)
+    )
+    if total_ns <= 0:
+        raise ValueError(f"bin_width must be > 0, got {spec!r}")
+    return total_ns
+
+
+def _epoch_ns_range(table: Any, time_col: str) -> Optional[tuple[int, int]]:
+    """Return (min_ns, max_ns) for ``time_col`` in ``table``, or None on failure."""
+    try:
+        size = table.size
+    except Exception:
+        return None
+    if size <= 0:
+        return None
+    if agg is None:
+        return None
+    try:
+        summary = table.view([f"__T = epochNanos({time_col})"]).agg_by(
+            [agg.min_("__Min=__T"), agg.max_("__Max=__T")]
+        )
+        snap = summary.snapshot()
+        col_min = snap.j_table.getColumnSource("__Min").get(0)
+        col_max = snap.j_table.getColumnSource("__Max").get(0)
+        return int(col_min), int(col_max)
+    except Exception:
+        logger.exception("failed to compute time range for %s", time_col)
+        return None
+
+
+def get_full_range_ns(table: Any, time_col: str) -> Optional[tuple[int, int]]:
+    """Public helper exposing the (min, max) epoch-ns range for a column."""
+    return _epoch_ns_range(table, time_col)
+
+
+def _common_aggregated_view(
+    raw: Any,
+    time_col: str,
+    bin_width_ns: int,
+    aggs: list[Any],
+    extra_value_cols: list[str],
+) -> Any:
+    """Bin by upperBin(time, w) and aggregate, restoring the time column name.
+
+    The output schema is ``[time_col, *extra_value_cols]`` so the renderer can
+    consume it without knowing it was aggregated.
+    """
+    binned = raw.update_view([f"__Bin = upperBin({time_col}, {bin_width_ns}L)"])
+    aggregated = binned.agg_by(aggs, by=["__Bin"])
+    # Replace __Bin with the original time column name and order columns
+    final = aggregated.update_view([f"{time_col} = __Bin"]).drop_columns(["__Bin"])
+    return final.view([time_col, *extra_value_cols]).sort(time_col)
+
+
+def _build_anchor(
+    raw: Any,
+    time_col: str,
+    slice_filter: str,
+    aggs: list[Any],
+    out_cols: list[str],
+    time_pos: str,
+) -> Any:
+    """Build a one-row anchor table from a filtered slice of ``raw``.
+
+    The anchor's value columns come from ``aggs`` collapsed across the slice
+    (no by argument). Its time column comes from ``agg.first(time_col)`` for
+    ``time_pos='first'`` or ``agg.last(time_col)`` for ``time_pos='last'``;
+    that's the leftmost / rightmost real row in the slice — which is at most
+    ``body_from`` for the head and at least ``body_to`` for the tail. LWC
+    only needs *something* at-or-before ``fullStart`` and at-or-after
+    ``fullEnd`` for ``fixLeftEdge`` / ``fixRightEdge`` to clamp, so this is
+    sufficient. If the slice is empty, ``agg_by`` returns 0 rows.
+    """
+    assert agg is not None, "_build_anchor requires deephaven.agg to be importable"
+    time_agg = agg.first(time_col) if time_pos == "first" else agg.last(time_col)
+    sliced = raw.where([slice_filter])
+    return sliced.agg_by([time_agg, *aggs]).view([time_col, *out_cols])
+
+
+def _build_scoped_view(
+    raw: Any,
+    time_col: str,
+    bin_width_ns: int,
+    aggs: list[Any],
+    out_cols: list[str],
+    body_range_ns: Optional[tuple[int, int]],
+    full_range_ns: Optional[tuple[int, int]],
+) -> Any:
+    """Build the aggregated view, scoped to ``body_range_ns`` if provided.
+
+    Returns:
+      - Full-source aggregation @ ``bin_width_ns`` (no anchors) when
+        ``body_range_ns`` is None or covers ``full_range_ns``.
+      - ``head + body + tail`` merged & sorted, where the head and tail are
+        single-row anchors flanking the body. The body covers the visible
+        window at fine bin width; anchors give LWC ``fixLeftEdge`` /
+        ``fixRightEdge`` something to clamp against.
+    """
+    full = (
+        body_range_ns is None
+        or full_range_ns is None
+        or (
+            body_range_ns[0] <= full_range_ns[0]
+            and body_range_ns[1] >= full_range_ns[1]
+        )
+    )
+    if full:
+        return _common_aggregated_view(raw, time_col, bin_width_ns, aggs, out_cols)
+
+    if dh_merge is None:
+        raise RuntimeError("deephaven.merge is not available in this environment")
+
+    body_from, body_to = body_range_ns  # type: ignore[misc]
+    body_raw = raw.where(
+        [
+            f"epochNanos({time_col}) >= {int(body_from)}L",
+            f"epochNanos({time_col}) <= {int(body_to)}L",
+        ]
+    )
+    body = _common_aggregated_view(body_raw, time_col, bin_width_ns, aggs, out_cols)
+    head = _build_anchor(
+        raw,
+        time_col,
+        f"epochNanos({time_col}) < {int(body_from)}L",
+        aggs,
+        out_cols,
+        time_pos="first",
+    )
+    tail = _build_anchor(
+        raw,
+        time_col,
+        f"epochNanos({time_col}) > {int(body_to)}L",
+        aggs,
+        out_cols,
+        time_pos="last",
+    )
+    return dh_merge([head, body, tail]).sort(time_col)
+
+
+def build_histogram_view(
+    raw: Any,
+    time_col: str,
+    value_col: str,
+    bin_width_ns: int,
+    agg_mode: str = "sum",
+    color_col: Optional[str] = None,
+    *,
+    body_range_ns: Optional[tuple[int, int]] = None,
+    full_range_ns: Optional[tuple[int, int]] = None,
+) -> Any:
+    """Build an aggregated histogram view over ``raw``.
+
+    ``agg_mode`` selects the per-bin reduction: sum (default), count, avg, last.
+
+    When ``body_range_ns`` is given and is strictly inside ``full_range_ns``,
+    the result is ``head_anchor + body + tail_anchor`` where the body is
+    binned at ``bin_width_ns`` over the visible window and the anchors are
+    single agg rows over the head / tail slices. Otherwise the full source
+    is binned at ``bin_width_ns``.
+    """
+    if agg_mode not in HIST_AGGS:
+        raise ValueError(f"agg must be one of {sorted(HIST_AGGS)}, got {agg_mode!r}")
+    if bin_width_ns <= 0:
+        raise ValueError(f"bin_width_ns must be > 0, got {bin_width_ns}")
+    if agg is None:
+        raise RuntimeError("deephaven.agg is not available in this environment")
+
+    if agg_mode == "sum":
+        aggs = [agg.sum_(f"{value_col}={value_col}")]
+    elif agg_mode == "count":
+        # Count rows in each bin and present as the value column.
+        aggs = [agg.count_(value_col)]
+    elif agg_mode == "avg":
+        aggs = [agg.avg(f"{value_col}={value_col}")]
+    else:  # last
+        aggs = [agg.last(f"{value_col}={value_col}")]
+
+    out_cols = [value_col]
+    if color_col is not None and color_col != value_col:
+        # Color reduces to last(color) per bin (decision §Edge cases)
+        aggs.append(agg.last(f"{color_col}={color_col}"))
+        out_cols.append(color_col)
+
+    return _build_scoped_view(
+        raw, time_col, bin_width_ns, aggs, out_cols, body_range_ns, full_range_ns
+    )
+
+
+def build_ohlc_view(
+    raw: Any,
+    time_col: str,
+    open_col: str,
+    high_col: str,
+    low_col: str,
+    close_col: str,
+    bin_width_ns: int,
+    *,
+    body_range_ns: Optional[tuple[int, int]] = None,
+    full_range_ns: Optional[tuple[int, int]] = None,
+) -> Any:
+    """Build an aggregated OHLC view: first(open), max(high), min(low), last(close).
+
+    When ``body_range_ns`` is strictly inside ``full_range_ns``, the result
+    is head + body + tail (anchored single-row slices flanking a body that
+    covers the visible window). Otherwise the full source is binned.
+    """
+    if bin_width_ns <= 0:
+        raise ValueError(f"bin_width_ns must be > 0, got {bin_width_ns}")
+
+    cols = {open_col, high_col, low_col, close_col}
+    if len(cols) != 4:
+        raise ValueError(
+            "OHLC requires four distinct columns; got "
+            f"open={open_col!r}, high={high_col!r}, low={low_col!r}, close={close_col!r}"
+        )
+    if agg is None:
+        raise RuntimeError("deephaven.agg is not available in this environment")
+
+    aggs = [
+        agg.first(f"{open_col}={open_col}"),
+        agg.max_(f"{high_col}={high_col}"),
+        agg.min_(f"{low_col}={low_col}"),
+        agg.last(f"{close_col}={close_col}"),
+    ]
+    return _build_scoped_view(
+        raw,
+        time_col,
+        bin_width_ns,
+        aggs,
+        [open_col, high_col, low_col, close_col],
+        body_range_ns,
+        full_range_ns,
+    )
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/chart.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/chart.py
new file mode 100644
index 000000000..5533d4bf6
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/chart.py
@@ -0,0 +1,2335 @@
+"""TvlChart class and chart creation functions."""
+
+from __future__ import annotations
+
+import inspect
+from typing import Any, Optional
+
+from .series import SeriesSpec
+from .markers import Marker, MarkerSpec, PriceLine
+from .events import (
+    PressEventCallable,
+    PRESS,
+    DOUBLE_PRESS,
+)
+
+# Optional imports — unavailable in test environments without a Deephaven server
+try:
+    from deephaven.liveness_scope import LivenessScope
+    from deephaven.table import Table
+except ImportError:
+    LivenessScope = None  # type: ignore[assignment,misc]
+    Table = None  # type: ignore[assignment,misc]
+from .options import (
+    ChartType,
+    ColorSpace,
+    CrosshairMode,
+    HorzAlign,
+    LastPriceAnimationMode,
+    LineStyle,
+    LineType,
+    LineWidth,
+    PrecomputeConflationPriority,
+    PriceFormat,
+    PriceLineSource,
+    PriceScaleId,
+    PriceScaleMode,
+    PriceFormatter,
+    TickmarksPriceFormatter,
+    PercentageFormatter,
+    TickmarksPercentageFormatter,
+    TrackingModeExitMode,
+    VertAlign,
+    WatermarkLine,
+    _watermark_line_to_dict,
+    CHART_TYPE_MAP,
+    CROSSHAIR_MODE_MAP,
+    LINE_STYLE_MAP,
+    PRICE_SCALE_MODE_MAP,
+    TRACKING_MODE_EXIT_MODE_MAP,
+)
+from . import series as series_module
+from ._colors import Color
+
+_YIELD_CURVE_SERIES_TYPES = {"Line", "Area"}
+
+# Per-type constructor kwargs that are chart-level (not series-factory args).
+# Excluded from the ``locals()`` dict forwarded to the ``*_series`` factory.
+_CHART_ONLY_KWARGS = {
+    "by",
+    "on_press",
+    "on_double_press",
+}
+
+
+def _filter_none(d: dict) -> dict:
+    return {k: v for k, v in d.items() if v is not None}
+
+
+def _wrap_as_chart(
+    spec: SeriesSpec,
+    by: Optional[str],
+    func_name: str,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> "TvlChart":
+    """Build a default-styled TvlChart wrapping a single SeriesSpec.
+
+    Used by the per-type unified constructors (``tvl.line``, ``tvl.area``,
+    etc.). When ``by`` is set, the source table is partitioned and the
+    resulting :class:`PartitionedTable` is stashed on the spec for the
+    JS partition-watcher. Press handlers are chart-level and forwarded to
+    the wrapping :class:`TvlChart` (they survive standalone display; when
+    the result is later passed to :func:`chart`, that call's handlers win).
+    """
+    _validate_series_columns(spec, func_name)
+    if by is not None:
+        _validate_by_column(spec.table, by, func_name)
+        spec.by = by
+        spec.partitioned_table = spec.table.partition_by([by])
+    return TvlChart(
+        series_list=[spec],
+        chart_options={},
+        on_press=on_press,
+        on_double_press=on_double_press,
+    )
+
+
+def _table_column_names(table: Any) -> Optional[list[str]]:
+    """Column names of ``table``, or ``None`` if they can't be determined.
+
+    Mock/typeless tables used in unit tests don't expose a real ``.columns``;
+    a ``MagicMock`` iterates to an empty list rather than raising. Either way
+    we can't validate, so return ``None`` (an empty result is treated the same
+    as unreadable) and let callers skip validation rather than reject every
+    column. A real Deephaven table always has at least one column.
+    """
+    try:
+        names = [c.name for c in table.columns]
+    except Exception:
+        return None
+    return names or None
+
+
+def _validate_by_column(table: Any, by: str, func: str) -> None:
+    """Raise a clear ValueError if ``by`` is not a column on ``table``.
+
+    Without this check ``table.partition_by([by])`` would still raise, but
+    with a much less actionable error wrapped in a Java exception. Surface
+    a Python-native error early so a typo in ``by="Symm"`` is obvious.
+    """
+    col_names = _table_column_names(table)
+    if col_names is None:
+        return
+    if by not in col_names:
+        raise ValueError(
+            f"{func}(by={by!r}) — column not found on table. "
+            f"Available columns: {col_names}"
+        )
+
+
+def _check_columns(table: Any, needed: Any, func: str, what: str) -> None:
+    """Raise ValueError if any name in ``needed`` is missing from ``table``.
+
+    ``what`` names the kind of column for the message (e.g. ``"column"``,
+    ``"price line column"``). Skips validation when the table's columns can't
+    be determined (mock/typeless tables — see :func:`_table_column_names`).
+    """
+    col_names = _table_column_names(table)
+    if col_names is None:
+        return
+    missing = sorted({c for c in needed if c not in col_names})
+    if missing:
+        raise ValueError(
+            f"{func} — {what}(s) not found on table: {missing}. "
+            f"Available columns: {col_names}"
+        )
+
+
+def _validate_series_columns(spec: SeriesSpec, func: str) -> None:
+    """Raise a clear ValueError if any column the series reads is missing.
+
+    Covers every prop that accepts a column name, so a typo like
+    ``value="Emaa"`` is surfaced as a Python-native error here — before the
+    figure is ever sent to the client — rather than silently rendering an
+    empty series (the unknown column is dropped client-side at subscribe time):
+
+    - the time / value / OHLC data channels and per-row color columns held in
+      ``column_mapping`` (validated against the series table);
+    - column-driven price lines (:attr:`PriceLine.column`, same table);
+    - table-driven markers (every column in :meth:`MarkerSpec.get_columns`,
+      validated against the marker spec's own table).
+    """
+    _check_columns(spec.table, spec.column_mapping.values(), func, "column")
+
+    if spec.price_lines:
+        pl_cols = [pl.column for pl in spec.price_lines if pl.column is not None]
+        _check_columns(spec.table, pl_cols, func, "price line column")
+
+    if spec.marker_spec is not None:
+        _check_columns(
+            spec.marker_spec.table,
+            spec.marker_spec.get_columns(),
+            func,
+            "marker column",
+        )
+
+
+class TvlChart:
+    """A TradingView Lightweight Chart.
+
+    Holds chart configuration and series specs.  When displayed in
+    Deephaven, the chart is serialized to JSON and rendered by the
+    TVL JS plugin.
+
+    Construct instances through :func:`chart` (or one of the
+    convenience helpers like :func:`candlestick`, :func:`line`,
+    :func:`area`) rather than calling this constructor directly.  The
+    constructor signature is considered semi-internal: it accepts the
+    already-resolved chart options dict and may change between
+    releases.
+
+    Args:
+        series_list: One or more :class:`SeriesSpec` instances to plot.
+        chart_options: Pre-resolved camelCase JS-shaped options dict
+            (the output of :func:`chart`'s argument processing).
+        pane_stretch_factors: Optional list of per-pane stretch
+            factors.  Length must match the highest ``pane`` index used
+            by any series + 1.
+        pane_preserve_empty: Optional list of booleans controlling
+            whether each pane is preserved even when empty.
+        chart_type: One of ``"standard"``, ``"yieldCurve"``,
+            ``"options"`` (camelCase TVL backend names).  Use
+            :func:`chart` to translate from the Pythonic
+            :data:`ChartType` aliases.
+    """
+
+    def __init__(
+        self,
+        series_list: list[SeriesSpec],
+        chart_options: dict,
+        pane_stretch_factors: Optional[list[float]] = None,
+        pane_preserve_empty: Optional[list[bool]] = None,
+        chart_type: str = "standard",
+        on_press: Optional[PressEventCallable] = None,
+        on_double_press: Optional[PressEventCallable] = None,
+    ):
+        self._series_list = series_list
+        self._chart_options = chart_options
+        self._pane_stretch_factors = pane_stretch_factors
+        self._pane_preserve_empty = pane_preserve_empty
+        self._chart_type = chart_type
+        self._on_press = on_press
+        self._on_double_press = on_double_press
+
+        # Liveness: manage refreshing tables so they survive GC
+        self._liveness_scope = None
+        if LivenessScope is not None:
+            self._liveness_scope = LivenessScope()
+            self._manage_tables()
+
+    def _manage_tables(self) -> None:
+        """Register refreshing tables with the liveness scope."""
+        if self._liveness_scope is None or Table is None:
+            return
+        for table in self.get_tables():
+            # Static tables must not be managed (causes errors later)
+            if isinstance(table, Table) and not table.is_refreshing:
+                continue
+            self._liveness_scope.manage(table)
+        # Per-series partitioned tables must also be managed.
+        for s in self._series_list:
+            if s.partitioned_table is not None:
+                self._liveness_scope.manage(s.partitioned_table)
+
+    @property
+    def partitioned_series(self) -> list[SeriesSpec]:
+        """Series in this chart that carry a partition (``by=``) template."""
+        return [s for s in self._series_list if s.by is not None]
+
+    def __del__(self) -> None:
+        if self._liveness_scope is not None:
+            self._liveness_scope.release()
+
+    @property
+    def series_list(self) -> list[SeriesSpec]:
+        return self._series_list
+
+    @property
+    def chart_options(self) -> dict:
+        return self._chart_options
+
+    @property
+    def pane_stretch_factors(self) -> Optional[list[float]]:
+        return self._pane_stretch_factors
+
+    @property
+    def pane_preserve_empty(self) -> Optional[list[bool]]:
+        return self._pane_preserve_empty
+
+    @property
+    def chart_type(self) -> str:
+        return self._chart_type
+
+    @property
+    def on_press(self) -> Optional[PressEventCallable]:
+        return self._on_press
+
+    @property
+    def on_double_press(self) -> Optional[PressEventCallable]:
+        return self._on_double_press
+
+    def enabled_handlers(self) -> list[str]:
+        """Handler ids that are wired, in advertise order.
+
+        Mirrors the ``enabledHandlers`` array emitted in :meth:`to_dict`;
+        the listener uses this to build its dispatch registry so the two
+        never drift apart.
+        """
+        handlers: list[str] = []
+        if self._on_press is not None:
+            handlers.append(PRESS)
+        if self._on_double_press is not None:
+            handlers.append(DOUBLE_PRESS)
+        return handlers
+
+    def get_tables(self) -> list[Any]:
+        """Return all unique Deephaven tables referenced by this chart's
+        series and marker specs.
+
+        Returns:
+            list[Any]: De-duplicated list of tables (order = first
+            occurrence in :attr:`series_list`).  Marker-spec tables
+            are appended after series tables.
+        """
+        seen = set()
+        tables = []
+        for s in self._series_list:
+            table_id = id(s.table)
+            if table_id not in seen:
+                seen.add(table_id)
+                tables.append(s.table)
+            if s.marker_spec is not None:
+                mt_id = id(s.marker_spec.table)
+                if mt_id not in seen:
+                    seen.add(mt_id)
+                    tables.append(s.marker_spec.table)
+        return tables
+
+    def to_dict(self, table_id_map: dict) -> dict:
+        """Serialize this chart to a dict suitable for JSON transport
+        to the JS plugin.
+
+        Args:
+            table_id_map: dict mapping Python ``id(table)`` to the
+                integer reference ID used by the wire protocol.
+
+        Returns:
+            dict: A JSON-serializable dict with keys ``chartType``,
+            ``chartOptions``, ``series``, and (when set)
+            ``paneStretchFactors``, ``panePreserveEmpty``. Each series
+            entry may carry a ``"partition"`` block when its ``by``
+            field is set.
+        """
+        series_dicts = []
+        for i, s in enumerate(self._series_list):
+            tid = table_id_map[id(s.table)]
+            marker_tid = None
+            if s.marker_spec is not None:
+                marker_tid = table_id_map[id(s.marker_spec.table)]
+            series_dicts.append(
+                s.to_dict(f"series_{i}", tid, marker_table_id=marker_tid)
+            )
+
+        result = {
+            "chartType": self._chart_type,
+            "chartOptions": self._chart_options,
+            "series": series_dicts,
+        }
+        if self._pane_stretch_factors is not None:
+            result["paneStretchFactors"] = self._pane_stretch_factors
+        if self._pane_preserve_empty is not None:
+            result["panePreserveEmpty"] = self._pane_preserve_empty
+        enabled = self.enabled_handlers()
+        if enabled:
+            result["enabledHandlers"] = enabled
+        return result
+
+
+def chart(
+    *sources: "TvlChart | SeriesSpec",
+    # Chart type
+    chart_type: Optional[ChartType] = None,
+    # Yield curve options (only for chart_type="yield_curve")
+    base_resolution: Optional[int] = None,
+    minimum_time_range: Optional[int] = None,
+    start_time_range: Optional[int] = None,
+    # Layout
+    background_color: Optional[Color] = None,
+    background_top_color: Optional[Color] = None,
+    background_bottom_color: Optional[Color] = None,
+    text_color: Optional[Color] = None,
+    font_size: Optional[int] = None,
+    # fontFamily is intentionally omitted — we do not allow font customization.
+    attribution_logo: Optional[bool] = None,
+    color_space: Optional[ColorSpace] = None,
+    hovered_series_on_top: Optional[bool] = None,
+    default_visible_price_scale_id: Optional[PriceScaleId] = None,
+    # Grid
+    vert_lines_visible: Optional[bool] = None,
+    vert_lines_color: Optional[Color] = None,
+    vert_lines_style: Optional[LineStyle] = None,
+    horz_lines_visible: Optional[bool] = None,
+    horz_lines_color: Optional[Color] = None,
+    horz_lines_style: Optional[LineStyle] = None,
+    # Crosshair
+    crosshair_mode: Optional[CrosshairMode] = None,
+    crosshair_vert_line_width: Optional[LineWidth] = None,
+    crosshair_vert_line_color: Optional[Color] = None,
+    crosshair_vert_line_style: Optional[LineStyle] = None,
+    crosshair_vert_line_visible: Optional[bool] = None,
+    crosshair_vert_line_label_visible: Optional[bool] = None,
+    crosshair_vert_line_label_background_color: Optional[Color] = None,
+    crosshair_horz_line_width: Optional[LineWidth] = None,
+    crosshair_horz_line_color: Optional[Color] = None,
+    crosshair_horz_line_style: Optional[LineStyle] = None,
+    crosshair_horz_line_visible: Optional[bool] = None,
+    crosshair_horz_line_label_visible: Optional[bool] = None,
+    crosshair_horz_line_label_background_color: Optional[Color] = None,
+    crosshair_do_not_snap_to_hidden_series: Optional[bool] = None,
+    # Right price scale
+    right_price_scale_visible: Optional[bool] = None,
+    right_price_scale_border_visible: Optional[bool] = None,
+    right_price_scale_border_color: Optional[Color] = None,
+    right_price_scale_auto_scale: Optional[bool] = None,
+    right_price_scale_mode: Optional[PriceScaleMode] = None,
+    right_price_scale_invert_scale: Optional[bool] = None,
+    right_price_scale_align_labels: Optional[bool] = None,
+    right_price_scale_text_color: Optional[Color] = None,
+    right_price_scale_entire_text_only: Optional[bool] = None,
+    right_price_scale_ticks_visible: Optional[bool] = None,
+    right_price_scale_minimum_width: Optional[int] = None,
+    right_price_scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    right_price_scale_tick_mark_density: Optional[float] = None,
+    right_price_scale_margin_top: Optional[float] = None,
+    right_price_scale_margin_bottom: Optional[float] = None,
+    # Left price scale
+    left_price_scale_visible: Optional[bool] = None,
+    left_price_scale_border_visible: Optional[bool] = None,
+    left_price_scale_border_color: Optional[Color] = None,
+    left_price_scale_auto_scale: Optional[bool] = None,
+    left_price_scale_mode: Optional[PriceScaleMode] = None,
+    left_price_scale_invert_scale: Optional[bool] = None,
+    left_price_scale_align_labels: Optional[bool] = None,
+    left_price_scale_text_color: Optional[Color] = None,
+    left_price_scale_entire_text_only: Optional[bool] = None,
+    left_price_scale_ticks_visible: Optional[bool] = None,
+    left_price_scale_minimum_width: Optional[int] = None,
+    left_price_scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    left_price_scale_tick_mark_density: Optional[float] = None,
+    left_price_scale_margin_top: Optional[float] = None,
+    left_price_scale_margin_bottom: Optional[float] = None,
+    # Overlay price scale defaults
+    overlay_price_scale_border_visible: Optional[bool] = None,
+    overlay_price_scale_ticks_visible: Optional[bool] = None,
+    overlay_price_scale_minimum_width: Optional[int] = None,
+    overlay_price_scale_margin_top: Optional[float] = None,
+    overlay_price_scale_margin_bottom: Optional[float] = None,
+    overlay_price_scale_auto_scale: Optional[bool] = None,
+    overlay_price_scale_mode: Optional[PriceScaleMode] = None,
+    overlay_price_scale_invert_scale: Optional[bool] = None,
+    overlay_price_scale_align_labels: Optional[bool] = None,
+    overlay_price_scale_border_color: Optional[Color] = None,
+    overlay_price_scale_text_color: Optional[Color] = None,
+    overlay_price_scale_entire_text_only: Optional[bool] = None,
+    overlay_price_scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    overlay_price_scale_tick_mark_density: Optional[float] = None,
+    # Time scale
+    time_visible: Optional[bool] = None,
+    seconds_visible: Optional[bool] = None,
+    time_scale_border_visible: Optional[bool] = None,
+    time_scale_border_color: Optional[Color] = None,
+    right_offset: Optional[int] = None,
+    right_offset_pixels: Optional[int] = None,
+    bar_spacing: Optional[float] = None,
+    min_bar_spacing: Optional[float] = None,
+    max_bar_spacing: Optional[float] = None,
+    fix_left_edge: Optional[bool] = None,
+    fix_right_edge: Optional[bool] = None,
+    lock_visible_time_range_on_resize: Optional[bool] = None,
+    right_bar_stays_on_scroll: Optional[bool] = None,
+    shift_visible_range_on_new_bar: Optional[bool] = None,
+    allow_shift_visible_range_on_whitespace_replacement: Optional[bool] = None,
+    time_scale_ticks_visible: Optional[bool] = None,
+    tick_mark_max_character_length: Optional[int] = None,
+    uniform_distribution: Optional[bool] = None,
+    time_scale_minimum_height: Optional[int] = None,
+    allow_bold_labels: Optional[bool] = None,
+    ignore_whitespace_indices: Optional[bool] = None,
+    enable_conflation: Optional[bool] = None,
+    conflation_threshold_factor: Optional[float] = None,
+    precompute_conflation_on_init: Optional[bool] = None,
+    precompute_conflation_priority: Optional[PrecomputeConflationPriority] = None,
+    time_scale_visible: Optional[bool] = None,
+    # Watermark — single-line shortcut (backwards-compatible)
+    watermark_text: Optional[str] = None,
+    watermark_color: Optional[Color] = None,
+    watermark_visible: Optional[bool] = None,
+    watermark_font_size: Optional[int] = None,
+    # watermark_font_family is intentionally omitted — we do not allow font customization.
+    watermark_font_style: Optional[str] = None,
+    watermark_line_height: Optional[float] = None,
+    watermark_horz_align: Optional[HorzAlign] = None,
+    watermark_vert_align: Optional[VertAlign] = None,
+    # Watermark — multi-line (mutually exclusive with single-line shortcut)
+    watermark_lines: Optional[list[WatermarkLine]] = None,
+    # Watermark — image (independent; can coexist with text watermark)
+    watermark_image_url: Optional[str] = None,
+    watermark_image_max_width: Optional[int] = None,
+    watermark_image_max_height: Optional[int] = None,
+    watermark_image_padding: Optional[int] = None,
+    watermark_image_alpha: Optional[float] = None,
+    watermark_image_visible: Optional[bool] = None,
+    # Scroll / Scale / Kinetic scroll
+    handle_scroll: Optional[bool] = None,
+    handle_scroll_mouse_wheel: Optional[bool] = None,
+    handle_scroll_pressed_mouse_move: Optional[bool] = None,
+    handle_scroll_horz_touch_drag: Optional[bool] = None,
+    handle_scroll_vert_touch_drag: Optional[bool] = None,
+    handle_scale: Optional[bool] = None,
+    handle_scale_mouse_wheel: Optional[bool] = None,
+    handle_scale_pinch: Optional[bool] = None,
+    handle_scale_axis_pressed_mouse_move: Optional[bool] = None,
+    handle_scale_axis_double_click_reset: Optional[bool] = None,
+    kinetic_scroll_touch: Optional[bool] = None,
+    kinetic_scroll_mouse: Optional[bool] = None,
+    # Localization
+    price_formatter: Optional[PriceFormatter] = None,
+    locale: Optional[str] = None,
+    tickmarks_price_formatter: Optional[TickmarksPriceFormatter] = None,
+    percentage_formatter: Optional[PercentageFormatter] = None,
+    tickmarks_percentage_formatter: Optional[TickmarksPercentageFormatter] = None,
+    # Panes
+    pane_separator_color: Optional[Color] = None,
+    pane_separator_hover_color: Optional[Color] = None,
+    pane_enable_resize: Optional[bool] = None,
+    pane_stretch_factors: Optional[list[float]] = None,
+    pane_preserve_empty: Optional[list[bool]] = None,
+    # Pane primitives (attachPrimitive / detachPrimitive) are not supported.
+    # They require callable JS objects with a draw() method that receives a
+    # canvas rendering context at browser render time. The Python plugin is a
+    # static configuration builder with no mechanism to express JS callables.
+    # Behavior / interaction
+    tracking_mode_exit_mode: Optional[TrackingModeExitMode] = None,
+    add_default_pane: Optional[bool] = None,
+    # Tracking tooltip (cursor-following overlay)
+    tooltip_visible: Optional[bool] = None,
+    tooltip_show_title: Optional[bool] = None,
+    tooltip_show_value: Optional[bool] = None,
+    tooltip_show_date: Optional[bool] = None,
+    tooltip_value_precision: Optional[int] = None,
+    # Event handlers
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Compose one or more series into a TradingView Lightweight chart.
+
+    This is the chart-composition entry point. Each positional input is
+    a :class:`TvlChart` returned by one of the per-type constructors
+    (:func:`candlestick`, :func:`line`, :func:`area`, :func:`bar`,
+    :func:`baseline`, :func:`histogram`). Their series are concatenated
+    in order, and the chart-level styling kwargs supplied here apply to
+    the composed chart. Any chart-level state on the input sources
+    (default options from standalone use) is discarded.
+
+    A single-series chart is most often created by the per-type
+    constructor directly (e.g. ``tvl.area(t, timestamp="T", value="V")``).
+    Reach for ``tvl.chart(...)`` when you want multi-series, multi-pane,
+    or fine-grained chart styling.
+
+    Args:
+        *sources (TvlChart): One or more per-type construction results
+            (e.g. ``tvl.candlestick(...)``, ``tvl.line(...)``). Their
+            series are merged in order; the pane each series targets
+            comes from its ``pane=`` argument (default pane 0).
+
+        chart_type (Optional[ChartType]): Selects the horizontal scale
+            backend.  See :data:`ChartType` for the allowed values
+            (``"standard"`` (default), ``"yield_curve"``, ``"options"``,
+            ``"custom_numeric"``).
+
+
+        base_resolution (Optional[int]): The base time resolution in
+            seconds — controls how the maturity axis is rendered.
+        minimum_time_range (Optional[int]): Minimum visible time range
+            in maturity units.
+        start_time_range (Optional[int]): Initial visible time range.
+
+
+        background_color (Optional[Color]): Solid background color as a
+            CSS color string (e.g. ``"#1a1a2e"``).  Mutually exclusive
+            with the gradient pair.
+        background_top_color (Optional[Color]): Top color for a vertical
+            gradient.  Must be set together with
+            ``background_bottom_color``.
+        background_bottom_color (Optional[Color]): Bottom color of the
+            gradient; pair with ``background_top_color``.
+        text_color (Optional[Color]): Default text color for axis labels
+            and tooltips.
+        font_size (Optional[int]): Base font size in pixels for axis
+            labels and tooltips.
+        attribution_logo (Optional[bool]): Show the TradingView
+            attribution logo (default ``True``).
+        color_space (Optional[ColorSpace]): Canvas color space — see
+            :data:`ColorSpace`.
+        hovered_series_on_top (Optional[bool]): Render the hovered
+            series above its siblings in the same pane (default
+            ``True``).
+        default_visible_price_scale_id (Optional[PriceScaleId]):
+            Default price scale (``"left"`` / ``"right"``) for series
+            that do not specify one.
+
+
+        vert_lines_visible (Optional[bool]): Show vertical gridlines.
+        vert_lines_color (Optional[Color]): Vertical gridline CSS color.
+        vert_lines_style (Optional[LineStyle]): Vertical gridline dash
+            pattern; see :data:`LineStyle`.
+        horz_lines_visible (Optional[bool]): Show horizontal gridlines.
+        horz_lines_color (Optional[Color]): Horizontal gridline CSS color.
+        horz_lines_style (Optional[LineStyle]): Horizontal gridline
+            dash pattern.
+
+
+        crosshair_mode (Optional[CrosshairMode]): Crosshair tracking
+            behavior; see :data:`CrosshairMode`.
+        crosshair_vert_line_width (Optional[LineWidth]): Width of the
+            vertical crosshair line in pixels.
+        crosshair_vert_line_color (Optional[Color]): Vertical crosshair
+            color.
+        crosshair_vert_line_style (Optional[LineStyle]): Vertical
+            crosshair dash pattern.
+        crosshair_vert_line_visible (Optional[bool]): Show the vertical
+            crosshair line.
+        crosshair_vert_line_label_visible (Optional[bool]): Show the
+            vertical crosshair's axis label.
+        crosshair_vert_line_label_background_color (Optional[Color]):
+            Vertical crosshair label background color.
+        crosshair_horz_line_width (Optional[LineWidth]): Width of the
+            horizontal crosshair line in pixels.
+        crosshair_horz_line_color (Optional[Color]): Horizontal crosshair
+            color.
+        crosshair_horz_line_style (Optional[LineStyle]): Horizontal
+            crosshair dash pattern.
+        crosshair_horz_line_visible (Optional[bool]): Show the
+            horizontal crosshair line.
+        crosshair_horz_line_label_visible (Optional[bool]): Show the
+            horizontal crosshair's axis label.
+        crosshair_horz_line_label_background_color (Optional[Color]):
+            Horizontal crosshair label background color.
+        crosshair_do_not_snap_to_hidden_series (Optional[bool]): When
+            ``True``, the crosshair skips hidden series in
+            magnet/snap modes.
+
+
+        right_price_scale_visible (Optional[bool]): Show the right
+            price scale.
+        right_price_scale_border_visible (Optional[bool]): Show the
+            scale border.
+        right_price_scale_border_color (Optional[Color]): Border color.
+        right_price_scale_auto_scale (Optional[bool]): Auto-fit the
+            scale to the visible data.
+        right_price_scale_mode (Optional[PriceScaleMode]): Scale mode;
+            see :data:`PriceScaleMode`.
+        right_price_scale_invert_scale (Optional[bool]): Invert the
+            scale (high values at bottom).
+        right_price_scale_align_labels (Optional[bool]): Align scale
+            labels with chart pixels.
+        right_price_scale_text_color (Optional[Color]): Scale label
+            color.
+        right_price_scale_entire_text_only (Optional[bool]): Render
+            only complete labels (avoid clipping).
+        right_price_scale_ticks_visible (Optional[bool]): Show tick
+            marks on the scale.
+        right_price_scale_minimum_width (Optional[int]): Minimum width
+            of the scale in pixels.
+        right_price_scale_ensure_edge_tick_marks_visible (Optional[bool]):
+            Force-render tick marks at the very top and bottom edges.
+        right_price_scale_tick_mark_density (Optional[float]):
+            Approximate tick density (default ``2.5``).
+        right_price_scale_margin_top (Optional[float]): Top margin as a
+            fraction (0–1).
+        right_price_scale_margin_bottom (Optional[float]): Bottom
+            margin as a fraction (0–1).
+
+
+        left_price_scale_visible (Optional[bool]): Show the left price
+            scale.
+        left_price_scale_border_visible (Optional[bool]): Show its
+            border.
+        left_price_scale_border_color (Optional[Color]): Border color.
+        left_price_scale_auto_scale (Optional[bool]): Auto-fit the
+            scale.
+        left_price_scale_mode (Optional[PriceScaleMode]): Scale mode.
+        left_price_scale_invert_scale (Optional[bool]): Invert the
+            scale.
+        left_price_scale_align_labels (Optional[bool]): Align labels
+            with pixels.
+        left_price_scale_text_color (Optional[Color]): Label color.
+        left_price_scale_entire_text_only (Optional[bool]): Only render
+            complete labels.
+        left_price_scale_ticks_visible (Optional[bool]): Show tick
+            marks.
+        left_price_scale_minimum_width (Optional[int]): Minimum width
+            in pixels.
+        left_price_scale_ensure_edge_tick_marks_visible (Optional[bool]):
+            Force-render edge tick marks.
+        left_price_scale_tick_mark_density (Optional[float]): Tick
+            density.
+        left_price_scale_margin_top (Optional[float]): Top margin
+            fraction.
+        left_price_scale_margin_bottom (Optional[float]): Bottom margin
+            fraction.
+
+        overlay_price_scale_border_visible (Optional[bool]): Show
+            overlay scale borders.
+        overlay_price_scale_ticks_visible (Optional[bool]): Show
+            overlay tick marks.
+        overlay_price_scale_minimum_width (Optional[int]): Minimum
+            overlay width.
+        overlay_price_scale_margin_top (Optional[float]): Top margin.
+        overlay_price_scale_margin_bottom (Optional[float]): Bottom
+            margin.
+        overlay_price_scale_auto_scale (Optional[bool]): Auto-fit.
+        overlay_price_scale_mode (Optional[PriceScaleMode]): Scale mode.
+        overlay_price_scale_invert_scale (Optional[bool]): Invert.
+        overlay_price_scale_align_labels (Optional[bool]): Align labels.
+        overlay_price_scale_border_color (Optional[Color]): Border color.
+        overlay_price_scale_text_color (Optional[Color]): Label color.
+        overlay_price_scale_entire_text_only (Optional[bool]): Only
+            complete labels.
+        overlay_price_scale_ensure_edge_tick_marks_visible (Optional[bool]):
+            Force edge ticks.
+        overlay_price_scale_tick_mark_density (Optional[float]): Tick
+            density.
+
+
+        time_visible (Optional[bool]): Show the time scale at the
+            bottom of the chart.
+        seconds_visible (Optional[bool]): Show seconds in time labels.
+        time_scale_border_visible (Optional[bool]): Show time scale
+            border.
+        time_scale_border_color (Optional[Color]): Border color.
+        right_offset (Optional[int]): Empty bars beyond the rightmost
+            data point.
+        right_offset_pixels (Optional[int]): Pixel offset of the right
+            edge.
+        bar_spacing (Optional[float]): Pixels between adjacent bars.
+        min_bar_spacing (Optional[float]): Minimum bar spacing
+            (zoom-in cap).
+        max_bar_spacing (Optional[float]): Maximum bar spacing
+            (zoom-out cap).
+        fix_left_edge (Optional[bool]): Prevent scrolling past the
+            leftmost data point.
+        fix_right_edge (Optional[bool]): Prevent scrolling past the
+            rightmost data point.
+        lock_visible_time_range_on_resize (Optional[bool]): Keep the
+            visible time range when the chart is resized.
+        right_bar_stays_on_scroll (Optional[bool]): Pin the rightmost
+            bar in view while scrolling.
+        shift_visible_range_on_new_bar (Optional[bool]): Auto-scroll
+            when a new bar is added.
+        allow_shift_visible_range_on_whitespace_replacement (Optional[bool]):
+            Shift when whitespace bars are replaced by real data.
+        time_scale_ticks_visible (Optional[bool]): Show tick marks on
+            the time scale.
+        tick_mark_max_character_length (Optional[int]): Maximum
+            character length of a tick label before truncation.
+        uniform_distribution (Optional[bool]): Force uniform bar
+            spacing regardless of timestamp gaps.
+        time_scale_minimum_height (Optional[int]): Minimum height of
+            the time scale area in pixels.
+        allow_bold_labels (Optional[bool]): Allow bold time labels.
+        ignore_whitespace_indices (Optional[bool]): Ignore whitespace
+            indices when computing visible logical range.
+        enable_conflation (Optional[bool]): Conflate sub-pixel data
+            points for performance.
+        conflation_threshold_factor (Optional[float]): Conflation
+            sensitivity multiplier.
+        precompute_conflation_on_init (Optional[bool]): Precompute
+            conflation on chart init.
+        precompute_conflation_priority (Optional[PrecomputeConflationPriority]):
+            Scheduling priority for precomputation; see
+            :data:`PrecomputeConflationPriority`.
+        time_scale_visible (Optional[bool]): Master visibility toggle
+            for the time scale.
+
+
+        watermark_text (Optional[str]): Text to display as a single
+            watermark line.  Mutually exclusive with ``watermark_lines``.
+        watermark_color (Optional[Color]): Watermark text color.
+        watermark_visible (Optional[bool]): Show the watermark.
+        watermark_font_size (Optional[int]): Font size in pixels.
+        watermark_font_style (Optional[str]): CSS font-style string
+            (e.g. ``"italic"``).
+        watermark_line_height (Optional[float]): Line height in pixels.
+        watermark_horz_align (Optional[HorzAlign]): Horizontal
+            alignment; see :data:`HorzAlign`.
+        watermark_vert_align (Optional[VertAlign]): Vertical alignment;
+            see :data:`VertAlign`.
+
+
+        watermark_lines (Optional[list[WatermarkLine]]): List of
+            :class:`WatermarkLine` instances, each with its own text
+            and per-line styling.  Mutually exclusive with the
+            single-line shortcut params.
+
+
+        watermark_image_url (Optional[str]): URL of an image to draw
+            as a watermark.
+        watermark_image_max_width (Optional[int]): Maximum image width
+            in pixels.
+        watermark_image_max_height (Optional[int]): Maximum image
+            height in pixels.
+        watermark_image_padding (Optional[int]): Padding around the
+            image in pixels.
+        watermark_image_alpha (Optional[float]): Image opacity (0–1).
+        watermark_image_visible (Optional[bool]): Show the image
+            watermark.
+
+
+        handle_scroll (Optional[bool]): Master toggle for all scroll
+            interactions.  When set, overrides the per-axis booleans.
+        handle_scroll_mouse_wheel (Optional[bool]): Allow mouse-wheel
+            scrolling.
+        handle_scroll_pressed_mouse_move (Optional[bool]): Allow
+            click-drag scrolling.
+        handle_scroll_horz_touch_drag (Optional[bool]): Allow
+            horizontal touch scrolling.
+        handle_scroll_vert_touch_drag (Optional[bool]): Allow vertical
+            touch scrolling.
+        handle_scale (Optional[bool]): Master toggle for all scale /
+            zoom interactions.
+        handle_scale_mouse_wheel (Optional[bool]): Allow zooming with
+            the mouse wheel.
+        handle_scale_pinch (Optional[bool]): Allow pinch-to-zoom on
+            touch devices.
+        handle_scale_axis_pressed_mouse_move (Optional[bool]): Allow
+            scaling by dragging an axis.
+        handle_scale_axis_double_click_reset (Optional[bool]): Reset
+            axis scale on double-click.
+        kinetic_scroll_touch (Optional[bool]): Enable kinetic scrolling
+            on touch devices.
+        kinetic_scroll_mouse (Optional[bool]): Enable kinetic scrolling
+            with the mouse.
+
+
+        price_formatter (Optional[PriceFormatter]): Price formatter
+            preset; see :data:`PriceFormatter`.
+        locale (Optional[str]): BCP 47 locale string for number
+            formatting (e.g. ``"en-US"``).
+        tickmarks_price_formatter (Optional[TickmarksPriceFormatter]):
+            Tick-label price formatter; see :data:`TickmarksPriceFormatter`.
+        percentage_formatter (Optional[PercentageFormatter]):
+            Crosshair percentage formatter; see :data:`PercentageFormatter`.
+        tickmarks_percentage_formatter (Optional[TickmarksPercentageFormatter]):
+            Tick-label percentage formatter; see
+            :data:`TickmarksPercentageFormatter`.
+
+
+        pane_separator_color (Optional[Color]): Color of the lines
+            between panes.
+        pane_separator_hover_color (Optional[Color]): Pane separator
+            color when hovered.
+        pane_enable_resize (Optional[bool]): Allow the user to resize
+            panes by dragging separators.
+        pane_stretch_factors (Optional[list[float]]): Relative stretch
+            factor per pane (longer list = more panes).
+        pane_preserve_empty (Optional[list[bool]]): Per-pane flag — if
+            ``True``, the pane is kept visible even when empty.
+
+
+        tracking_mode_exit_mode (Optional[TrackingModeExitMode]): When
+            the touch-device tracking mode exits; see
+            :data:`TrackingModeExitMode`.
+        add_default_pane (Optional[bool]): Add a default pane on
+            chart creation (default ``True``).  Set ``False`` for
+            advanced multi-pane setups that fully specify their own
+            panes.
+        tooltip_visible (Optional[bool]): Enable the tracking tooltip — a
+            small overlay that follows the cursor and shows the focused
+            series' title, value, and time. This is the master switch; the
+            other ``tooltip_*`` options only take effect when it is ``True``.
+            In a multi-series chart the tooltip shows a single focused
+            series: the one under the cursor (LWC hit test), falling back to
+            the series whose value is nearest the cursor. Its colors come
+            entirely from the active Deephaven theme (the title line is
+            tinted with the focused series' own color); there are no color
+            options.
+        tooltip_show_title (Optional[bool]): Show the series title line
+            (the series ``title``, or its id when untitled), tinted with the
+            series color. Default ``True``.
+        tooltip_show_value (Optional[bool]): Show the series value at the
+            cursor, formatted with the series' price format. For OHLC series
+            the close is shown. Default ``True``.
+        tooltip_show_date (Optional[bool]): Show the time/date line, matching
+            the chart's time-axis formatting. Default ``True``.
+        tooltip_value_precision (Optional[int]): Override the number of
+            decimal places for the value line. When unset, the series' own
+            price format is used.
+        on_press (Optional[PressEventCallable]): Server-side callback
+            invoked when the user presses (clicks) on the chart. Receives
+            a ``TvlPressEvent`` dict (or no argument). See
+            :mod:`deephaven.plot.tradingview_lightweight.events`.
+        on_double_press (Optional[PressEventCallable]): Server-side
+            callback invoked when the user double-presses on the chart.
+
+    Returns:
+        TvlChart: A chart object that can be displayed in Deephaven.
+
+    Note:
+        ``createChartEx`` with a custom ``horzScaleBehavior`` is not
+        supported from Python.  The named :data:`ChartType` values
+        cover all built-in horizontal-scale behaviors shipped with TVL
+        v5.  Users needing arbitrary custom horizontal scales must
+        ship a JS plugin extension.
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> c = tvl.chart(tvl.line(my_table, timestamp="Timestamp", value="Price"),
+        ...               background_color="#1a1a2e", time_visible=True)
+    """
+    # Resolve chart type
+    if chart_type is None:
+        resolved_type = "standard"
+    elif chart_type in CHART_TYPE_MAP:
+        resolved_type = CHART_TYPE_MAP[chart_type]
+    else:
+        valid = ", ".join(f'"{k}"' for k in CHART_TYPE_MAP)
+        raise ValueError(
+            f"Unknown chart_type {chart_type!r}. "
+            f"Valid values are: {valid}. "
+            f"Note: createChartEx with a custom horzScaleBehavior is not supported "
+            f"from Python — use a JS plugin extension for fully custom horizontal scales."
+        )
+
+    # Extract series from each source. Accept both TvlChart (the new
+    # public API) and bare SeriesSpec (for internal callers like
+    # yield_curve / options_chart / custom_numeric).
+    series_list: list[SeriesSpec] = []
+    for src in sources:
+        if isinstance(src, TvlChart):
+            # Specs from tvl.line()/area()/etc. were validated in _wrap_as_chart.
+            series_list.extend(src.series_list)
+        elif isinstance(src, SeriesSpec):
+            # Bare specs reach chart() from yield_curve/options_chart/
+            # custom_numeric — validate their columns here.
+            _validate_series_columns(src, f"chart() {src.series_type} series")
+            series_list.append(src)
+        else:
+            raise TypeError(
+                f"chart() inputs must be TvlChart instances (returned by "
+                f"tvl.line(), tvl.area(), etc.), got {type(src).__name__}"
+            )
+
+    # Validate yield curve series constraints
+    if resolved_type == "yieldCurve":
+        for s in series_list:
+            if s.series_type not in _YIELD_CURVE_SERIES_TYPES:
+                raise ValueError(
+                    f"Yield curve charts only support Line and Area series, "
+                    f"got {s.series_type}"
+                )
+
+    chart_options: dict = {}
+
+    # Yield curve options
+    if resolved_type == "yieldCurve":
+        yc = _filter_none(
+            {
+                "baseResolution": base_resolution,
+                "minimumTimeRange": minimum_time_range,
+                "startTimeRange": start_time_range,
+            }
+        )
+        if yc:
+            chart_options["yieldCurve"] = yc
+
+    # Layout
+    # --- Background validation ---
+    # Note: colorParsers (array of CustomColorParser JS callables) is not
+    # implementable from Python — the plugin serializes static JSON config
+    # and cannot ship Python callables as JS functions.
+    _has_gradient = (
+        background_top_color is not None or background_bottom_color is not None
+    )
+    if background_color is not None and _has_gradient:
+        raise ValueError(
+            "Cannot set both background_color and gradient background parameters. "
+            "Use background_color for a solid background, or use "
+            "background_top_color and background_bottom_color together for a gradient."
+        )
+    if (background_top_color is None) != (background_bottom_color is None):
+        raise ValueError(
+            "Both background_top_color and background_bottom_color must be provided "
+            "together for a gradient background; only one was given."
+        )
+
+    # fontFamily is intentionally not user-configurable; we always use Fira.
+    layout = _filter_none(
+        {
+            "textColor": text_color,
+            "fontSize": font_size,
+            "fontFamily": "Fira, sans-serif",
+            "attributionLogo": attribution_logo,
+            "colorSpace": color_space,
+        }
+    )
+    if background_color is not None:
+        layout["background"] = {"type": "solid", "color": background_color}
+    elif background_top_color is not None:
+        # Both are set (validated above)
+        layout["background"] = {
+            "type": "gradient",
+            "topColor": background_top_color,
+            "bottomColor": background_bottom_color,
+        }
+    panes_opts = _filter_none(
+        {
+            "separatorColor": pane_separator_color,
+            "separatorHoverColor": pane_separator_hover_color,
+            "enableResize": pane_enable_resize,
+        }
+    )
+    if panes_opts:
+        layout["panes"] = panes_opts
+    if layout:
+        chart_options["layout"] = layout
+
+    # Grid
+    grid: dict = {}
+    vert = _filter_none(
+        {
+            "visible": vert_lines_visible,
+            "color": vert_lines_color,
+            "style": LINE_STYLE_MAP.get(vert_lines_style) if vert_lines_style else None,
+        }
+    )
+    if vert:
+        grid["vertLines"] = vert
+    horz = _filter_none(
+        {
+            "visible": horz_lines_visible,
+            "color": horz_lines_color,
+            "style": LINE_STYLE_MAP.get(horz_lines_style) if horz_lines_style else None,
+        }
+    )
+    if horz:
+        grid["horzLines"] = horz
+    if grid:
+        chart_options["grid"] = grid
+
+    # Crosshair
+    crosshair: dict = {}
+    if crosshair_mode is not None:
+        crosshair["mode"] = CROSSHAIR_MODE_MAP.get(crosshair_mode, 0)
+    if crosshair_do_not_snap_to_hidden_series is not None:
+        crosshair[
+            "doNotSnapToHiddenSeriesIndices"
+        ] = crosshair_do_not_snap_to_hidden_series
+    vert_line = _filter_none(
+        {
+            "width": crosshair_vert_line_width,
+            "color": crosshair_vert_line_color,
+            "style": (
+                LINE_STYLE_MAP.get(crosshair_vert_line_style)
+                if crosshair_vert_line_style
+                else None
+            ),
+            "visible": crosshair_vert_line_visible,
+            "labelVisible": crosshair_vert_line_label_visible,
+            "labelBackgroundColor": crosshair_vert_line_label_background_color,
+        }
+    )
+    if vert_line:
+        crosshair["vertLine"] = vert_line
+    horz_line = _filter_none(
+        {
+            "width": crosshair_horz_line_width,
+            "color": crosshair_horz_line_color,
+            "style": (
+                LINE_STYLE_MAP.get(crosshair_horz_line_style)
+                if crosshair_horz_line_style
+                else None
+            ),
+            "visible": crosshair_horz_line_visible,
+            "labelVisible": crosshair_horz_line_label_visible,
+            "labelBackgroundColor": crosshair_horz_line_label_background_color,
+        }
+    )
+    if horz_line:
+        crosshair["horzLine"] = horz_line
+    if crosshair:
+        chart_options["crosshair"] = crosshair
+
+    # Right price scale
+    rps = _filter_none(
+        {
+            "visible": right_price_scale_visible,
+            "borderVisible": right_price_scale_border_visible,
+            "borderColor": right_price_scale_border_color,
+            "autoScale": right_price_scale_auto_scale,
+            "mode": (
+                PRICE_SCALE_MODE_MAP.get(right_price_scale_mode)
+                if right_price_scale_mode
+                else None
+            ),
+            "invertScale": right_price_scale_invert_scale,
+            "alignLabels": right_price_scale_align_labels,
+            "textColor": right_price_scale_text_color,
+            "entireTextOnly": right_price_scale_entire_text_only,
+            "ticksVisible": right_price_scale_ticks_visible,
+            "minimumWidth": right_price_scale_minimum_width,
+            "ensureEdgeTickMarksVisible": right_price_scale_ensure_edge_tick_marks_visible,
+            "tickMarkDensity": right_price_scale_tick_mark_density,
+        }
+    )
+    rps_margins = _filter_none(
+        {
+            "top": right_price_scale_margin_top,
+            "bottom": right_price_scale_margin_bottom,
+        }
+    )
+    if rps_margins:
+        rps["scaleMargins"] = rps_margins
+    if rps:
+        chart_options["rightPriceScale"] = rps
+
+    # Left price scale
+    lps = _filter_none(
+        {
+            "visible": left_price_scale_visible,
+            "borderVisible": left_price_scale_border_visible,
+            "borderColor": left_price_scale_border_color,
+            "autoScale": left_price_scale_auto_scale,
+            "mode": (
+                PRICE_SCALE_MODE_MAP.get(left_price_scale_mode)
+                if left_price_scale_mode
+                else None
+            ),
+            "invertScale": left_price_scale_invert_scale,
+            "alignLabels": left_price_scale_align_labels,
+            "textColor": left_price_scale_text_color,
+            "entireTextOnly": left_price_scale_entire_text_only,
+            "ticksVisible": left_price_scale_ticks_visible,
+            "minimumWidth": left_price_scale_minimum_width,
+            "ensureEdgeTickMarksVisible": left_price_scale_ensure_edge_tick_marks_visible,
+            "tickMarkDensity": left_price_scale_tick_mark_density,
+        }
+    )
+    lps_margins = _filter_none(
+        {
+            "top": left_price_scale_margin_top,
+            "bottom": left_price_scale_margin_bottom,
+        }
+    )
+    if lps_margins:
+        lps["scaleMargins"] = lps_margins
+    if lps:
+        chart_options["leftPriceScale"] = lps
+
+    # Overlay price scale defaults
+    ops: dict = _filter_none(
+        {
+            "autoScale": overlay_price_scale_auto_scale,
+            "mode": (
+                PRICE_SCALE_MODE_MAP.get(overlay_price_scale_mode)
+                if overlay_price_scale_mode
+                else None
+            ),
+            "invertScale": overlay_price_scale_invert_scale,
+            "alignLabels": overlay_price_scale_align_labels,
+            "borderVisible": overlay_price_scale_border_visible,
+            "borderColor": overlay_price_scale_border_color,
+            "textColor": overlay_price_scale_text_color,
+            "entireTextOnly": overlay_price_scale_entire_text_only,
+            "ticksVisible": overlay_price_scale_ticks_visible,
+            "minimumWidth": overlay_price_scale_minimum_width,
+            "ensureEdgeTickMarksVisible": overlay_price_scale_ensure_edge_tick_marks_visible,
+            "tickMarkDensity": overlay_price_scale_tick_mark_density,
+        }
+    )
+    ops_margins = _filter_none(
+        {
+            "top": overlay_price_scale_margin_top,
+            "bottom": overlay_price_scale_margin_bottom,
+        }
+    )
+    if ops_margins:
+        ops["scaleMargins"] = ops_margins
+    if ops:
+        chart_options["overlayPriceScales"] = ops
+
+    # Time scale
+    ts = _filter_none(
+        {
+            "timeVisible": time_visible,
+            "secondsVisible": seconds_visible,
+            "borderVisible": time_scale_border_visible,
+            "borderColor": time_scale_border_color,
+            "visible": time_scale_visible,
+            "rightOffset": right_offset,
+            "rightOffsetPixels": right_offset_pixels,
+            "barSpacing": bar_spacing,
+            "minBarSpacing": min_bar_spacing,
+            "maxBarSpacing": max_bar_spacing,
+            "fixLeftEdge": fix_left_edge,
+            "fixRightEdge": fix_right_edge,
+            "lockVisibleTimeRangeOnResize": lock_visible_time_range_on_resize,
+            "rightBarStaysOnScroll": right_bar_stays_on_scroll,
+            "shiftVisibleRangeOnNewBar": shift_visible_range_on_new_bar,
+            "allowShiftVisibleRangeOnWhitespaceReplacement": allow_shift_visible_range_on_whitespace_replacement,
+            "ticksVisible": time_scale_ticks_visible,
+            "tickMarkMaxCharacterLength": tick_mark_max_character_length,
+            "uniformDistribution": uniform_distribution,
+            "minimumHeight": time_scale_minimum_height,
+            "allowBoldLabels": allow_bold_labels,
+            "ignoreWhitespaceIndices": ignore_whitespace_indices,
+            "enableConflation": enable_conflation,
+            "conflationThresholdFactor": conflation_threshold_factor,
+            "precomputeConflationOnInit": precompute_conflation_on_init,
+            "precomputeConflationPriority": precompute_conflation_priority,
+        }
+    )
+    if ts:
+        chart_options["timeScale"] = ts
+
+    # --- Watermark ---
+
+    # Validate mutual exclusion
+    if watermark_lines is not None and watermark_text is not None:
+        raise ValueError(
+            "Provide either 'watermark_text' (single-line shortcut) or "
+            "'watermark_lines' (multi-line), not both."
+        )
+
+    # Single-line styling params are not applicable with watermark_lines
+    if watermark_lines is not None and any(
+        p is not None
+        for p in (
+            watermark_color,
+            watermark_font_size,
+            watermark_font_style,
+            watermark_line_height,
+        )
+    ):
+        raise ValueError(
+            "Single-line watermark params (watermark_color, watermark_font_size, "
+            "watermark_font_style, watermark_line_height) cannot be combined with "
+            "'watermark_lines'. Set per-line styling on each WatermarkLine instead."
+        )
+
+    if watermark_lines is not None:
+        # Multi-line path: serialise each WatermarkLine to a dict
+        lines_payload = [_watermark_line_to_dict(ln) for ln in watermark_lines]
+        wm: dict = {
+            "lines": lines_payload,
+        }
+        if watermark_visible is not None:
+            wm["visible"] = watermark_visible
+        elif lines_payload:
+            wm["visible"] = True
+        if watermark_horz_align is not None:
+            wm["horzAlign"] = watermark_horz_align
+        if watermark_vert_align is not None:
+            wm["vertAlign"] = watermark_vert_align
+        chart_options["watermark"] = wm
+
+    elif watermark_text is not None or watermark_visible is not None:
+        # Legacy single-line path (fully backwards-compatible)
+        wm = _filter_none(
+            {
+                "text": watermark_text,
+                "color": watermark_color,
+                "visible": (
+                    watermark_visible
+                    if watermark_visible is not None
+                    else (True if watermark_text else None)
+                ),
+                "fontSize": watermark_font_size,
+                "fontStyle": watermark_font_style,
+                "lineHeight": watermark_line_height,
+                "horzAlign": watermark_horz_align,
+                "vertAlign": watermark_vert_align,
+            }
+        )
+        if wm:
+            chart_options["watermark"] = wm
+
+    # Image watermark (orthogonal to text watermark)
+    if watermark_image_url is not None or watermark_image_visible is not None:
+        img_wm = _filter_none(
+            {
+                "url": watermark_image_url,
+                "maxWidth": watermark_image_max_width,
+                "maxHeight": watermark_image_max_height,
+                "padding": watermark_image_padding,
+                "alpha": watermark_image_alpha,
+                "visible": (
+                    watermark_image_visible
+                    if watermark_image_visible is not None
+                    else (True if watermark_image_url else None)
+                ),
+            }
+        )
+        if img_wm:
+            chart_options["imageWatermark"] = img_wm
+
+    # HandleScroll
+    if handle_scroll is not None:
+        chart_options["handleScroll"] = handle_scroll
+    else:
+        hs = _filter_none(
+            {
+                "mouseWheel": handle_scroll_mouse_wheel,
+                "pressedMouseMove": handle_scroll_pressed_mouse_move,
+                "horzTouchDrag": handle_scroll_horz_touch_drag,
+                "vertTouchDrag": handle_scroll_vert_touch_drag,
+            }
+        )
+        if hs:
+            chart_options["handleScroll"] = hs
+
+    # HandleScale
+    if handle_scale is not None:
+        chart_options["handleScale"] = handle_scale
+    else:
+        hsc = _filter_none(
+            {
+                "mouseWheel": handle_scale_mouse_wheel,
+                "pinch": handle_scale_pinch,
+                "axisPressedMouseMove": handle_scale_axis_pressed_mouse_move,
+                "axisDoubleClickReset": handle_scale_axis_double_click_reset,
+            }
+        )
+        if hsc:
+            chart_options["handleScale"] = hsc
+
+    # KineticScroll
+    ks = _filter_none(
+        {
+            "touch": kinetic_scroll_touch,
+            "mouse": kinetic_scroll_mouse,
+        }
+    )
+    if ks:
+        chart_options["kineticScroll"] = ks
+
+    # Localization
+    loc: dict = {}
+    if price_formatter is not None:
+        loc["priceFormatterName"] = price_formatter
+    if locale is not None:
+        loc["locale"] = locale
+    if tickmarks_price_formatter is not None:
+        loc["tickmarksPriceFormatterName"] = tickmarks_price_formatter
+    if percentage_formatter is not None:
+        loc["percentageFormatterName"] = percentage_formatter
+    if tickmarks_percentage_formatter is not None:
+        loc["tickmarksPercentageFormatterName"] = tickmarks_percentage_formatter
+    if loc:
+        chart_options["localization"] = loc
+
+    # Behavior / interaction
+    if tracking_mode_exit_mode is not None:
+        chart_options["trackingMode"] = {
+            "exitMode": TRACKING_MODE_EXIT_MODE_MAP[tracking_mode_exit_mode]
+        }
+    if add_default_pane is not None:
+        chart_options["addDefaultPane"] = add_default_pane
+    if hovered_series_on_top is not None:
+        chart_options["hoveredSeriesOnTop"] = hovered_series_on_top
+    if default_visible_price_scale_id is not None:
+        chart_options["defaultVisiblePriceScaleId"] = default_visible_price_scale_id
+
+    # --- Tracking tooltip ---
+    # tooltip_visible is the master switch; the detail options are meaningless
+    # without it, so reject them early (mirrors the watermark validation).
+    _tooltip_details = {
+        "tooltip_show_title": tooltip_show_title,
+        "tooltip_show_value": tooltip_show_value,
+        "tooltip_show_date": tooltip_show_date,
+        "tooltip_value_precision": tooltip_value_precision,
+    }
+    if not tooltip_visible:
+        set_details = [name for name, v in _tooltip_details.items() if v is not None]
+        if set_details:
+            raise ValueError(
+                f"{', '.join(set_details)} require tooltip_visible=True. "
+                f"Set tooltip_visible=True to enable the tracking tooltip."
+            )
+    else:
+        chart_options["tooltip"] = _filter_none(
+            {
+                "visible": True,
+                "showTitle": tooltip_show_title,
+                "showValue": tooltip_show_value,
+                "showDate": tooltip_show_date,
+                "valuePrecision": tooltip_value_precision,
+            }
+        )
+
+    return TvlChart(
+        series_list=series_list,
+        chart_options=chart_options,
+        pane_stretch_factors=pane_stretch_factors,
+        pane_preserve_empty=pane_preserve_empty,
+        chart_type=resolved_type,
+        on_press=on_press,
+        on_double_press=on_double_press,
+    )
+
+
+# --- Per-type unified constructors ---
+#
+# Each of the six functions below is the public entry point for a series
+# type. They accept the FULL series-factory signature from series.py +
+# `by=` for partitioning, and return a single-series TvlChart with default
+# chart options. The returned TvlChart can be displayed directly OR passed
+# to tvl.chart(...) to be combined with other series under shared chart
+# styling. Chart-styling options (background_color, text_color, watermark_*,
+# crosshair_*, time_*, width, height, etc.) live only on tvl.chart.
+
+
+def candlestick(
+    table: Any,
+    timestamp: str = "Timestamp",
+    open: str = "Open",
+    high: str = "High",
+    low: str = "Low",
+    close: str = "Close",
+    up_color: Optional[Color] = None,
+    down_color: Optional[Color] = None,
+    border_visible: Optional[bool] = None,
+    border_color: Optional[Color] = None,
+    border_up_color: Optional[Color] = None,
+    border_down_color: Optional[Color] = None,
+    wick_visible: Optional[bool] = None,
+    wick_color: Optional[Color] = None,
+    wick_up_color: Optional[Color] = None,
+    wick_down_color: Optional[Color] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    last_value_visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    color_column: Optional[str] = None,
+    border_color_column: Optional[str] = None,
+    wick_color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    auto_bin: Optional[bool] = None,
+    bin_width: Optional[str] = None,
+    bin_count: Optional[int] = None,
+    by: Optional[str] = None,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Create a candlestick series.
+
+    The result is a single-series :class:`TvlChart` that can be
+    displayed directly OR passed to :func:`chart` to be combined with
+    other series under shared chart styling.
+
+    All series-level options are accepted (full TVL Candlestick
+    options surface). Chart-level styling (background_color,
+    watermark_text, crosshair_mode, time_visible, width, height, etc.)
+    lives on :func:`chart` — wrap this result in ``tvl.chart(...)`` to
+    customize them.
+
+    Args:
+        table: Deephaven table containing OHLC data.
+        timestamp, open, high, low, close: Column names for the OHLC channels.
+        by (Optional[str]): Column name to partition the table by. When
+            set, one runtime series is created per unique value.
+        Other parameters: see :func:`candlestick_series`-equivalent docs.
+
+    Returns:
+        TvlChart: A chart wrapping a single candlestick series.
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> c = tvl.candlestick(ohlc)
+        >>> # Composed with other series:
+        >>> c = tvl.chart(tvl.candlestick(ohlc), tvl.line(sma, "Timestamp", "Sma"))
+    """
+    kwargs = {k: v for k, v in locals().items() if k not in _CHART_ONLY_KWARGS}
+    spec = series_module.candlestick_series(**kwargs)
+    return _wrap_as_chart(spec, by, "candlestick", on_press, on_double_press)
+
+
+def line(
+    table: Any,
+    timestamp: str,
+    value: str,
+    color: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_type: Optional[LineType] = None,
+    line_visible: Optional[bool] = None,
+    point_markers_visible: Optional[bool] = None,
+    point_markers_radius: Optional[float] = None,
+    crosshair_marker_visible: Optional[bool] = None,
+    crosshair_marker_radius: Optional[float] = None,
+    crosshair_marker_border_color: Optional[Color] = None,
+    crosshair_marker_background_color: Optional[Color] = None,
+    crosshair_marker_border_width: Optional[float] = None,
+    last_price_animation: Optional[LastPriceAnimationMode] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    by: Optional[str] = None,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Create a line series.
+
+    The result is a single-series :class:`TvlChart` that can be
+    displayed directly OR passed to :func:`chart` to be combined with
+    other series under shared chart styling.
+
+    Args:
+        table: Deephaven table with the data.
+        timestamp: Column name for the time axis.
+        value: Column name for the y-axis.
+        by (Optional[str]): Column name to partition the table by.
+            When set, one line is drawn per unique value of this column;
+            new partition keys discovered at runtime (ticking tables)
+            add new lines automatically.
+        Other parameters: full TVL Line series options surface (see
+            equivalent of :func:`line_series`).
+
+    Returns:
+        TvlChart: A chart wrapping a single line series (or one line per
+        partition when ``by`` is set).
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> tvl.line(t, "Timestamp", "Price")
+        >>> tvl.chart(tvl.line(t, "Timestamp", "Price", by="Sym"))
+    """
+    kwargs = {k: v for k, v in locals().items() if k not in _CHART_ONLY_KWARGS}
+    spec = series_module.line_series(**kwargs)
+    return _wrap_as_chart(spec, by, "line", on_press, on_double_press)
+
+
+def area(
+    table: Any,
+    timestamp: str,
+    value: str,
+    line_color: Optional[Color] = None,
+    top_color: Optional[Color] = None,
+    bottom_color: Optional[Color] = None,
+    relative_gradient: Optional[bool] = None,
+    invert_filled_area: Optional[bool] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_type: Optional[LineType] = None,
+    line_visible: Optional[bool] = None,
+    point_markers_visible: Optional[bool] = None,
+    point_markers_radius: Optional[float] = None,
+    crosshair_marker_visible: Optional[bool] = None,
+    crosshair_marker_radius: Optional[float] = None,
+    crosshair_marker_border_color: Optional[Color] = None,
+    crosshair_marker_background_color: Optional[Color] = None,
+    crosshair_marker_border_width: Optional[float] = None,
+    last_price_animation: Optional[LastPriceAnimationMode] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    line_color_column: Optional[str] = None,
+    top_color_column: Optional[str] = None,
+    bottom_color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    by: Optional[str] = None,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Create an area series.
+
+    The result is a single-series :class:`TvlChart` that can be
+    displayed directly OR passed to :func:`chart` to be combined with
+    other series under shared chart styling.
+
+    Args:
+        table: Deephaven table with the data.
+        timestamp: Column name for the time axis.
+        value: Column name for the y-axis.
+        by (Optional[str]): Column name to partition by. One area series
+            per unique value (new keys at runtime add new series).
+        Other parameters: full TVL Area series options surface.
+
+    Returns:
+        TvlChart: A chart wrapping a single area series (or one per
+        partition when ``by`` is set).
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> tvl.area(t, "Timestamp", "Price")
+        >>> tvl.chart(tvl.area(t, "Timestamp", "Price"), background_color="#111")
+    """
+    kwargs = {k: v for k, v in locals().items() if k not in _CHART_ONLY_KWARGS}
+    spec = series_module.area_series(**kwargs)
+    return _wrap_as_chart(spec, by, "area", on_press, on_double_press)
+
+
+def bar(
+    table: Any,
+    timestamp: str = "Timestamp",
+    open: str = "Open",
+    high: str = "High",
+    low: str = "Low",
+    close: str = "Close",
+    up_color: Optional[Color] = None,
+    down_color: Optional[Color] = None,
+    open_visible: Optional[bool] = None,
+    thin_bars: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    last_value_visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    auto_bin: Optional[bool] = None,
+    bin_width: Optional[str] = None,
+    bin_count: Optional[int] = None,
+    by: Optional[str] = None,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Create a bar (OHLC) series.
+
+    Bar charts render each bucket as a vertical line with open/close
+    ticks; contrast with :func:`candlestick` which fills the body.
+    The result is a single-series :class:`TvlChart` standalone-renderable
+    or nestable inside :func:`chart`.
+
+    Args:
+        table: Deephaven OHLC table.
+        timestamp, open, high, low, close: Column names for OHLC channels.
+        by (Optional[str]): Partition column.
+        Other parameters: full TVL Bar series options surface.
+
+    Returns:
+        TvlChart: A chart wrapping a single bar series.
+    """
+    kwargs = {k: v for k, v in locals().items() if k not in _CHART_ONLY_KWARGS}
+    spec = series_module.bar_series(**kwargs)
+    return _wrap_as_chart(spec, by, "bar", on_press, on_double_press)
+
+
+def baseline(
+    table: Any,
+    timestamp: str,
+    value: str,
+    base_value: Optional[float] = None,
+    top_line_color: Optional[Color] = None,
+    top_fill_color1: Optional[Color] = None,
+    top_fill_color2: Optional[Color] = None,
+    bottom_line_color: Optional[Color] = None,
+    bottom_fill_color1: Optional[Color] = None,
+    bottom_fill_color2: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_type: Optional[LineType] = None,
+    line_visible: Optional[bool] = None,
+    relative_gradient: Optional[bool] = None,
+    point_markers_visible: Optional[bool] = None,
+    point_markers_radius: Optional[float] = None,
+    crosshair_marker_visible: Optional[bool] = None,
+    crosshair_marker_radius: Optional[float] = None,
+    crosshair_marker_border_color: Optional[Color] = None,
+    crosshair_marker_background_color: Optional[Color] = None,
+    crosshair_marker_border_width: Optional[float] = None,
+    last_price_animation: Optional[LastPriceAnimationMode] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    top_line_color_column: Optional[str] = None,
+    top_fill_color1_column: Optional[str] = None,
+    top_fill_color2_column: Optional[str] = None,
+    bottom_line_color_column: Optional[str] = None,
+    bottom_fill_color1_column: Optional[str] = None,
+    bottom_fill_color2_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    by: Optional[str] = None,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Create a baseline series.
+
+    Fills the area between the value line and a horizontal base value
+    with different gradient colors above (top) and below (bottom).
+    Single-series :class:`TvlChart` standalone-renderable or nestable in
+    :func:`chart`.
+
+    Args:
+        table: Deephaven table.
+        timestamp, value: Column names.
+        base_value: Baseline price level (default 0.0).
+        by (Optional[str]): Partition column.
+        Other parameters: full TVL Baseline series options surface.
+    """
+    kwargs = {k: v for k, v in locals().items() if k not in _CHART_ONLY_KWARGS}
+    spec = series_module.baseline_series(**kwargs)
+    return _wrap_as_chart(spec, by, "baseline", on_press, on_double_press)
+
+
+def histogram(
+    table: Any,
+    timestamp: str,
+    value: str,
+    color: Optional[Color] = None,
+    base: Optional[float] = None,
+    color_column: Optional[str] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    auto_bin: Optional[bool] = None,
+    bin_width: Optional[str] = None,
+    bin_count: Optional[int] = None,
+    agg: str = "sum",
+    by: Optional[str] = None,
+    on_press: Optional[PressEventCallable] = None,
+    on_double_press: Optional[PressEventCallable] = None,
+) -> TvlChart:
+    """Create a histogram series.
+
+    One vertical bar per time bucket. ``agg`` selects the per-bin
+    reduction (sum / count / avg / last) when auto-binning fires.
+    Single-series :class:`TvlChart` standalone-renderable or nestable in
+    :func:`chart`.
+
+    Args:
+        table: Deephaven table.
+        timestamp, value: Column names.
+        agg: Per-bin reduction (``"sum"``, ``"count"``, ``"avg"``, ``"last"``).
+        by (Optional[str]): Partition column.
+        Other parameters: full TVL Histogram series options surface.
+    """
+    kwargs = {k: v for k, v in locals().items() if k not in _CHART_ONLY_KWARGS}
+    spec = series_module.histogram_series(**kwargs)
+    return _wrap_as_chart(spec, by, "histogram", on_press, on_double_press)
+
+
+# --- Non-standard chart type convenience functions ---
+
+
+def yield_curve(
+    table: Any,
+    maturity: str = "Maturity",
+    value: str = "Yield",
+    series_type: str = "line",
+    # Series styling
+    color: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    title: Optional[str] = None,
+    # Area-specific (only used when series_type="area")
+    line_color: Optional[Color] = None,
+    top_color: Optional[Color] = None,
+    bottom_color: Optional[Color] = None,
+    # Yield curve options
+    base_resolution: Optional[int] = None,
+    minimum_time_range: Optional[int] = None,
+    start_time_range: Optional[int] = None,
+    # Common chart options
+    background_color: Optional[Color] = None,
+    text_color: Optional[Color] = None,
+    crosshair_mode: Optional[CrosshairMode] = None,
+    watermark_text: Optional[str] = None,
+) -> TvlChart:
+    """Create a yield curve chart with a single Line or Area series.
+
+    A yield-curve chart has a numeric horizontal axis representing
+    maturity in months and is rendered via the TVL JS
+    ``createYieldCurveChart`` backend.  Only Line and Area series are
+    supported.
+
+    Args:
+        table (Any): Deephaven table with the yield-curve data.
+        maturity (str): Column name for the x-axis (months, numeric).
+        value (str): Column name for the y-axis (yield values).
+        series_type (str): ``"line"`` (default) or ``"area"``.
+        color (Optional[Color]): Line color (also used as the area's
+            line color when ``line_color`` is not set).
+        line_width (Optional[LineWidth]): Stroke width in pixels (1–4).
+        title (Optional[str]): Title shown in the series tooltip /
+            legend.
+        line_color (Optional[Color]): Area-only: explicit line color
+            (overrides ``color``).
+        top_color (Optional[Color]): Area-only: top gradient fill color.
+        bottom_color (Optional[Color]): Area-only: bottom gradient fill
+            color.
+        base_resolution (Optional[int]): Yield-curve x-axis base
+            resolution in seconds.
+        minimum_time_range (Optional[int]): Minimum visible time range.
+        start_time_range (Optional[int]): Initial visible time range.
+        background_color (Optional[Color]): Chart background CSS color.
+        text_color (Optional[Color]): Axis / label text color.
+        crosshair_mode (Optional[CrosshairMode]): Crosshair mode; see
+            :data:`CrosshairMode`.
+        watermark_text (Optional[str]): Single-line watermark text.
+
+    Returns:
+        TvlChart: A yield-curve chart with a single series.
+
+    Raises:
+        ValueError: If ``series_type`` is not ``"line"`` or ``"area"``.
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> c = tvl.yield_curve(curve, maturity="Maturity",
+        ...                     value="Yield", series_type="line")
+    """
+    st = series_type.lower()
+    _valid_yc = {"line", "area"}
+    if st not in _valid_yc:
+        raise ValueError(
+            f"yield_curve() series_type must be one of {sorted(_valid_yc)}, got {series_type!r}"
+        )
+    if st == "area":
+        s = series_module.area_series(
+            table,
+            timestamp=maturity,
+            value=value,
+            line_color=line_color or color,
+            top_color=top_color,
+            bottom_color=bottom_color,
+            line_width=line_width,
+            title=title,
+        )
+    else:
+        s = series_module.line_series(
+            table,
+            timestamp=maturity,
+            value=value,
+            color=color,
+            line_width=line_width,
+            title=title,
+        )
+    return chart(
+        s,
+        chart_type="yield_curve",
+        base_resolution=base_resolution,
+        minimum_time_range=minimum_time_range,
+        start_time_range=start_time_range,
+        background_color=background_color,
+        text_color=text_color,
+        crosshair_mode=crosshair_mode,
+        watermark_text=watermark_text,
+    )
+
+
+def options_chart(
+    table: Any,
+    strike: str = "Strike",
+    value: str = "Value",
+    series_type: str = "line",
+    # Series styling
+    color: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    title: Optional[str] = None,
+    # Area-specific
+    line_color: Optional[Color] = None,
+    top_color: Optional[Color] = None,
+    bottom_color: Optional[Color] = None,
+    # Common chart options
+    background_color: Optional[Color] = None,
+    text_color: Optional[Color] = None,
+    crosshair_mode: Optional[CrosshairMode] = None,
+    watermark_text: Optional[str] = None,
+) -> TvlChart:
+    """Create an options chart with a single series.
+
+    The horizontal axis represents strike prices (numeric) and the
+    chart is rendered via the TVL JS ``createOptionsChart`` backend.
+    For non-strike numeric x-axes (frequency, distance, etc.), prefer
+    :func:`custom_numeric`, which uses the same renderer with a more
+    descriptive name and parameter (``x`` instead of ``strike``).
+
+    Args:
+        table (Any): Deephaven table with the data.
+        strike (str): Column name for the x-axis (strike prices,
+            numeric).
+        value (str): Column name for the y-axis.
+        series_type (str): ``"line"`` (default), ``"area"``, or
+            ``"histogram"``.
+        color (Optional[Color]): Line / histogram color.  For area
+            series, falls back to ``line_color`` when set.
+        line_width (Optional[LineWidth]): Stroke width in pixels (1–4).
+        title (Optional[str]): Title shown in the series tooltip /
+            legend.
+        line_color (Optional[Color]): Area-only: explicit line color.
+        top_color (Optional[Color]): Area-only: top gradient fill color.
+        bottom_color (Optional[Color]): Area-only: bottom gradient fill
+            color.
+        background_color (Optional[Color]): Chart background CSS color.
+        text_color (Optional[Color]): Axis / label text color.
+        crosshair_mode (Optional[CrosshairMode]): Crosshair mode; see
+            :data:`CrosshairMode`.
+        watermark_text (Optional[str]): Single-line watermark text.
+
+    Returns:
+        TvlChart: An options chart with a single series.
+
+    Raises:
+        ValueError: If ``series_type`` is not ``"line"``, ``"area"``,
+            or ``"histogram"``.
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> c = tvl.options_chart(opt_chain, strike="Strike",
+        ...                       value="IV", series_type="line")
+    """
+    st = series_type.lower()
+    _valid_oc = {"line", "area", "histogram"}
+    if st not in _valid_oc:
+        raise ValueError(
+            f"options_chart() series_type must be one of {sorted(_valid_oc)}, got {series_type!r}"
+        )
+    if st == "area":
+        s = series_module.area_series(
+            table,
+            timestamp=strike,
+            value=value,
+            line_color=line_color or color,
+            top_color=top_color,
+            bottom_color=bottom_color,
+            line_width=line_width,
+            title=title,
+        )
+    elif st == "histogram":
+        s = series_module.histogram_series(
+            table,
+            timestamp=strike,
+            value=value,
+            color=color,
+            title=title,
+        )
+    else:
+        s = series_module.line_series(
+            table,
+            timestamp=strike,
+            value=value,
+            color=color,
+            line_width=line_width,
+            title=title,
+        )
+    return chart(
+        s,
+        chart_type="options",
+        background_color=background_color,
+        text_color=text_color,
+        crosshair_mode=crosshair_mode,
+        watermark_text=watermark_text,
+    )
+
+
+def custom_numeric(
+    table: Any,
+    x: str = "X",
+    value: str = "Value",
+    series_type: str = "line",
+    # Series styling
+    color: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    title: Optional[str] = None,
+    # Area-specific
+    line_color: Optional[Color] = None,
+    top_color: Optional[Color] = None,
+    bottom_color: Optional[Color] = None,
+    # Common chart options
+    background_color: Optional[Color] = None,
+    text_color: Optional[Color] = None,
+    crosshair_mode: Optional[CrosshairMode] = None,
+    watermark_text: Optional[str] = None,
+) -> TvlChart:
+    """Create a chart with a generic numeric x-axis.
+
+    Use this when the x-axis represents arbitrary numeric values
+    (frequency, distance, price level, etc.) rather than timestamps.
+    Internally uses the same ``createOptionsChart`` renderer as
+    :func:`options_chart`, which provides a linearly-spaced numeric
+    horizontal scale.
+
+    Args:
+        table (Any): Deephaven table with the data.
+        x (str): Column name for the x-axis (numeric values).
+        value (str): Column name for the y-axis.
+        series_type (str): ``"line"`` (default), ``"area"``, or
+            ``"histogram"``.
+        color (Optional[Color]): Line / histogram color.
+        line_width (Optional[LineWidth]): Stroke width in pixels (1–4).
+        title (Optional[str]): Title shown in the series tooltip /
+            legend.
+        line_color (Optional[Color]): Area-only: explicit line color.
+        top_color (Optional[Color]): Area-only: top gradient fill color.
+        bottom_color (Optional[Color]): Area-only: bottom gradient fill
+            color.
+        background_color (Optional[Color]): Chart background CSS color.
+        text_color (Optional[Color]): Axis / label text color.
+        crosshair_mode (Optional[CrosshairMode]): Crosshair mode; see
+            :data:`CrosshairMode`.
+        watermark_text (Optional[str]): Single-line watermark text.
+
+    Returns:
+        TvlChart: A chart with a generic numeric x-axis.
+
+    Raises:
+        ValueError: If ``series_type`` is not ``"line"``, ``"area"``,
+            or ``"histogram"``.
+
+    Note:
+        ``createChartEx`` with a fully custom ``horzScaleBehavior``
+        is not supported from Python.  Ship a JS plugin extension for
+        that use case.
+
+    Example:
+        >>> import deephaven.plot.tradingview_lightweight as tvl
+        >>> c = tvl.custom_numeric(data, x="Frequency",
+        ...                        value="Amplitude")
+    """
+    st = series_type.lower()
+    _valid_cn = {"line", "area", "histogram"}
+    if st not in _valid_cn:
+        raise ValueError(
+            f"custom_numeric() series_type must be one of {sorted(_valid_cn)}, got {series_type!r}"
+        )
+    if st == "area":
+        s = series_module.area_series(
+            table,
+            timestamp=x,
+            value=value,
+            line_color=line_color or color,
+            top_color=top_color,
+            bottom_color=bottom_color,
+            line_width=line_width,
+            title=title,
+        )
+    elif st == "histogram":
+        s = series_module.histogram_series(
+            table,
+            timestamp=x,
+            value=value,
+            color=color,
+            title=title,
+        )
+    else:
+        s = series_module.line_series(
+            table,
+            timestamp=x,
+            value=value,
+            color=color,
+            line_width=line_width,
+            title=title,
+        )
+    return chart(
+        s,
+        chart_type="custom_numeric",
+        background_color=background_color,
+        text_color=text_color,
+        crosshair_mode=crosshair_mode,
+        watermark_text=watermark_text,
+    )
+
+
+def _inherit_series_docstring(
+    unified_fn: Any, factory_fn: Any, returns_desc: str
+) -> None:
+    """Replace the unified constructor's terse docstring with one derived
+    from the matching ``*_series`` factory.
+
+    The deephaven_autodoc Sphinx extension iterates the function signature
+    and requires every parameter to appear in the rendered Args list with
+    ``name (type) -- description`` format. The unified constructors share
+    the factory's parameter set + ``by``, so the factory's Args block is
+    reused verbatim and a ``by`` entry is appended. The Returns line is
+    rewritten to ``TvlChart`` since the unified constructor wraps the spec.
+    """
+    # Normalize indentation first: Python 3.13+ dedents docstrings at
+    # compile time, so the raw __doc__ indentation differs across
+    # versions. After cleandoc, sections sit at column 0 and Args
+    # entries at 4 regardless of interpreter.
+    factory_doc = inspect.cleandoc(factory_fn.__doc__ or "")
+    lines = factory_doc.split("\n")
+    # Find Args: and Returns: section boundaries
+    args_idx = None
+    returns_idx = None
+    for i, ln in enumerate(lines):
+        if ln.strip() == "Args:":
+            args_idx = i
+        elif ln.strip().startswith("Returns:"):
+            returns_idx = i
+            break
+    if args_idx is None or returns_idx is None:
+        return  # factory has no Args/Returns; leave the existing terse doc
+
+    # Insert `by` + event-handler entries as the last items in Args
+    # (before Returns). These params are added by the per-type constructor
+    # on top of the factory's signature, so they need explicit Args lines
+    # for the autodoc coverage check.
+    by_doc = [
+        "    by (Optional[str]): Column name to partition the table by.",
+        "        When set, one runtime series is created per unique value;",
+        "        new partition keys discovered at runtime (ticking tables)",
+        "        add new series automatically.",
+        "    on_press (Optional[PressEventCallable]): Server-side callback",
+        "        invoked when the user presses (clicks) on the chart. Receives",
+        "        a TvlPressEvent dict, or no argument.",
+        "    on_double_press (Optional[PressEventCallable]): Server-side",
+        "        callback invoked when the user double-presses on the chart.",
+    ]
+    # Find the last non-blank line of the Args block.
+    insert_at = returns_idx
+    while insert_at > args_idx + 1 and not lines[insert_at - 1].strip():
+        insert_at -= 1
+
+    new_lines = lines[:insert_at] + by_doc + [""] + lines[returns_idx:]
+
+    # Rewrite the Returns body. Find the indented description line(s)
+    # after `Returns:` and replace with the unified-constructor's return.
+    out: list[str] = []
+    in_returns = False
+    skipped_returns_body = False
+    for ln in new_lines:
+        if ln.strip().startswith("Returns:"):
+            out.append(ln)
+            in_returns = True
+            skipped_returns_body = False
+            continue
+        if in_returns and not skipped_returns_body:
+            # Replace the first description with our own.
+            if ln.strip() and ln.startswith(" "):
+                out.append("    TvlChart: " + returns_desc)
+                skipped_returns_body = True
+                continue
+            elif ln.strip() == "":
+                continue
+        if in_returns and ln and not ln.startswith(" "):
+            in_returns = False
+        out.append(ln)
+
+    # Take the first paragraph of the factory's docstring as the summary
+    # and prepend a sentence about the unified constructor's behavior.
+    summary_end = 0
+    for i, ln in enumerate(lines):
+        if i > 0 and ln.strip() == "":
+            summary_end = i
+            break
+    summary = "\n".join(lines[:summary_end])
+
+    unified_fn.__doc__ = (
+        summary
+        + "\n\nThe result is a single-series :class:`TvlChart` that can be displayed\n"
+        + "directly OR passed to :func:`chart` to be combined with other series\n"
+        + "under shared chart styling.\n\n"
+        + "\n".join(out[summary_end:])
+    )
+
+
+_inherit_series_docstring(
+    candlestick,
+    series_module.candlestick_series,
+    "A chart wrapping a single candlestick series.",
+)
+_inherit_series_docstring(
+    line,
+    series_module.line_series,
+    "A chart wrapping a single line series (or one line per partition when ``by`` is set).",
+)
+_inherit_series_docstring(
+    area,
+    series_module.area_series,
+    "A chart wrapping a single area series (or one per partition when ``by`` is set).",
+)
+_inherit_series_docstring(
+    bar,
+    series_module.bar_series,
+    "A chart wrapping a single bar series.",
+)
+_inherit_series_docstring(
+    baseline,
+    series_module.baseline_series,
+    "A chart wrapping a single baseline series.",
+)
+_inherit_series_docstring(
+    histogram,
+    series_module.histogram_series,
+    "A chart wrapping a single histogram series.",
+)
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/__init__.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/__init__.py
new file mode 100644
index 000000000..f5502570a
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/__init__.py
@@ -0,0 +1,4 @@
+from .connection import TvlChartConnection
+from .listener import TvlChartListener
+
+__all__ = ["TvlChartConnection", "TvlChartListener"]
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/connection.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/connection.py
new file mode 100644
index 000000000..c9f190455
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/connection.py
@@ -0,0 +1,79 @@
+"""Connection for TvlChart bidirectional communication."""
+
+from __future__ import annotations
+
+import json
+from typing import Any, Optional
+
+from deephaven.plugin.object_type import MessageStream
+
+from ..chart import TvlChart
+from .listener import TvlChartListener
+
+# Capturing the execution context at connection-creation time lets press-event
+# handlers run real Deephaven work later (the EVENT arrives on a thread with no
+# ambient context). Optional so the module still imports without a server.
+try:
+    from deephaven.execution_context import get_exec_ctx
+except ImportError:  # pragma: no cover - exercised only without a server
+    get_exec_ctx = None  # type: ignore[assignment]
+
+
+class TvlChartConnection(MessageStream):
+    """Connection for TvlChart.
+
+    Attributes:
+        _listener: TvlChartListener: The listener for the chart
+        _client_connection: MessageStream: The connection to the client
+    """
+
+    def __init__(self, chart: TvlChart, client_connection: MessageStream):
+        super().__init__()
+        exec_ctx = get_exec_ctx() if get_exec_ctx is not None else None
+        self._listener: Optional[TvlChartListener] = TvlChartListener(
+            chart, client_connection, exec_ctx=exec_ctx
+        )
+        self._client_connection: Optional[MessageStream] = client_connection
+
+    def on_data(self, payload: bytes, references: list[Any]) -> tuple[bytes, list[Any]]:
+        """Process incoming data from the client.
+
+        For the initial RETRIEVE, the response is returned and pushed by
+        create_client_connection in __init__.py.  For subsequent messages
+        (ZOOM, RESET) sent via widget.sendMessage(), the framework does
+        NOT automatically push the return value to the client.  We must
+        explicitly call client_connection.on_data() to deliver the
+        response as a Widget.EVENT_MESSAGE on the JS side.
+        """
+        if self._listener is None:
+            raise RuntimeError("Connection is closed")
+
+        response_payload, response_refs = self._listener.process_message(
+            payload, references
+        )
+
+        # Push asynchronous responses to the client explicitly. The initial
+        # NEW_FIGURE response (replying to the seed RETRIEVE) is pushed by
+        # create_client_connection in __init__.py.
+        _PUSHED_TYPES = {"DOWNSAMPLE_READY", "AUTOBIN_FIGURE"}
+        if response_payload and self._client_connection is not None:
+            try:
+                raw = (
+                    response_payload.decode("utf-8")
+                    if isinstance(response_payload, bytes)
+                    else bytes(response_payload).decode("utf-8")
+                )
+                msg = json.loads(raw)
+                if msg.get("type") in _PUSHED_TYPES:
+                    self._client_connection.on_data(response_payload, response_refs)
+            except (json.JSONDecodeError, UnicodeDecodeError):
+                pass
+
+        return response_payload, response_refs
+
+    def on_close(self) -> None:
+        """Close the connection and release resources."""
+        if self._listener is not None:
+            self._listener.close()
+        self._listener = None
+        self._client_connection = None
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/listener.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/listener.py
new file mode 100644
index 000000000..0096909a2
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/communication/listener.py
@@ -0,0 +1,771 @@
+"""Table listener for TvlChart real-time updates."""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+from dataclasses import dataclass, field
+from typing import Any, Optional
+
+from deephaven.plugin.object_type import MessageStream
+
+from ..chart import TvlChart
+from ..events import (
+    PRESS,
+    DOUBLE_PRESS,
+    TvlPressEvent,
+    build_press_event,
+    time_converter_for,
+    wrap_callable,
+)
+from .. import auto_bin
+
+# Liveness scope for handler dispatch. Optional so the module imports without
+# a server (unit tests); when absent, handlers run without a managed scope.
+try:
+    from deephaven.liveness_scope import liveness_scope
+except ImportError:  # pragma: no cover - exercised only without a server
+    liveness_scope = None  # type: ignore[assignment]
+
+logger = logging.getLogger(__name__)
+
+# Series types eligible for JS-side downsampling via runChartDownsample
+DOWNSAMPLE_ELIGIBLE_TYPES = {"Line", "Area", "Baseline"}
+
+# Tables smaller than this are rendered directly without downsampling
+DOWNSAMPLE_THRESHOLD = 1000
+
+# Series types eligible for server-side time-bin aggregation
+AUTO_BIN_ELIGIBLE_TYPES = {"Histogram", "Candlestick", "Bar"}
+
+# Tables smaller than this are not auto-binned. Override via TVL_AUTO_BIN_THRESHOLD.
+# Defaults to 2x the visual target so anything that would render sub-pixel
+# bars triggers aggregation (raw rows > 2x display capacity ≈ illegible).
+AUTO_BIN_THRESHOLD = int(
+    os.environ.get("TVL_AUTO_BIN_THRESHOLD", str(2 * auto_bin.TARGET_BINS))
+)
+
+
+def _series_index(series_id: Any) -> Optional[int]:
+    """Extract the series index ``i`` from a wire id ``"series_{i}"``.
+
+    Partitioned (``by=``) series carry a key suffix (``"series_{i}_{key}"``);
+    the leading index still identifies the owning :class:`SeriesSpec`. Returns
+    ``None`` for anything that isn't a recognizable series id.
+    """
+    if not isinstance(series_id, str) or not series_id.startswith("series_"):
+        return None
+    head = series_id[len("series_") :].split("_", 1)[0]
+    return int(head) if head.isdigit() else None
+
+
+def _time_type_name(spec: Any) -> Optional[str]:
+    """Return a series' time-column ``DType.j_name``, or ``None`` if unknown.
+
+    Defensive against mock/typeless tables (tests) and missing columns: any
+    failure resolves to ``None`` so the event falls back to a ``datetime``.
+    """
+    time_col = (getattr(spec, "column_mapping", None) or {}).get("time")
+    table = getattr(spec, "table", None)
+    if not time_col or table is None:
+        return None
+    try:
+        for col in table.columns:
+            if col.name == time_col:
+                return getattr(col.data_type, "j_name", None)
+    except Exception:  # noqa: BLE001 - mock tables and odd schemas resolve to None
+        return None
+    return None
+
+
+def _common_time_type(types: list[Optional[str]]) -> Optional[str]:
+    """The single shared time type across all series, else ``None``.
+
+    Requires every series to resolve to the *same* non-``None`` type; a mix
+    (or any unresolved series) yields ``None`` so we don't mislabel a press
+    that named no series.
+    """
+    if not types or any(t is None for t in types):
+        return None
+    return types[0] if len(set(types)) == 1 else None
+
+
+@dataclass
+class _AutoBinTableState:
+    """Per-source-table auto-bin state.
+
+    A "source table" here is the raw input table referenced by one or more
+    Histogram/Candlestick/Bar series. The aggregated table is rebuilt on
+    pan and zoom: the body covers the visible window at fine bin width
+    flanked by single-row anchors at the source extremes so LWC's
+    fixLeftEdge / fixRightEdge clamp correctly. ``body_range_ns`` is None
+    when the build is full-source (no anchors needed); set to (from, to)
+    when scoped.
+    """
+
+    ref_index: int
+    raw_table: Any
+    time_col: str
+    full_range_ns: tuple[int, int]
+    bin_width_ns: int
+    initial_bin_width_ns: int
+    target_bins: int
+    aggregated_table: Any = None
+    # series_id -> dict with keys: type, agg, value_cols
+    series_meta: dict[str, dict[str, Any]] = field(default_factory=dict)
+    body_range_ns: Optional[tuple[int, int]] = None
+
+
+class TvlChartListener:
+    """Listens to table changes and sends chart updates to the client."""
+
+    def __init__(
+        self,
+        chart: TvlChart,
+        client_connection: MessageStream,
+        exec_ctx: Any = None,
+    ):
+        self._chart = chart
+        self._client_connection = client_connection
+        self._exec_ctx = exec_ctx
+        self._revision = 0
+        self._table_id_map: dict[int, int] = {}
+        # Auto-bin state, keyed by ref index of the source table.
+        self._autobin_states: dict[int, _AutoBinTableState] = {}
+        # Handler id -> arity-wrapped callable, built from the chart's
+        # on_press / on_double_press. Mirrors the figure's enabledHandlers
+        # so JS only fires events we can dispatch.
+        self._handlers: dict[str, Any] = {}
+        on_press = getattr(chart, "on_press", None)
+        on_double_press = getattr(chart, "on_double_press", None)
+        if on_press is not None:
+            self._handlers[PRESS] = wrap_callable(on_press)
+        if on_double_press is not None:
+            self._handlers[DOUBLE_PRESS] = wrap_callable(on_double_press)
+        # Per-series time-column dtype names (DType.j_name) so a press event's
+        # ``timestamp`` can mirror the source column type. Only resolved when a
+        # handler is wired, since that's the only consumer.
+        self._series_time_types: list[Optional[str]] = (
+            self._resolve_series_time_types() if self._handlers else []
+        )
+        # Type to use when the press names no series (e.g. a press between
+        # lines): the shared type when every series agrees, else None
+        # (datetime fallback) rather than guessing one series' type.
+        self._default_time_type = _common_time_type(self._series_time_types)
+
+    def _resolve_series_time_types(self) -> list[Optional[str]]:
+        """Map each series (by index) to its time column's ``DType.j_name``.
+
+        Resilient to mock/typeless tables used in tests: any series whose
+        time column or dtype can't be read resolves to ``None``.
+        """
+        return [
+            _time_type_name(spec)
+            for spec in getattr(self._chart, "series_list", []) or []
+        ]
+
+    def process_message(
+        self, payload: bytes, references: list[Any]
+    ) -> tuple[bytes, list[Any]]:
+        """Process an incoming message from the client."""
+        try:
+            if isinstance(payload, bytes):
+                raw = payload.decode("utf-8")
+            else:
+                raw = bytes(payload).decode("utf-8")
+            message = json.loads(raw)
+        except (json.JSONDecodeError, UnicodeDecodeError, TypeError):
+            return b"", []
+
+        msg_type = message.get("type", "")
+
+        if msg_type == "RETRIEVE":
+            return self._handle_retrieve()
+        if msg_type == "AUTOBIN_ZOOM":
+            return self._handle_autobin_zoom(message)
+        if msg_type == "AUTOBIN_RESET":
+            return self._handle_autobin_reset(message)
+        if msg_type == "EVENT":
+            return self._handle_event(message)
+
+        return b"", []
+
+    # ---- EVENT (press / double-press) ----
+
+    def _handle_event(self, message: dict[str, Any]) -> tuple[bytes, list[Any]]:
+        """Dispatch a press / double-press event to its Python handler.
+
+        Fire-and-forget: handlers run under the captured execution context
+        and a fresh liveness scope so they may do real Deephaven work, and
+        any exception is logged and swallowed so a buggy handler cannot kill
+        the widget stream. No client response is produced.
+        """
+        handler_id = message.get("handler", "")
+        callback = self._handlers.get(handler_id)
+        if callback is None:
+            return b"", []
+
+        payload = message.get("payload") or {}
+        event = self._build_event(handler_id, payload)
+
+        try:
+            if self._exec_ctx is not None and liveness_scope is not None:
+                with self._exec_ctx, liveness_scope():
+                    callback(event)
+            else:
+                callback(event)
+        except Exception:  # noqa: BLE001 - a handler bug must not kill the stream
+            logger.exception("TVL %s handler raised", handler_id)
+
+        return b"", []
+
+    def _build_event(self, handler_id: str, payload: dict[str, Any]) -> TvlPressEvent:
+        """Build the event dict for ``handler_id`` from the wire payload.
+
+        Press / double-press mirror ``MouseEventParams`` (time mirrored from the
+        hovered series' column type).
+        """
+        time_type = self._time_type_for_payload(payload)
+        converter = time_converter_for(time_type, payload.get("timeZone"))
+        return build_press_event(handler_id, payload, converter)
+
+    def _time_type_for_payload(self, payload: dict[str, Any]) -> Optional[str]:
+        """Resolve the source time-column type to mirror for this press.
+
+        Prefers the hovered series (from its stable ``hoveredSeriesId``);
+        falls back to the chart's shared type when the press hovered no series
+        or that series' type is unknown.
+        """
+        idx = _series_index(payload.get("hoveredSeriesId"))
+        if idx is not None and 0 <= idx < len(self._series_time_types):
+            hit = self._series_time_types[idx]
+            if hit is not None:
+                return hit
+        return self._default_time_type
+
+    # ---- Eligibility ----
+
+    def _is_series_autobin_eligible(
+        self, table: Any, series: Any, chart_type: str
+    ) -> bool:
+        """Per-series eligibility check.
+
+        A series is auto-bin eligible if:
+        - chart is "standard"
+        - series.series_type in AUTO_BIN_ELIGIBLE_TYPES
+          (Histogram / Candlestick / Bar — series types whose visual
+          representation needs server-side aggregation)
+        - series.auto_bin is not False
+        - either auto_bin=True or table.size > AUTO_BIN_THRESHOLD
+
+        Line / Area / Baseline series on the same source table are NOT
+        eligible — they keep using the JS-side runChartDownsample path.
+        That asymmetry is intentional: line/area degrades smoothly when
+        downsampled per-zoom, but a histogram needs proper bins to render
+        meaningfully.
+        """
+        if chart_type != "standard":
+            return False
+        if series.series_type not in AUTO_BIN_ELIGIBLE_TYPES:
+            return False
+        if series.auto_bin is False:
+            return False
+        if series.auto_bin is True:
+            return True
+        try:
+            return table.size > AUTO_BIN_THRESHOLD
+        except Exception:
+            return False
+
+    # ---- Aggregation ----
+
+    def _build_state_for_table(
+        self,
+        ref_index: int,
+        table: Any,
+        series_for_table: list[Any],
+    ) -> Optional[_AutoBinTableState]:
+        """Compute the initial aggregated view for the source table."""
+        time_col = series_for_table[0].column_mapping.get("time")
+        if time_col is None:
+            return None
+
+        full_range = auto_bin.get_full_range_ns(table, time_col)
+        if full_range is None:
+            return None
+        range_ns = max(1, full_range[1] - full_range[0])
+
+        # Per-series target bins (use first override; mixed series share a width)
+        target_bins = auto_bin.TARGET_BINS
+        for s in series_for_table:
+            if s.bin_count is not None:
+                target_bins = max(1, int(s.bin_count))
+                break
+
+        # Per-series bin_width override
+        bin_width_ns: Optional[int] = None
+        for s in series_for_table:
+            if s.bin_width is not None:
+                bin_width_ns = auto_bin.parse_bin_width(s.bin_width)
+                break
+        if bin_width_ns is None:
+            bin_width_ns = auto_bin.nice_bin_width(range_ns, target_bins)
+
+        state = _AutoBinTableState(
+            ref_index=ref_index,
+            raw_table=table,
+            time_col=time_col,
+            full_range_ns=full_range,
+            bin_width_ns=bin_width_ns,
+            initial_bin_width_ns=bin_width_ns,
+            target_bins=target_bins,
+        )
+
+        for s in series_for_table:
+            series_id = self._series_id_for(s)
+            if s.series_type == "Histogram":
+                value_col = s.column_mapping["value"]
+                color_col = s.column_mapping.get("color")
+                state.series_meta[series_id] = {
+                    "type": "Histogram",
+                    "agg": s.agg or "sum",
+                    "valueCols": [value_col]
+                    + ([color_col] if color_col is not None else []),
+                }
+            else:  # Candlestick / Bar
+                state.series_meta[series_id] = {
+                    "type": s.series_type,
+                    "agg": "ohlc",
+                    "valueCols": [
+                        s.column_mapping["open"],
+                        s.column_mapping["high"],
+                        s.column_mapping["low"],
+                        s.column_mapping["close"],
+                    ],
+                }
+
+        # Mixed-type tables (Histogram + Candlestick on same source) are unusual
+        # and require a single aggregated schema. We handle them by building one
+        # combined aggregated table whose schema is the superset of needed
+        # columns. For a pure-histogram or pure-OHLC table that's the typical
+        # case, this is straightforward.
+        state.aggregated_table = self._build_aggregated_table(state, series_for_table)
+        if state.aggregated_table is None:
+            return None
+        return state
+
+    def _build_aggregated_table(
+        self,
+        state: _AutoBinTableState,
+        series_for_table: list[Any],
+    ) -> Any:
+        """Build the aggregated table.
+
+        Body covers ``state.body_range_ns`` (or the full source when None)
+        at ``state.bin_width_ns``; head / tail anchors flank it at the
+        source extremes when scoped. Series sharing one source table all
+        use the same bin width and the result schema is the union of
+        needed columns.
+        """
+        types = {s.series_type for s in series_for_table}
+        if types == {"Histogram"}:
+            primary = series_for_table[0]
+            value_col = primary.column_mapping["value"]
+            color_col = primary.column_mapping.get("color")
+            return auto_bin.build_histogram_view(
+                state.raw_table,
+                state.time_col,
+                value_col,
+                state.bin_width_ns,
+                agg_mode=primary.agg or "sum",
+                color_col=color_col,
+                body_range_ns=state.body_range_ns,
+                full_range_ns=state.full_range_ns,
+            )
+        if types <= {"Candlestick", "Bar"}:
+            primary = series_for_table[0]
+            return auto_bin.build_ohlc_view(
+                state.raw_table,
+                state.time_col,
+                primary.column_mapping["open"],
+                primary.column_mapping["high"],
+                primary.column_mapping["low"],
+                primary.column_mapping["close"],
+                state.bin_width_ns,
+                body_range_ns=state.body_range_ns,
+                full_range_ns=state.full_range_ns,
+            )
+        # Mixed Histogram + OHLC on a single source table is unusual. The
+        # type-dispatch above keeps the build paths simple.
+        logger.warning(
+            "auto-bin: mixed series types on a single source table not supported; "
+            "shipping raw table for ref %s",
+            state.ref_index,
+        )
+        return None
+
+    def _series_id_for(self, series: Any) -> str:
+        """Stable series ID matching what TvlChart.to_dict assigns."""
+        # series ids are assigned by index in TvlChart.to_dict (series_<i>);
+        # we mirror that ordering here.
+        for i, s in enumerate(self._chart.series_list):
+            if s is series:
+                return f"series_{i}"
+        return ""
+
+    # ---- RETRIEVE ----
+
+    def _handle_retrieve(self) -> tuple[bytes, list[Any]]:
+        """Build and return the current figure state.
+
+        For each source table we partition its series into:
+          - auto-bin eligible (Histogram/Candlestick/Bar that pass the threshold)
+          - other (Line/Area/Baseline, or auto_bin=False)
+
+        Eligible series share a per-source-table aggregated view at a new
+        ref index. Other series continue to reference the original table.
+        """
+        self._revision += 1
+
+        tables = self._chart.get_tables()
+        series_list = self._chart.series_list
+        chart_type = self._chart.chart_type
+
+        self._autobin_states = {}
+
+        # Per-table series mapping
+        table_series_map: dict[int, list[Any]] = {}
+        for s in series_list:
+            tid = id(s.table)
+            table_series_map.setdefault(tid, []).append(s)
+
+        self._table_id_map = {}
+        exported_objects: list[Any] = []
+        new_refs: list[int] = []
+
+        # First pass: export originals at their natural ref index.
+        for i, table in enumerate(tables):
+            self._table_id_map[id(table)] = i
+            new_refs.append(i)
+            exported_objects.append(table)
+
+        # Second pass: per-source, build aggregated table for the
+        # auto-bin-eligible subset of series (if any). Series-id -> new
+        # tableId. Line / Area / Baseline siblings on the same source
+        # table keep their original tableId and are handled by the
+        # downsample path below.
+        autobin_meta: dict[str, Any] = {}
+        series_table_overrides: dict[str, int] = {}
+
+        for i, table in enumerate(tables):
+            series_for_table = table_series_map.get(id(table), [])
+            eligible_series = [
+                s
+                for s in series_for_table
+                if self._is_series_autobin_eligible(table, s, chart_type)
+            ]
+            if not eligible_series:
+                continue
+
+            agg_ref_index = len(exported_objects)
+            state = self._build_state_for_table(agg_ref_index, table, eligible_series)
+            if state is None:
+                continue
+            exported_objects.append(state.aggregated_table)
+            new_refs.append(agg_ref_index)
+            self._autobin_states[agg_ref_index] = state
+
+            # Only the autobin-eligible series read from the agg table.
+            for s in eligible_series:
+                sid = self._series_id_for(s)
+                series_table_overrides[sid] = agg_ref_index
+
+            autobin_meta[str(agg_ref_index)] = self._build_autobin_meta(state)
+
+        # Compute downsample meta for any source table whose series are
+        # downsample-eligible (Line / Area / Baseline). This includes
+        # source tables that ALSO have an autobin-eligible histogram or
+        # candlestick — both paths run side-by-side on the same source.
+        downsample_meta: dict[str, Any] = {}
+        for i, table in enumerate(tables):
+            series_for_table = table_series_map.get(id(table), [])
+            ds_series = [
+                s
+                for s in series_for_table
+                if s.series_type in DOWNSAMPLE_ELIGIBLE_TYPES
+            ]
+            if not ds_series or chart_type != "standard":
+                continue
+            if not hasattr(table, "size") or table.size <= DOWNSAMPLE_THRESHOLD:
+                continue
+
+            time_col = ds_series[0].column_mapping.get("time")
+            value_cols: set[str] = set()
+            for s in ds_series:
+                for key, col in s.column_mapping.items():
+                    if key != "time":
+                        value_cols.add(col)
+            if time_col and value_cols:
+                downsample_meta[str(i)] = {
+                    "tableSize": table.size,
+                    "timeCol": time_col,
+                    "valueCols": list(value_cols),
+                    "seriesTypes": [s.series_type for s in ds_series],
+                }
+
+        # Export PartitionedTable per series that carries `by=`. The
+        # series_id -> partitioned-table refIndex is patched into the
+        # figure's per-series "partition" block below.
+        partition_ref_indices: dict[str, int] = {}
+        for i, s in enumerate(self._chart.series_list):
+            if s.partitioned_table is None:
+                continue
+            ref_index = len(exported_objects)
+            exported_objects.append(s.partitioned_table)
+            new_refs.append(ref_index)
+            partition_ref_indices[f"series_{i}"] = ref_index
+
+        # Serialize figure (using original table_id_map), then patch the
+        # auto-binned series' dataMapping.tableId to the aggregated ref.
+        figure_data = self._chart.to_dict(self._table_id_map)
+        if series_table_overrides:
+            for s_dict in figure_data.get("series", []):
+                sid = s_dict.get("id")
+                if sid in series_table_overrides:
+                    s_dict["dataMapping"]["tableId"] = series_table_overrides[sid]
+
+        if partition_ref_indices:
+            for s_dict in figure_data.get("series", []):
+                sid = s_dict.get("id")
+                if sid in partition_ref_indices and "partition" in s_dict:
+                    s_dict["partition"]["refIndex"] = partition_ref_indices[sid]
+
+        if downsample_meta:
+            figure_data["downsampleMeta"] = downsample_meta
+        if autobin_meta:
+            figure_data["autoBinMeta"] = autobin_meta
+
+        message = json.dumps(
+            {
+                "type": "NEW_FIGURE",
+                "figure": figure_data,
+                "revision": self._revision,
+                "new_references": new_refs,
+                "removed_references": [],
+            }
+        ).encode("utf-8")
+
+        return message, exported_objects
+
+    @staticmethod
+    def _build_autobin_meta(state: _AutoBinTableState) -> dict[str, Any]:
+        return {
+            "timeCol": state.time_col,
+            "binWidthNs": state.bin_width_ns,
+            "fullRangeNs": [state.full_range_ns[0], state.full_range_ns[1]],
+            "targetBins": state.target_bins,
+            "series": state.series_meta,
+        }
+
+    # ---- AUTOBIN_ZOOM / AUTOBIN_RESET ----
+
+    def _bin_width_for_visible(
+        self,
+        from_ns: int,
+        to_ns: int,
+        target_bins: int,
+    ) -> int:
+        """Return the bin width to use for a visible window of ``target_bins`` bars.
+
+        Bin width comes directly from ``visible_ns / target_bins`` snapped
+        to the nearest nice duration — pan and zoom both refresh it. The
+        old min/max-visible-bins thresholds are gone: the body now only
+        covers the visible window, so its bar count is always close to
+        ``target_bins`` by construction.
+        """
+        if to_ns <= from_ns:
+            return 1
+        visible_ns = to_ns - from_ns
+        return auto_bin.nice_bin_width(visible_ns, target_bins)
+
+    def _apply_width_px(
+        self, state: _AutoBinTableState, message: dict[str, Any]
+    ) -> int:
+        """If the client supplied widthPx, refresh state.target_bins from it.
+
+        ``widthPx`` is the rounded (cache-friendly) chart width.
+        ``actualWidthPx`` is the real chart width and acts as a floor so that
+        bars are at least ``MIN_BAR_PX`` pixels wide regardless of rounding
+        overshoot.
+
+        Returns the effective target_bins for this operation.
+        """
+
+        def _coerce(value: Any) -> Optional[int]:
+            try:
+                return int(value) if value is not None else None
+            except (ValueError, TypeError):
+                return None
+
+        width_int = _coerce(message.get("widthPx"))
+        actual_int = _coerce(message.get("actualWidthPx"))
+        if width_int is not None and width_int > 0:
+            state.target_bins = auto_bin.target_bins_for_width(
+                width_int, actual_width_px=actual_int
+            )
+        return state.target_bins
+
+    def _handle_autobin_zoom(self, message: dict[str, Any]) -> tuple[bytes, list[Any]]:
+        """Rebuild the aggregation for a (possibly scoped) visible window.
+
+        Pan and zoom both flow through here. Bin width is derived from
+        ``visible_ns / target_bins`` so it tracks the user's window. The
+        body covers the visible window; head/tail anchors flank it.
+
+        ``atLiveEdge`` extends the body's right bound to ``MAX_LONG`` so
+        ticks landing past the visible window's right edge fall into the
+        body's last bin (rather than into the tail anchor).
+        """
+        try:
+            ref_index = int(message["tableRef"])
+            from_ns = int(message["fromNs"])
+            to_ns = int(message["toNs"])
+        except (KeyError, ValueError, TypeError):
+            return b"", []
+
+        state = self._autobin_states.get(ref_index)
+        if state is None:
+            return b"", []
+
+        target_bins = self._apply_width_px(state, message)
+        new_width = self._bin_width_for_visible(from_ns, to_ns, target_bins)
+        at_live_edge = bool(message.get("atLiveEdge"))
+        body_to = (1 << 63) - 1 if at_live_edge else to_ns
+        new_body_range: tuple[int, int] = (from_ns, body_to)
+
+        if new_width == state.bin_width_ns and state.body_range_ns == new_body_range:
+            return self._autobin_ack(state)
+        return self._rebuild(state, new_width, new_body_range)
+
+    def _handle_autobin_reset(self, message: dict[str, Any]) -> tuple[bytes, list[Any]]:
+        try:
+            ref_index = int(message["tableRef"])
+        except (KeyError, ValueError, TypeError):
+            return b"", []
+        state = self._autobin_states.get(ref_index)
+        if state is None:
+            return b"", []
+        # If the client sent a widthPx, recompute the initial bin width at
+        # that target. This lets a chart that just learned its real width
+        # refine the initial render (otherwise the constant-default
+        # TARGET_BINS is used).
+        target_bins = self._apply_width_px(state, message)
+        full_range_ns = max(1, state.full_range_ns[1] - state.full_range_ns[0])
+        new_initial = auto_bin.nice_bin_width(full_range_ns, target_bins)
+        state.initial_bin_width_ns = new_initial
+        if state.bin_width_ns == new_initial and state.body_range_ns is None:
+            return self._autobin_ack(state)
+        return self._rebuild(state, new_initial, None)
+
+    def _series_for_state(self, state: _AutoBinTableState) -> list[Any]:
+        chart_type = self._chart.chart_type
+        return [
+            s
+            for s in self._chart.series_list
+            if id(s.table) == id(state.raw_table)
+            and self._is_series_autobin_eligible(state.raw_table, s, chart_type)
+        ]
+
+    def _rebuild(
+        self,
+        state: _AutoBinTableState,
+        new_width_ns: int,
+        new_body_range: Optional[tuple[int, int]],
+    ) -> tuple[bytes, list[Any]]:
+        """Rebuild the aggregated table at ``new_width_ns`` /
+        ``new_body_range`` and emit AUTOBIN_FIGURE. Pan and zoom both
+        flow through here.
+        """
+        old_table = state.aggregated_table
+        old_width = state.bin_width_ns
+        old_body = state.body_range_ns
+        state.bin_width_ns = new_width_ns
+        state.body_range_ns = new_body_range
+        state.aggregated_table = self._build_aggregated_table(
+            state, self._series_for_state(state)
+        )
+        if state.aggregated_table is None:
+            state.aggregated_table = old_table
+            state.bin_width_ns = old_width
+            state.body_range_ns = old_body
+            return b"", []
+
+        self._revision += 1
+
+        # Reconstruct the exported objects list: originals at their natural
+        # refs, aggregated tables at their (post-original) refs.
+        tables = self._chart.get_tables()
+        partitioned_tables = [
+            s.partitioned_table
+            for s in self._chart.series_list
+            if s.partitioned_table is not None
+        ]
+        max_ref = max(self._autobin_states.keys(), default=len(tables) - 1)
+        if partitioned_tables:
+            max_ref = max(max_ref, max_ref + len(partitioned_tables))
+        size_needed = max_ref + 1
+        exported_objects: list[Any] = [None] * size_needed
+        new_refs: list[int] = []
+
+        for i, table in enumerate(tables):
+            exported_objects[i] = table
+            new_refs.append(i)
+        for ref_index, st in self._autobin_states.items():
+            exported_objects[ref_index] = st.aggregated_table
+            new_refs.append(ref_index)
+
+        for pt in partitioned_tables:
+            pt_ref = len(exported_objects)
+            exported_objects.append(pt)
+            new_refs.append(pt_ref)
+
+        meta = {
+            str(ref): self._build_autobin_meta(st)
+            for ref, st in self._autobin_states.items()
+        }
+
+        message = json.dumps(
+            {
+                "type": "AUTOBIN_FIGURE",
+                "revision": self._revision,
+                "tableRef": state.ref_index,
+                "binWidthNs": state.bin_width_ns,
+                "autoBinMeta": meta,
+                "new_references": new_refs,
+            }
+        ).encode("utf-8")
+
+        return message, exported_objects
+
+    def _autobin_ack(self, state: _AutoBinTableState) -> tuple[bytes, list[Any]]:
+        """Send a no-op AUTOBIN_FIGURE so the client can clear pending state."""
+        message = json.dumps(
+            {
+                "type": "AUTOBIN_FIGURE",
+                "revision": self._revision,
+                "tableRef": state.ref_index,
+                "binWidthNs": state.bin_width_ns,
+                "autoBinMeta": {
+                    str(i): self._build_autobin_meta(st)
+                    for i, st in self._autobin_states.items()
+                },
+                "noop": True,
+                "new_references": [],
+            }
+        ).encode("utf-8")
+        return message, []
+
+    def close(self) -> None:
+        """Clean up resources."""
+        self._autobin_states.clear()
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/data.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/data.py
new file mode 100644
index 000000000..d72d6b6ec
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/data.py
@@ -0,0 +1,518 @@
+"""Deterministic example-data tables for TradingView Lightweight charts.
+
+Mirrors :mod:`deephaven.plot.express.data`: every function returns a fresh,
+deterministic :class:`deephaven.table.Table` for docs examples and snapshot
+tests. Generators produce realistic-looking market data via deterministic
+random walks (geometric-Brownian-motion style) rather than closed-form
+sine waves, so charts have visible structure without being noisy.
+
+Each function takes a ``ticking`` argument. When ``ticking=True`` (default)
+the table seeds with an initial static block and a ``time_table`` appends
+new rows every second. When ``ticking=False`` the static block is returned
+on its own. The env var ``DEEPHAVEN_PLUGINS_STATIC_DATA=1`` forces every
+generator into static mode regardless of the argument; the docs snapshotter
+sets it so captured PNGs are reproducible.
+
+Typical usage::
+
+    from deephaven.plot import tradingview_lightweight as tvl
+
+    t = tvl.data.ohlc()
+    chart = tvl.candlestick(t, timestamp="Timestamp", open="Open", high="High",
+                            low="Low", close="Close")
+"""
+
+from __future__ import annotations
+
+import math
+import os
+from random import Random
+
+from deephaven import empty_table, time_table, merge
+from deephaven.table import Table
+from deephaven.time import to_j_instant
+from deephaven.updateby import ema_tick, rolling_sum_tick
+
+
+__all__ = [
+    "ohlc",
+    "stocks",
+    "volume",
+    "yields",
+    "options_chain",
+    "values",
+    "large_prices",
+]
+
+
+# Only SECOND is exported as a Python constant — it fits comfortably in a
+# Java int and matches dx.data's convention. MINUTE/HOUR/DAY are NOT
+# defined here: DH provides them as built-in `long` constants inside formula
+# scope, and shadowing them with Python ints overflows the formula compiler.
+SECOND = 1_000_000_000
+
+STARTING_TIME = "2024-01-01T09:30:00 ET"
+
+
+def _resolve_ticking(ticking: bool) -> bool:
+    """Apply the ``DEEPHAVEN_PLUGINS_STATIC_DATA=1`` global override."""
+    if os.environ.get("DEEPHAVEN_PLUGINS_STATIC_DATA") == "1":
+        return False
+    return ticking
+
+
+def _seeded(base_rows: int, ticking: bool) -> "Table":
+    """Return a static-only or static-plus-ticking index table.
+
+    The result has a single ``Index`` column counting from zero. When
+    ``ticking`` is true, ``time_table("PT1S")`` continues to append rows
+    indexed ``base_rows, base_rows + 1, ...``.
+    """
+    static = empty_table(base_rows).update("Index = ii")
+    if not ticking:
+        return static
+    return merge(
+        [
+            static,
+            time_table("PT1S")
+            .update(f"Index = ii + {base_rows}")
+            .drop_columns("Timestamp"),
+        ]
+    )
+
+
+def ohlc(ticking: bool = True) -> "Table":
+    """Build a daily OHLCV candle series from a deterministic price walk.
+
+    Each row represents one trading day starting 2024-01-01. The price path
+    is a smoothed random walk (windowed cumulative sum of Gaussian log-returns
+    plus an EMA), giving visible trends and reversals instead of a pure sine.
+    High/Low straddle Open/Close by an absolute-Gaussian intra-bar range, and
+    volume swells with absolute return so big moves print big bars.
+
+    Args:
+        ticking: If true (default), the seed block is followed by one new
+            candle per second. If false, only the static seed is returned.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Timestamp`` (Instant): daily timestamps from 2024-01-01.
+        - ``Open`` (double): opening price.
+        - ``High`` (double): high price, ≥ max(Open, Close).
+        - ``Low`` (double): low price, ≤ min(Open, Close).
+        - ``Close`` (double): closing price.
+        - ``Volume`` (long): bar volume; correlates with |return|.
+        - ``Ema`` (double): 20-tick EMA of ``Close``, for overlay examples.
+    """
+    base_time = to_j_instant(STARTING_TIME)
+    base_rows = 90
+    init_price = 100.0
+
+    def gauss(seed: int) -> float:
+        return Random(seed).gauss(0.0, 1.0)
+
+    def lognorm(seed: int) -> float:
+        return Random(seed).lognormvariate(0.0, 0.5)
+
+    return (
+        _seeded(base_rows, _resolve_ticking(ticking))
+        .update(
+            [
+                "Timestamp = base_time + (long)(Index * DAY)",
+                "Step = (double)gauss((int)(Index + 1))",
+            ]
+        )
+        .update_by(
+            ops=[rolling_sum_tick(cols=["Drift = Step"], rev_ticks=20, fwd_ticks=0)]
+        )
+        .update_by(ops=[ema_tick(decay_ticks=5, cols=["Smooth = Drift"])])
+        .update(
+            [
+                "Mid = init_price + Smooth * 2.0",
+                "BarStep = (double)gauss((int)(Index + 11)) * 0.8",
+                "Range = (double)Math.abs(gauss((int)(Index + 7))) * 1.5 + 0.4",
+                "Open = Mid",
+                "Close = Mid + BarStep",
+                "High = Math.max(Open, Close) + Range",
+                "Low = Math.min(Open, Close) - Range",
+                "Volume = (long)Math.max(50.0, 1000.0 + Math.abs(BarStep) * 800.0 "
+                "+ (double)lognorm((int)(Index + 13)) * 300.0)",
+            ]
+        )
+        .update_by(ops=[ema_tick(decay_ticks=20, cols=["Ema = Close"])])
+        .view(["Timestamp", "Open", "High", "Low", "Close", "Volume", "Ema"])
+    )
+
+
+def stocks(ticking: bool = True) -> "Table":
+    """Build a multi-symbol trades table with per-symbol price walks.
+
+    Three symbols (``AAA``, ``BBB``, ``CCC``) tick in round-robin. Each
+    symbol has an independent random walk anchored at a distinct base
+    price (90, 140, 60) with its own volatility, so by-grouped chart
+    examples (line/area/baseline) show three visually distinct series.
+
+    Args:
+        ticking: If true (default), trades tick in once per second after
+            an initial 120-row seed. If false, only the static seed is
+            returned.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Timestamp`` (Instant): daily timestamps from 2024-01-01.
+        - ``Sym`` (string): one of ``"AAA"``, ``"BBB"``, ``"CCC"``.
+        - ``Price`` (double): symbol-dependent price walk.
+        - ``Size`` (long): trade size; lognormal-ish, ~100 +/- 50.
+    """
+    base_time = to_j_instant(STARTING_TIME)
+    base_rows = 360
+
+    syms = ["AAA", "BBB", "CCC"]
+    sym_bases = {"AAA": 90.0, "BBB": 140.0, "CCC": 60.0}
+    sym_vols = {"AAA": 1.6, "BBB": 2.8, "CCC": 1.0}
+
+    def pick_sym(seed: int) -> str:
+        return syms[seed % 3]
+
+    def sym_step(sym: str, seed: int) -> float:
+        return Random(seed * 7 + hash(sym) % 1000).gauss(0.0, sym_vols[sym])
+
+    def sym_base(sym: str) -> float:
+        return sym_bases[sym]
+
+    def size_lognorm(seed: int) -> int:
+        return max(1, int(round(Random(seed).lognormvariate(4.0, 0.6))))
+
+    return (
+        _seeded(base_rows, _resolve_ticking(ticking))
+        .update(
+            [
+                "Timestamp = base_time + (long)(Index * DAY)",
+                "Sym = (String)pick_sym((int)Index)",
+                "Step = (double)sym_step(Sym, (int)(Index + 3))",
+            ]
+        )
+        .update_by(
+            ops=[rolling_sum_tick(cols=["Drift = Step"], rev_ticks=30, fwd_ticks=0)],
+            by=["Sym"],
+        )
+        .update_by(
+            ops=[ema_tick(decay_ticks=3, cols=["Smooth = Drift"])],
+            by=["Sym"],
+        )
+        .update(
+            [
+                "Price = (double)sym_base(Sym) + Smooth",
+                "Size = (long)size_lognorm((int)(Index + 17))",
+            ]
+        )
+        .view(["Timestamp", "Sym", "Price", "Size"])
+    )
+
+
+def volume(ticking: bool = True) -> "Table":
+    """Build a standalone daily volume series with weekly seasonality.
+
+    Designed for the histogram example. The volume curve is a lognormal
+    base scaled by a weekday-of-week factor (Mondays/Fridays heavier),
+    so the histogram has visible structure beyond pure noise.
+
+    Args:
+        ticking: If true (default), one new bar ticks in per second after
+            the 60-row seed. If false, only the static seed is returned.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Timestamp`` (Instant): daily timestamps from 2024-01-01.
+        - ``Volume`` (long): daily volume, lognormal w/ weekly seasonality.
+    """
+    base_time = to_j_instant(STARTING_TIME)
+    base_rows = 60
+
+    # Mon..Sun multipliers; weekends omitted from the synthetic feed.
+    weekday_mult = [1.4, 0.9, 0.85, 0.95, 1.3]
+
+    def weekday_factor(idx: int) -> float:
+        return weekday_mult[idx % 5]
+
+    def vol_noise(seed: int) -> float:
+        return Random(seed).lognormvariate(0.0, 0.35)
+
+    return (
+        _seeded(base_rows, _resolve_ticking(ticking))
+        .update(
+            [
+                "Timestamp = base_time + (long)(Index * DAY)",
+                "Volume = (long)Math.max(50.0, 1000.0 "
+                "* (double)weekday_factor((int)Index) "
+                "* (double)vol_noise((int)(Index + 23)))",
+            ]
+        )
+        .view(["Timestamp", "Volume"])
+    )
+
+
+def yields(ticking: bool = True) -> "Table":
+    """Build an 11-point Treasury yield-curve snapshot.
+
+    Tenors follow the canonical Treasury set (3M, 6M, 1Y, 2Y, 3Y, 5Y, 7Y,
+    10Y, 20Y, 30Y, 40Y) and are emitted **in months** (3, 6, 12, 24, 36,
+    60, 84, 120, 240, 360, 480) — the unit LWC's ``createYieldCurveChart``
+    expects on its maturity axis. The yields use a Nelson-Siegel-style mix
+    of level, slope, and curvature factors, producing a normal
+    upward-sloping curve with a belly peak.
+
+    In ticking mode a single replacement curve emits each second with the
+    factors perturbed by small Gaussians, so the chart redraws a slowly
+    drifting curve over time. ``last_by("Tenor")`` keeps the row count flat.
+
+    Args:
+        ticking: If true (default), the curve updates once per second.
+            If false, a single static snapshot is returned.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Tenor`` (double): months to maturity.
+        - ``Yield`` (double): yield in percent.
+    """
+    tenors = [3.0, 6.0, 12.0, 24.0, 36.0, 60.0, 84.0, 120.0, 240.0, 360.0, 480.0]
+
+    def tenor_at(i: int) -> float:
+        return tenors[i % len(tenors)]
+
+    # Nelson-Siegel level/slope/curvature with a small per-tick drift.
+    # `decay` is in years; convert tenor (months) to years inside yield_at.
+    def curve_factor(seed: int, idx: int) -> tuple[float, float, float, float]:
+        r = Random(seed)
+        level = 4.0 + r.gauss(0.0, 0.05)
+        slope = -2.0 + r.gauss(0.0, 0.05)
+        curv = 2.0 + r.gauss(0.0, 0.05)
+        decay = 1.5
+        return level, slope, curv, decay
+
+    def yield_at(tenor: float, seed: int, idx: int) -> float:
+        level, slope, curv, decay = curve_factor(seed, idx)
+        tenor_y = tenor / 12.0
+        if tenor_y <= 0:
+            return level + slope + curv
+        x = tenor_y / decay
+        expx = math.exp(-x)
+        factor1 = (1.0 - expx) / x
+        factor2 = factor1 - expx
+        return round(level + slope * factor1 + curv * factor2, 3)
+
+    static = empty_table(len(tenors)).update(
+        [
+            "Tenor = (double)tenor_at((int)ii)",
+            "Yield = (double)yield_at(Tenor, 0, (int)ii)",
+        ]
+    )
+
+    if not _resolve_ticking(ticking):
+        return static
+
+    ticking_curve = (
+        time_table("PT1S")
+        .update(
+            [
+                "Bucket = ii % 11",
+                "Tenor = (double)tenor_at((int)Bucket)",
+                "Yield = (double)yield_at(Tenor, (int)(ii / 11) + 1, (int)Bucket)",
+            ]
+        )
+        .drop_columns(["Timestamp", "Bucket"])
+        .last_by("Tenor")
+    )
+
+    return merge([static, ticking_curve]).last_by("Tenor")
+
+
+def options_chain(ticking: bool = True) -> "Table":
+    """Build a 21-strike options chain with a Black-Scholes-flavored smile.
+
+    Strikes step by 5 from 50 to 150 (ATM = 100). Call and put mid prices
+    follow intrinsic value plus a Gaussian-shaped time premium centered on
+    the spot; bid/ask spreads widen at the wings to mimic real chains.
+    A small volatility smile pushes wing IVs above the ATM IV.
+
+    In ticking mode the chain refreshes every second with the spot drifting
+    via a smoothed random walk, so the smile and intrinsic legs slide
+    together.
+
+    Args:
+        ticking: If true (default), the chain refreshes once per second.
+            If false, a single static snapshot at spot=100 is returned.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Strike`` (double): strike price, 50..150 by 5.
+        - ``CallBid`` (double): call bid price.
+        - ``CallAsk`` (double): call ask price.
+        - ``PutBid`` (double): put bid price.
+        - ``PutAsk`` (double): put ask price.
+    """
+    strike_count = 21
+
+    def strike_at(i: int) -> float:
+        return 50.0 + (i % strike_count) * 5.0
+
+    def spot_at(seed: int) -> float:
+        # Smooth drift around 100 for the ticking case; deterministic per second.
+        steps = [Random(s).gauss(0.0, 0.4) for s in range(seed + 1)]
+        return round(100.0 + sum(steps[-40:]), 2)
+
+    def smile_iv(strike: float, spot: float) -> float:
+        moneyness = (strike - spot) / spot
+        return 0.22 + 0.6 * moneyness * moneyness
+
+    def call_mid(strike: float, spot: float) -> float:
+        intrinsic = max(0.0, spot - strike)
+        time_value = 6.0 * math.exp(-((strike - spot) ** 2) / 600.0)
+        return round(intrinsic + time_value * (1.0 + smile_iv(strike, spot) * 0.4), 2)
+
+    def put_mid(strike: float, spot: float) -> float:
+        intrinsic = max(0.0, strike - spot)
+        time_value = 6.0 * math.exp(-((strike - spot) ** 2) / 600.0)
+        return round(intrinsic + time_value * (1.0 + smile_iv(strike, spot) * 0.4), 2)
+
+    def half_spread(strike: float, spot: float) -> float:
+        moneyness = abs(strike - spot) / spot
+        return round(0.1 + 0.6 * moneyness, 3)
+
+    static = (
+        empty_table(strike_count)
+        .update(
+            [
+                "Strike = (double)strike_at((int)ii)",
+                "Spot = 100.0",
+                "CallMid = (double)call_mid(Strike, Spot)",
+                "PutMid = (double)put_mid(Strike, Spot)",
+                "Spread = (double)half_spread(Strike, Spot)",
+                "CallBid = CallMid - Spread",
+                "CallAsk = CallMid + Spread",
+                "PutBid = PutMid - Spread",
+                "PutAsk = PutMid + Spread",
+            ]
+        )
+        .view(["Strike", "CallBid", "CallAsk", "PutBid", "PutAsk"])
+    )
+
+    if not _resolve_ticking(ticking):
+        return static
+
+    ticking_chain = (
+        time_table("PT1S")
+        .update(
+            [
+                "Bucket = ii % 21",
+                "Strike = (double)strike_at((int)Bucket)",
+                "Spot = (double)spot_at((int)(ii / 21))",
+                "CallMid = (double)call_mid(Strike, Spot)",
+                "PutMid = (double)put_mid(Strike, Spot)",
+                "Spread = (double)half_spread(Strike, Spot)",
+                "CallBid = CallMid - Spread",
+                "CallAsk = CallMid + Spread",
+                "PutBid = PutMid - Spread",
+                "PutAsk = PutMid + Spread",
+            ]
+        )
+        .drop_columns("Timestamp")
+        .last_by("Strike")
+        .view(["Strike", "CallBid", "CallAsk", "PutBid", "PutAsk"])
+    )
+
+    return merge([static, ticking_chain]).last_by("Strike")
+
+
+def values(ticking: bool = True) -> "Table":
+    """Build a single-value time series with visible structure.
+
+    Designed for the simplest line/area/baseline/histogram example pages.
+    The series is a smoothed random walk (Gaussian steps + EMA), so it
+    has runs, reversals, and consolidations — readable shape but not
+    pure noise.
+
+    Args:
+        ticking: If true (default), one new sample ticks in per second
+            after the 90-row seed. If false, only the static seed is
+            returned.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Timestamp`` (Instant): daily timestamps from 2024-01-01.
+        - ``Value`` (double): smoothed walk centered at ~100.
+    """
+    base_time = to_j_instant(STARTING_TIME)
+    base_rows = 90
+
+    def gauss(seed: int) -> float:
+        return Random(seed).gauss(0.0, 1.0)
+
+    return (
+        _seeded(base_rows, _resolve_ticking(ticking))
+        .update(
+            [
+                "Timestamp = base_time + (long)(Index * DAY)",
+                "Step = (double)gauss((int)(Index + 31))",
+            ]
+        )
+        .update_by(
+            ops=[rolling_sum_tick(cols=["Drift = Step"], rev_ticks=25, fwd_ticks=0)]
+        )
+        .update_by(ops=[ema_tick(decay_ticks=6, cols=["Smooth = Drift"])])
+        .update("Value = 100.0 + Smooth * 3.0")
+        .view(["Timestamp", "Value"])
+    )
+
+
+def large_prices(ticking: bool = True) -> "Table":
+    """Build a 1,000,000-row intraday price series for the downsampling demos.
+
+    Timestamps step uniformly so 1M rows cover ~10 years (~315 seconds per
+    row). The price curve combines a low-frequency drift (cumulative sum of
+    small Gaussians) with a higher-frequency wiggle, giving the downsampler
+    structure to thin without making the chart look noisy.
+
+    Args:
+        ticking: If true (default), additional rows tick in once per second
+            after the 1M-row seed. If false, only the static seed is
+            returned. Note that 1M static + ticking is a large table —
+            prefer ``ticking=False`` for the downsample comparison demo.
+
+    Returns:
+        A :class:`deephaven.table.Table` with columns:
+
+        - ``Timestamp`` (Instant): ~315-second spaced timestamps from 2020-01-01.
+        - ``Price`` (double): smoothed walk centered at ~100.
+    """
+    base_rows = 1_000_000
+    # ~315 seconds = 10 years / 1M rows. Inlined as a Java long literal in
+    # the formula below to avoid the Python-int-overflows-Java-int trap.
+    STEP_NANOS_LITERAL = "315360000000L"
+
+    def gauss(seed: int) -> float:
+        return Random(seed).gauss(0.0, 1.0)
+
+    return (
+        _seeded(base_rows, _resolve_ticking(ticking))
+        .update(
+            [
+                f"Timestamp = '2020-01-01T00:00:00Z' + (long)(Index * {STEP_NANOS_LITERAL})",
+                "Step = (double)gauss((int)(Index + 47))",
+            ]
+        )
+        .update_by(
+            ops=[rolling_sum_tick(cols=["Drift = Step"], rev_ticks=5000, fwd_ticks=0)]
+        )
+        .update_by(ops=[ema_tick(decay_ticks=100, cols=["Smooth = Drift"])])
+        .update(
+            "Price = 100.0 + Smooth * 0.6 + (double)gauss((int)(Index + 991)) * 2.0"
+        )
+        .view(["Timestamp", "Price"])
+    )
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/events.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/events.py
new file mode 100644
index 000000000..7d662f29c
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/events.py
@@ -0,0 +1,262 @@
+"""Event payloads and handler plumbing for TvlChart press events.
+
+This mirrors the deephaven.ui event convention: a handler is a plain Python
+callable that receives a single event argument (a ``TvlPressEvent`` dict with
+camelCase keys), or no argument at all. :func:`wrap_callable` adapts a handler
+so the dispatcher can always call it with one positional argument regardless of
+how many the handler actually declares.
+
+Only ``on_press`` / ``on_double_press`` are supported in v1.
+"""
+
+from __future__ import annotations
+
+import sys
+from datetime import datetime, timedelta, timezone
+from functools import partial
+from inspect import signature
+from typing import Any, Callable, Literal, Optional, TypedDict, Union, cast
+
+_NS_PER_SECOND = 1_000_000_000
+
+# Public handler ids advertised to the client in ``enabledHandlers``.
+PRESS = "press"
+DOUBLE_PRESS = "doublePress"
+
+PressEventType = Literal["press", "doublePress"]
+
+
+class TvlPressEvent(TypedDict, total=False):
+    """A press (or double-press) on a rendered TVL chart.
+
+    This mirrors lightweight-charts' ``MouseEventParams`` — the data of every
+    series at the event location, the hovered series, the pixel point, the
+    logical index, the pane, and the modifier keys — rather than a bespoke
+    model. Keys are camelCase to match both that upstream type and
+    deephaven.ui's ``events.py`` (whose ``PressEvent`` uses ``shiftKey`` etc.).
+    The event is a plain ``dict`` at runtime, so handlers read fields with
+    ``e["seriesData"]``.
+
+    Two deliberate deviations from the raw ``MouseEventParams``: the hovered
+    ``ISeriesApi`` object becomes a string id (``hoveredSeries`` /
+    ``hoveredSeriesId``), and ``time`` becomes a Deephaven ``timestamp``.
+
+    Fields that cannot be resolved for a given press are omitted rather than
+    set to ``None`` (e.g. pressing empty area outside the data range omits
+    ``timestamp`` and ``hoveredSeries``).
+    """
+
+    type: PressEventType
+    """``"press"`` or ``"doublePress"``."""
+
+    timestamp: Any
+    """Time of the data at the event location (``MouseEventParams.time``),
+    mirroring the hovered series' time-column type: a Deephaven ``Instant`` for
+    an ``Instant`` column, a ``ZonedDateTime`` (in the chart's displayed zone)
+    for a ``ZonedDateTime`` column, and a timezone-aware UTC ``datetime`` as the
+    fallback. Absent when the event is outside the data range."""
+
+    hoveredSeries: str
+    """Friendly id of the series under the cursor. Uses the rendered series
+    title when present (``by=`` charts use the partition key as the runtime
+    title), falling back to TVL's generated ``series_<n>`` id only when no
+    title/key exists. Omitted when no series is hovered. This is the key into
+    :attr:`seriesData`."""
+
+    hoveredSeriesId: str
+    """TVL's generated ``series_<n>`` id for the hovered series — a stable
+    handle that does not change with title/key, for unambiguous server-side
+    lookup. Omitted when no series is hovered."""
+
+    seriesData: dict
+    """Data of every series at the event location, keyed by friendly series id
+    (matching :attr:`hoveredSeries`). Each value mirrors the series' data
+    shape: ``{"value": ...}`` for line / area / baseline / histogram, or
+    ``{"open", "high", "low", "close"}`` for candlestick / bar."""
+
+    point: dict
+    """Pixel location of the event as ``{"x": ..., "y": ...}``
+    (``MouseEventParams.point``). Omitted when outside the chart."""
+
+    logical: int
+    """Logical index at the event location (``MouseEventParams.logical``)."""
+
+    paneIndex: int
+    """Index of the pane the event occurred in, when available."""
+
+    shiftKey: bool
+    ctrlKey: bool
+    metaKey: bool
+    altKey: bool
+
+
+# A handler takes the event dict, or nothing at all.
+PressEventCallable = Union[Callable[[TvlPressEvent], None], Callable[[], None]]
+
+
+def ns_to_datetime(time_ns: int) -> datetime:
+    """Convert UTC epoch nanoseconds to a timezone-aware UTC ``datetime``.
+
+    Seconds and sub-second nanos are split so the conversion is exact to
+    microsecond resolution (``datetime`` cannot hold nanoseconds; the
+    remaining nanos are truncated). The client sends ``timeNs`` already
+    shifted back to real UTC (its ``unconvertTime`` undoes the display-tz
+    offset), so no timezone math happens here.
+
+    Used as the fallback when the source time-column type is unknown or a
+    Deephaven date type cannot be built (see :func:`time_converter_for`).
+    """
+    seconds, sub_ns = divmod(int(time_ns), _NS_PER_SECOND)
+    base = datetime.fromtimestamp(seconds, tz=timezone.utc)
+    return base + timedelta(microseconds=sub_ns // 1000)
+
+
+def ns_to_instant(time_ns: int) -> Any:
+    """Convert UTC epoch nanoseconds to a Deephaven ``Instant``.
+
+    ``deephaven.time`` is imported lazily so this module still imports
+    without a running server (the conversion itself needs the JVM).
+    """
+    from deephaven.time import to_j_instant
+
+    return to_j_instant(int(time_ns))
+
+
+def ns_to_zoned_date_time(time_ns: int, time_zone: Optional[str] = None) -> Any:
+    """Convert UTC epoch nanoseconds to a Deephaven ``ZonedDateTime``.
+
+    The press travels over the wire as a plain UTC instant, so the source
+    column's original per-row zone is not recoverable. We reconstruct the
+    value in ``time_zone`` — the IANA zone the chart rendered in — falling
+    back to the Deephaven system zone when the client did not send one. This
+    matches what the user saw on the time axis.
+    """
+    from deephaven.dtypes import ZonedDateTime
+    from deephaven.time import dh_time_zone, to_j_instant, to_j_time_zone
+
+    instant = to_j_instant(int(time_ns))
+    zone = to_j_time_zone(time_zone) if time_zone else dh_time_zone()
+    return ZonedDateTime.j_type.ofInstant(instant, zone)  # type: ignore[attr-defined]
+
+
+# Fully-qualified Java class names of the source time column's dtype
+# (``DType.j_name``) that we mirror onto the event ``timestamp``.
+_INSTANT_JNAME = "java.time.Instant"
+_ZONED_DATE_TIME_JNAME = "java.time.ZonedDateTime"
+
+
+def time_converter_for(
+    time_type_name: Optional[str], time_zone: Optional[str] = None
+) -> Callable[[int], Any]:
+    """Pick a ``nanos -> value`` converter that mirrors the source column type.
+
+    ``time_type_name`` is the source time column's ``DType.j_name`` (or
+    ``None`` when it could not be resolved):
+
+    - ``java.time.Instant``       -> Deephaven ``Instant``
+    - ``java.time.ZonedDateTime`` -> Deephaven ``ZonedDateTime`` (in ``time_zone``)
+    - anything else / ``None``    -> timezone-aware UTC ``datetime`` (fallback)
+    """
+    if time_type_name == _INSTANT_JNAME:
+        return ns_to_instant
+    if time_type_name == _ZONED_DATE_TIME_JNAME:
+        return lambda ns: ns_to_zoned_date_time(ns, time_zone)
+    return ns_to_datetime
+
+
+_MODIFIER_KEYS = ("shiftKey", "ctrlKey", "metaKey", "altKey")
+
+# Optional fields copied through verbatim when present (camelCase, mirroring
+# the wire payload and deephaven.ui's event convention).
+_PASSTHROUGH_KEYS = (
+    "hoveredSeries",
+    "hoveredSeriesId",
+    "seriesData",
+    "point",
+    "logical",
+    "paneIndex",
+)
+
+
+def build_press_event(
+    handler_id: str,
+    payload: dict,
+    time_converter: Callable[[int], Any] = ns_to_datetime,
+) -> "TvlPressEvent":
+    """Build a :class:`TvlPressEvent` from the client EVENT payload.
+
+    The client payload mirrors lightweight-charts' ``MouseEventParams`` and is
+    already camelCase, matching the event dict handlers consume.
+
+    ``handler_id`` is ``"press"`` or ``"doublePress"`` and becomes the
+    event ``type``. Optional fields (``hoveredSeries``, ``hoveredSeriesId``,
+    ``seriesData``, ``point``, ``logical``, ``paneIndex``) are copied through
+    only when present; ``timeNs`` is converted to ``timestamp`` via
+    ``time_converter`` (omitted when the event was outside the data range,
+    where the client sends no ``timeNs``). Modifier keys always resolve to a
+    bool.
+
+    ``time_converter`` lets the caller mirror the source time-column type
+    (see :func:`time_converter_for`); it defaults to a UTC ``datetime``. A
+    failing converter (e.g. a transient JVM error) degrades to ``datetime``
+    rather than raising, so a press always carries a usable ``timestamp``.
+    """
+    event: TvlPressEvent = {"type": cast(PressEventType, handler_id)}
+    for key in _MODIFIER_KEYS:
+        event[key] = bool(payload.get(key, False))  # type: ignore[literal-required]
+    for key in _PASSTHROUGH_KEYS:
+        if payload.get(key) is not None:
+            event[key] = payload[key]  # type: ignore[literal-required]
+    time_ns = payload.get("timeNs")
+    if time_ns is not None:
+        try:
+            event["timestamp"] = time_converter(time_ns)
+        except Exception:  # noqa: BLE001 - never lose the press over a bad convert
+            event["timestamp"] = ns_to_datetime(time_ns)
+    return event
+
+
+def _wrapped_callable(
+    max_args: Optional[int],
+    func: Callable,
+    *args: Any,
+) -> Any:
+    """Call ``func`` with at most ``max_args`` positional arguments.
+
+    ``max_args`` is ``None`` when the function accepts ``*args`` (pass
+    everything through).
+    """
+    if max_args is not None:
+        args = args[:max_args]
+    return func(*args)
+
+
+def wrap_callable(func: Callable) -> Callable:
+    """Adapt a handler so it can always be invoked with one positional arg.
+
+    Ported from deephaven.ui's ``_internal/utils.wrap_callable`` (positional
+    arity only — TVL handlers never receive keyword arguments). A handler
+    declaring zero parameters and one declaring a single ``event`` parameter
+    are both valid; surplus positional arguments are dropped.
+    """
+    try:
+        if sys.version_info[0] == 3 and sys.version_info[1] >= 10:
+            sig = signature(func, eval_str=True)  # type: ignore[call-arg]
+        else:
+            sig = signature(func)
+
+        max_args: Optional[int] = 0
+        for param in sig.parameters.values():
+            if param.kind in (
+                param.POSITIONAL_ONLY,
+                param.POSITIONAL_OR_KEYWORD,
+            ):
+                max_args = cast(int, max_args) + 1
+            elif param.kind == param.VAR_POSITIONAL:
+                max_args = None
+            # KEYWORD_ONLY / VAR_KEYWORD params are never supplied by the
+            # dispatcher, so they don't affect the positional budget.
+        return partial(_wrapped_callable, max_args, func)
+    except (ValueError, TypeError):
+        # Builtins and some C callables have no introspectable signature.
+        return func
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/markers.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/markers.py
new file mode 100644
index 000000000..d18409a99
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/markers.py
@@ -0,0 +1,607 @@
+"""Marker and price line helpers for TradingView Lightweight Charts."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any, Optional
+
+from .options import (
+    LineStyle,
+    LineWidth,
+    MarkerPosition,
+    MarkerShape,
+    LINE_STYLE_MAP,
+    MARKER_POSITION_MAP,
+    MARKER_SHAPE_MAP,
+)
+from ._colors import Color
+
+# camelCase (used by Marker, which stores translated values)
+_PRICE_POSITIONS_JS = {"atPriceTop", "atPriceBottom", "atPriceMiddle"}
+# snake_case (used by MarkerSpec/factories, which store Python-style values)
+_PRICE_POSITIONS_PY = {"at_price_top", "at_price_bottom", "at_price_middle"}
+
+
+@dataclass
+class Marker:
+    """A single static marker placed on a series at a specific time.
+
+    Markers render a small glyph (circle, square, arrow) anchored to
+    one data point.  For markers driven by a Deephaven table (one
+    marker per row), use :class:`MarkerSpec` / :func:`markers_from_table`
+    instead.
+
+    The ``position`` and ``shape`` fields use camelCase JS values
+    (e.g. ``"aboveBar"``, ``"arrowUp"``).  When constructing through
+    :func:`marker`, supply snake_case Python aliases (e.g.
+    ``"above_bar"``, ``"arrow_up"``); the factory translates them.
+
+    Attributes:
+        time: The time value to anchor the marker to.  May be a UTC
+            timestamp (``int`` / ``float``), an ISO date string, or
+            a :class:`BusinessDay` dict.
+        position: Anchor position in camelCase JS form (e.g.
+            ``"aboveBar"``, ``"belowBar"``, ``"inBar"``,
+            ``"atPriceTop"``, ``"atPriceBottom"``, ``"atPriceMiddle"``).
+        shape: Glyph in camelCase JS form (``"circle"``, ``"square"``,
+            ``"arrowUp"``, ``"arrowDown"``).
+        color: CSS color string for the glyph fill.
+        text: Optional label text drawn near the marker.
+        size: Glyph size multiplier (default ``1``).
+        id: Optional string identifier.
+        price: Required when ``position`` is one of the ``"atPrice*"``
+            variants; ignored otherwise.
+
+    Raises:
+        ValueError: From ``__post_init__`` if ``position`` is a
+            price-based anchor and ``price`` is not supplied.
+    """
+
+    time: Any  # str, int, or float
+    position: str = "aboveBar"
+    shape: str = "circle"
+    color: Optional[Color] = None
+    text: str = ""
+    size: Optional[int] = None
+    id: Optional[str] = None
+    price: Optional[float] = None
+
+    def __post_init__(self) -> None:
+        if (
+            self.position in _PRICE_POSITIONS_JS or self.position in _PRICE_POSITIONS_PY
+        ) and self.price is None:
+            raise ValueError(
+                f"Marker position '{self.position}' requires the 'price' field to be set."
+            )
+
+    def to_dict(self) -> dict:
+        result: dict = {
+            "time": self.time,
+            "position": self.position,
+            "shape": self.shape,
+            "text": self.text,
+        }
+        if self.color is not None:
+            result["color"] = self.color
+        if self.size is not None:
+            result["size"] = self.size
+        if self.id is not None:
+            result["id"] = self.id
+        if self.price is not None:
+            result["price"] = self.price
+        return result
+
+
+@dataclass
+class PriceLine:
+    """A horizontal price line drawn on a series.
+
+    Provide either a static ``price`` or a ``column`` name.  When
+    ``column`` is set the price line tracks the last-row value of
+    that column in the series' data table (updated live as the table
+    ticks).  Constructing through :func:`price_line` is recommended.
+
+    Attributes:
+        price: Static price level.  Mutually exclusive with ``column``.
+        column: Deephaven extension — column name in the series' data
+            table whose last-row value sets the price level
+            dynamically.  Mutually exclusive with ``price``.
+        color: Line color (CSS color string).  Also used as the axis
+            label background color unless ``axis_label_color`` is set
+            explicitly.
+        line_width: Line thickness in pixels (1–4).
+        line_style: One of ``"solid"``, ``"dotted"``, ``"dashed"``,
+            ``"large_dashed"``, ``"sparse_dotted"``.
+        line_visible: Whether the horizontal line rule is drawn.  The
+            axis label can still be shown even when
+            ``line_visible=False``.
+        axis_label_visible: Whether the axis label is shown on the
+            price scale.
+        title: Short text label drawn on the chart pane next to the
+            line.
+        axis_label_color: Background color of the price-scale axis
+            label.  Defaults to the line ``color`` when not set.
+        axis_label_text_color: Text color of the price-scale axis
+            label.
+        id: Optional string identifier for the price line.
+
+    Raises:
+        ValueError: From ``__post_init__`` if neither or both of
+            ``price`` and ``column`` are supplied.
+    """
+
+    price: Optional[float] = None
+    column: Optional[str] = None
+    color: Optional[Color] = None
+    line_width: Optional[LineWidth] = None
+    line_style: Optional[str] = None
+    line_visible: Optional[bool] = None
+    axis_label_visible: Optional[bool] = None
+    title: Optional[str] = None
+    axis_label_color: Optional[Color] = None
+    axis_label_text_color: Optional[Color] = None
+    id: Optional[str] = None
+
+    def __post_init__(self) -> None:
+        if self.price is None and self.column is None:
+            raise ValueError("Either 'price' or 'column' must be provided")
+        if self.price is not None and self.column is not None:
+            raise ValueError("Cannot specify both 'price' and 'column'")
+
+    def to_dict(self) -> dict:
+        result: dict = {}
+        if self.id is not None:
+            result["id"] = self.id
+        if self.price is not None:
+            result["price"] = self.price
+        if self.column is not None:
+            result["column"] = self.column
+        if self.color is not None:
+            result["color"] = self.color
+        if self.line_width is not None:
+            result["lineWidth"] = self.line_width
+        if self.line_style is not None:
+            if self.line_style not in LINE_STYLE_MAP:
+                raise ValueError(
+                    f"Invalid line_style {self.line_style!r}. "
+                    f"Must be one of {list(LINE_STYLE_MAP)}"
+                )
+            result["lineStyle"] = LINE_STYLE_MAP[self.line_style]
+        if self.line_visible is not None:
+            result["lineVisible"] = self.line_visible
+        if self.axis_label_visible is not None:
+            result["axisLabelVisible"] = self.axis_label_visible
+        if self.title is not None:
+            result["title"] = self.title
+        if self.axis_label_color is not None:
+            result["axisLabelColor"] = self.axis_label_color
+        if self.axis_label_text_color is not None:
+            result["axisLabelTextColor"] = self.axis_label_text_color
+        return result
+
+
+@dataclass
+class MarkerSpec:
+    """Table-driven markers.  Each row of the table produces one marker.
+
+    The ``timestamp`` parameter is always a column name (every marker
+    has a different time).  For the other properties you can provide
+    either a **fixed value** (applied to every marker) or a
+    **column name** via the corresponding ``*_column`` parameter
+    (resolved per-row from the table).
+
+    Construct through :func:`markers_from_table` for the public API;
+    direct instantiation is supported but bypasses the keyword-only
+    convention the factory enforces.
+
+    Attributes:
+        table: Deephaven table whose rows drive the markers.
+        timestamp: Column name supplying each marker's time value.
+        position: Default snake_case marker position (e.g.
+            ``"above_bar"``); overridden per-row by
+            ``position_column`` when set.  See :data:`MarkerPosition`.
+        shape: Default snake_case marker shape (e.g. ``"circle"``);
+            overridden by ``shape_column`` when set.  See
+            :data:`MarkerShape`.
+        color: Default marker color (CSS string); overridden by
+            ``color_column``.
+        text: Default marker label text; overridden by
+            ``text_column``.
+        size: Default marker size multiplier; overridden by
+            ``size_column``.
+        price: Default price level for price-anchored positions;
+            overridden by ``price_column``.  Mutually exclusive with
+            ``price_column``.
+        id_column: Optional column supplying a per-row marker ID.
+        price_column: Optional column supplying per-row price values
+            (required for ``"at_price_*"`` positions when ``price`` is
+            not set).
+        position_column: Optional column supplying per-row
+            ``MarkerPosition`` values.
+        shape_column: Optional column supplying per-row
+            ``MarkerShape`` values.
+        color_column: Optional column supplying per-row color
+            strings.
+        text_column: Optional column supplying per-row text labels.
+        size_column: Optional column supplying per-row size values.
+
+    Raises:
+        ValueError: From ``__post_init__`` if both ``price`` and
+            ``price_column`` are supplied, or if a price-based
+            position is requested without supplying ``price`` /
+            ``price_column``.
+    """
+
+    table: Any  # Deephaven Table
+    timestamp: str = "Timestamp"
+    # Fixed defaults (apply to every marker unless overridden by a column)
+    position: str = "above_bar"
+    shape: str = "circle"
+    color: Optional[Color] = None
+    text: str = ""
+    size: Optional[int] = None
+    price: Optional[float] = None
+    # Per-row column overrides
+    id_column: Optional[str] = None
+    price_column: Optional[str] = None
+    position_column: Optional[str] = None
+    shape_column: Optional[str] = None
+    color_column: Optional[str] = None
+    text_column: Optional[str] = None
+    size_column: Optional[str] = None
+
+    def __post_init__(self) -> None:
+        if self.price is not None and self.price_column is not None:
+            raise ValueError(
+                "Cannot specify both 'price' and 'price_column' on MarkerSpec."
+            )
+        if (
+            self.position in _PRICE_POSITIONS_PY
+            and self.price is None
+            and self.price_column is None
+        ):
+            raise ValueError(
+                f"MarkerSpec position '{self.position}' requires 'price' or 'price_column' to be set."
+            )
+
+    def get_columns(self) -> list[str]:
+        """Return every column name this spec reads from
+        :attr:`table`.
+
+        Returns:
+            list[str]: The time column followed by every set
+            ``*_column`` value, in spec-declaration order.
+        """
+        cols = [self.timestamp]
+        for col in (
+            self.position_column,
+            self.shape_column,
+            self.color_column,
+            self.text_column,
+            self.size_column,
+            self.id_column,
+            self.price_column,
+        ):
+            if col is not None:
+                cols.append(col)
+        return cols
+
+    def to_dict(self, table_id: int) -> dict:
+        """Serialize the marker spec to a JSON-transport dict.
+
+        Args:
+            table_id: Wire-protocol integer reference for
+                :attr:`table`.
+
+        Returns:
+            dict: JSON-serializable dict with keys ``tableId``,
+            ``columns`` (per-row column mappings), and ``defaults``
+            (camelCase JS values applied where no column is set).
+        """
+        columns: dict = {"time": self.timestamp}
+        if self.position_column is not None:
+            columns["position"] = self.position_column
+        if self.shape_column is not None:
+            columns["shape"] = self.shape_column
+        if self.color_column is not None:
+            columns["color"] = self.color_column
+        if self.text_column is not None:
+            columns["text"] = self.text_column
+        if self.size_column is not None:
+            columns["size"] = self.size_column
+        if self.id_column is not None:
+            columns["id"] = self.id_column
+        if self.price_column is not None:
+            columns["price"] = self.price_column
+
+        defaults: dict = {}
+        if self.position_column is None:
+            defaults["position"] = MARKER_POSITION_MAP.get(self.position, "aboveBar")
+        if self.shape_column is None:
+            defaults["shape"] = MARKER_SHAPE_MAP.get(self.shape, "circle")
+        if self.color_column is None and self.color is not None:
+            defaults["color"] = self.color
+        if self.text_column is None:
+            defaults["text"] = self.text
+        if self.size_column is None and self.size is not None:
+            defaults["size"] = self.size
+        if self.price_column is None and self.price is not None:
+            defaults["price"] = self.price
+
+        return {
+            "tableId": table_id,
+            "columns": columns,
+            "defaults": defaults,
+        }
+
+
+def marker(
+    time: Any,
+    position: MarkerPosition = "above_bar",
+    shape: MarkerShape = "circle",
+    color: Optional[Color] = None,
+    text: str = "",
+    size: Optional[int] = None,
+    id: Optional[str] = None,
+    price: Optional[float] = None,
+) -> Marker:
+    """Create a single static marker to place on a series.
+
+    Args:
+        time (Any): Time anchor for the marker.  UTC timestamp,
+            ISO string, or :class:`BusinessDay` dict.
+        position (MarkerPosition): Anchor position.  See
+            :data:`MarkerPosition`.  For ``"at_price_*"`` positions
+            you must also supply ``price``.
+        shape (MarkerShape): Glyph drawn for the marker.  See
+            :data:`MarkerShape`.
+        color (Optional[Color]): CSS color for the glyph fill.
+        text (str): Optional label text drawn near the marker.
+        size (Optional[int]): Glyph size multiplier (default ``1``).
+        id (Optional[str]): Optional string identifier.
+        price (Optional[float]): Required when ``position`` is one of
+            the ``"at_price_*"`` variants.
+
+    Returns:
+        Marker: A :class:`Marker` instance with snake_case input
+        values translated to the camelCase JS form expected by the
+        wire protocol.
+
+    Raises:
+        ValueError: If ``position`` is a price-anchored variant and
+            ``price`` is not supplied.
+
+    Example:
+        >>> m = tvl.marker(time=1700000000, position="above_bar",
+        ...                shape="arrow_up", color="#26a69a",
+        ...                text="Buy")
+    """
+    return Marker(
+        time=time,
+        position=MARKER_POSITION_MAP.get(position, "aboveBar"),
+        shape=MARKER_SHAPE_MAP.get(shape, "circle"),
+        color=color,
+        text=text,
+        size=size,
+        id=id,
+        price=price,
+    )
+
+
+def up_down_markers(
+    up_times: list[Any],
+    down_times: list[Any],
+    up_color: Optional[Color] = None,
+    down_color: Optional[Color] = None,
+    up_text: str = "",
+    down_text: str = "",
+    up_size: Optional[int] = None,
+    down_size: Optional[int] = None,
+) -> list[Marker]:
+    """Create a combined list of up and down markers.
+
+    Equivalent to the JS ``createUpDownMarkers()`` convenience helper.
+    Up-markers are placed below the bar with an upward arrow; down-markers
+    are placed above the bar with a downward arrow.
+
+    The returned list can be passed directly to the ``markers=`` parameter
+    of any series factory.  The JS library will sort markers by time, so
+    Python ordering does not matter.
+
+    Args:
+        up_times: Time values for bullish / up events.
+        down_times: Time values for bearish / down events.
+        up_color: Fill color for up-markers.  Default: theme OHLC increase color.
+        down_color: Fill color for down-markers.  Default: theme OHLC decrease color.
+        up_text: Label text for up-markers.  Default: ``""`` (no label).
+        down_text: Label text for down-markers.  Default: ``""`` (no label).
+        up_size: Size multiplier for up-markers.  Default: library default (1).
+        down_size: Size multiplier for down-markers.  Default: library default (1).
+
+    Returns:
+        Flat list of :class:`Marker` objects — up events followed by down events.
+    """
+    up_markers = [
+        Marker(
+            time=t,
+            position="belowBar",
+            shape="arrowUp",
+            color=up_color,
+            text=up_text,
+            size=up_size,
+        )
+        for t in up_times
+    ]
+    down_markers = [
+        Marker(
+            time=t,
+            position="aboveBar",
+            shape="arrowDown",
+            color=down_color,
+            text=down_text,
+            size=down_size,
+        )
+        for t in down_times
+    ]
+    return up_markers + down_markers
+
+
+def price_line(
+    price: Optional[float] = None,
+    color: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_visible: Optional[bool] = None,
+    axis_label_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    axis_label_color: Optional[Color] = None,
+    axis_label_text_color: Optional[Color] = None,
+    id: Optional[str] = None,
+    column: Optional[str] = None,
+) -> PriceLine:
+    """Create a horizontal price line on a series.
+
+    Provide either ``price`` (static value) or ``column`` (dynamic,
+    tracking the last-row value of the named column in the series'
+    table).
+
+    Args:
+        price (Optional[float]): Static price level.  Mutually
+            exclusive with ``column``.
+        color (Optional[Color]): Line color (CSS color string).
+        line_width (Optional[LineWidth]): Line thickness in pixels
+            (1–4).
+        line_style (Optional[LineStyle]): Dash pattern; see
+            :data:`LineStyle`.
+        line_visible (Optional[bool]): Whether the horizontal line
+            rule is drawn (default ``True`` in TV-LW).  Set to
+            ``False`` to show only the axis label.
+        axis_label_visible (Optional[bool]): Whether the axis label
+            is shown on the price scale.
+        title (Optional[str]): Short text drawn on the chart pane
+            next to the line.
+        axis_label_color (Optional[Color]): Background color of the
+            price-scale axis label.
+        axis_label_text_color (Optional[Color]): Text color of the
+            price-scale axis label.
+        id (Optional[str]): Optional string identifier for the price
+            line.
+        column (Optional[str]): Deephaven extension — column name
+            whose last-row value sets the price level dynamically.
+            Mutually exclusive with ``price``.
+
+    Returns:
+        PriceLine: A :class:`PriceLine` instance.
+
+    Raises:
+        ValueError: If neither or both of ``price`` and ``column``
+            are supplied.
+
+    Example:
+        >>> pl = tvl.price_line(price=100.0, color="#ff0000",
+        ...                     title="Target")
+    """
+    return PriceLine(
+        price=price,
+        column=column,
+        color=color,
+        line_width=line_width,
+        line_style=line_style,
+        line_visible=line_visible,
+        axis_label_visible=axis_label_visible,
+        title=title,
+        axis_label_color=axis_label_color,
+        axis_label_text_color=axis_label_text_color,
+        id=id,
+    )
+
+
+def markers_from_table(
+    table: Any,
+    timestamp: str = "Timestamp",
+    # Fixed defaults
+    position: MarkerPosition = "above_bar",
+    shape: MarkerShape = "circle",
+    color: Optional[Color] = None,
+    text: str = "",
+    size: Optional[int] = None,
+    price: Optional[float] = None,
+    # Per-row column overrides
+    position_column: Optional[str] = None,
+    shape_column: Optional[str] = None,
+    color_column: Optional[str] = None,
+    text_column: Optional[str] = None,
+    size_column: Optional[str] = None,
+    id_column: Optional[str] = None,
+    price_column: Optional[str] = None,
+) -> MarkerSpec:
+    """Create a table-driven marker specification.  Each row produces
+    one marker.
+
+    ``timestamp`` is always a column name.  For each other property, you
+    may pass a fixed value (e.g. ``color="#FF0000"``) that applies to
+    every marker, or a ``*_column`` name (e.g. ``color_column="Color"``)
+    to read the value per-row from the table.  For price-based
+    positions (``"at_price_top"`` etc.) supply either ``price`` (same
+    price for every row) or ``price_column`` (different price per row).
+
+    Args:
+        table (Any): Deephaven table whose rows drive the markers.
+        timestamp (str): Column name supplying each marker's time value.
+        position (MarkerPosition): Default marker position; see
+            :data:`MarkerPosition`.
+        shape (MarkerShape): Default marker shape; see
+            :data:`MarkerShape`.
+        color (Optional[Color]): Default marker color.
+        text (str): Default label text.
+        size (Optional[int]): Default size multiplier.
+        price (Optional[float]): Default price for price-anchored
+            positions.
+        position_column (Optional[str]): Column supplying per-row
+            ``MarkerPosition`` values.
+        shape_column (Optional[str]): Column supplying per-row
+            ``MarkerShape`` values.
+        color_column (Optional[str]): Column supplying per-row CSS
+            color strings.
+        text_column (Optional[str]): Column supplying per-row text
+            labels.
+        size_column (Optional[str]): Column supplying per-row size
+            values.
+        id_column (Optional[str]): Column supplying per-row marker
+            IDs.
+        price_column (Optional[str]): Column supplying per-row price
+            values for price-anchored positions.
+
+    Returns:
+        MarkerSpec: A :class:`MarkerSpec` ready to attach to a series
+        via the ``marker_spec=`` parameter of any series factory.
+
+    Raises:
+        ValueError: If both ``price`` and ``price_column`` are
+            supplied, or if a price-anchored ``position`` is requested
+            without either.
+
+    Example:
+        >>> spec = tvl.markers_from_table(
+        ...     events, timestamp="Timestamp",
+        ...     shape_column="Shape", color_column="Color",
+        ...     text_column="Label",
+        ... )
+    """
+    return MarkerSpec(
+        table=table,
+        timestamp=timestamp,
+        position=position,
+        shape=shape,
+        color=color,
+        text=text,
+        size=size,
+        price=price,
+        position_column=position_column,
+        shape_column=shape_column,
+        color_column=color_column,
+        text_column=text_column,
+        size_column=size_column,
+        id_column=id_column,
+        price_column=price_column,
+    )
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/options.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/options.py
new file mode 100644
index 000000000..51a809ee5
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/options.py
@@ -0,0 +1,560 @@
+"""Type definitions and constants for TradingView Lightweight Charts plugin.
+
+This module exposes the string-literal type aliases ("enum-like" choices) used
+throughout the public TVL API for styling, axis behavior, and marker shapes.
+
+All such aliases are :data:`typing.Literal` types, not :class:`enum.Enum`
+subclasses, so they appear in signatures as a union of string literals (e.g.
+``Literal["solid", "dotted", ...]``).  Each alias also has a ``__doc__``
+attached via direct assignment so that ``dhautofunction`` and other autodoc
+machinery can surface the full list of allowed values.
+
+The full set of aliases exported as enums:
+
+* :data:`LineStyle`, :data:`LineType`, :data:`LineWidth`
+* :data:`CrosshairMode`, :data:`HorzAlign`, :data:`VertAlign`
+* :data:`PriceScaleMode`, :data:`MarkerShape`, :data:`MarkerPosition`
+* :data:`ChartType`, :data:`ColorSpace`, :data:`ColorType`
+* :data:`PriceFormatter`, :data:`TickmarksPriceFormatter`
+* :data:`PercentageFormatter`, :data:`TickmarksPercentageFormatter`
+* :data:`PrecomputeConflationPriority`, :data:`LastPriceAnimationMode`
+* :data:`MarkerSign`, :data:`MismatchDirection`, :data:`PriceLineSource`
+* :data:`TickMarkType`, :data:`TrackingModeExitMode`
+
+Limitation: Sphinx ``autodoc`` cannot render ``Literal`` aliases as full
+documented members on their own.  The ``__doc__`` attribute on a
+``Literal`` alias is only visible through ``help()`` / ``__doc__``
+introspection; the recommended docs surface is to refer back to this
+module's docstring for the enumerated values.  See
+``notes/docstring-audit-limitations.md`` for details.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Literal, Optional, TypedDict
+from ._colors import Color
+
+# Line style constants (matching lightweight-charts LineStyle enum)
+SOLID = 0
+DOTTED = 1
+DASHED = 2
+LARGE_DASHED = 3
+SPARSE_DOTTED = 4
+
+LineStyle = Literal["solid", "dotted", "dashed", "large_dashed", "sparse_dotted"]
+"""Line dash pattern used by chart grid lines, crosshairs, price lines, and
+series with a line component.
+
+Allowed values:
+
+- ``"solid"`` — unbroken line.
+- ``"dotted"`` — small evenly-spaced dots.
+- ``"dashed"`` — short dashes.
+- ``"large_dashed"`` — long dashes.
+- ``"sparse_dotted"`` — widely-spaced dots.
+"""
+
+LineType = Literal["simple", "with_steps", "curved"]
+"""Geometry used to connect successive data points in line / area / baseline
+series.
+
+Allowed values:
+
+- ``"simple"`` — straight line segments between points.
+- ``"with_steps"`` — staircase (constant value until next point).
+- ``"curved"`` — smoothed monotone-cubic interpolation.
+"""
+
+LineWidth = Literal[1, 2, 3, 4]
+"""Stroke width in CSS pixels for series lines, crosshairs, and price lines.
+
+Allowed values: ``1``, ``2``, ``3``, ``4``.  Values outside this range are
+rejected by the TVL JS runtime.
+"""
+
+# Coordinate and Logical are JS-only nominal types used by ITimeScaleApi
+# (logicalToCoordinate, coordinateToLogical) and mouse event handlers.
+# These APIs are architecturally unavailable from Python (no live chart handle).
+# See: notes/api-coverage-report.md §16, §26.
+
+HorzAlign = Literal["left", "center", "right"]
+"""Horizontal alignment for text watermarks.
+
+Allowed values: ``"left"``, ``"center"``, ``"right"``.
+"""
+
+VertAlign = Literal["top", "center", "bottom"]
+"""Vertical alignment for text watermarks.
+
+Allowed values: ``"top"``, ``"center"``, ``"bottom"``.
+"""
+
+PriceScaleId = Literal["left", "right"]
+"""Which built-in price scale a series is attached to.
+
+Allowed values: ``"left"``, ``"right"``.  Charts default to ``"right"``;
+supply ``"left"`` on a series to render against the left price scale.
+"""
+
+CrosshairMode = Literal["normal", "magnet", "hidden", "magnet_ohlc"]
+"""Crosshair tracking behavior.
+
+Allowed values:
+
+- ``"normal"`` — free cursor; crosshair follows the pointer exactly.
+- ``"magnet"`` — snaps the horizontal crosshair to the nearest data point.
+- ``"hidden"`` — crosshair is fully suppressed.
+- ``"magnet_ohlc"`` — like ``"magnet"`` but snaps to OHLC bar extremes
+  (open/high/low/close), not just data values.
+"""
+
+PriceScaleMode = Literal["normal", "logarithmic", "percentage", "indexed_to_100"]
+"""How a price scale maps data values to vertical screen coordinates.
+
+Allowed values:
+
+- ``"normal"`` — linear mapping from raw values.
+- ``"logarithmic"`` — base-10 logarithmic mapping.
+- ``"percentage"`` — values shown as percentage change from the leftmost
+  visible value.
+- ``"indexed_to_100"`` — leftmost visible value rebased to 100; subsequent
+  values shown relative to that 100.
+"""
+
+MarkerShape = Literal["circle", "square", "arrow_up", "arrow_down"]
+"""Glyph drawn for a series marker.
+
+Allowed values: ``"circle"``, ``"square"``, ``"arrow_up"``, ``"arrow_down"``.
+"""
+
+MarkerPosition = Literal[
+    "above_bar",
+    "below_bar",
+    "in_bar",
+    "at_price_top",
+    "at_price_bottom",
+    "at_price_middle",
+]
+"""Where on the chart a series marker is anchored.
+
+Allowed values:
+
+- ``"above_bar"`` — just above the data point / bar.
+- ``"below_bar"`` — just below the data point / bar.
+- ``"in_bar"`` — vertically centered on the bar body.
+- ``"at_price_top"`` — at the supplied ``price``, glyph above the line.
+- ``"at_price_bottom"`` — at the supplied ``price``, glyph below the line.
+- ``"at_price_middle"`` — at the supplied ``price``, glyph centered on the line.
+
+The three ``"at_price_*"`` positions require a ``price`` field on the marker.
+"""
+
+PriceFormatter = Literal[
+    "currency_usd",
+    "currency_eur",
+    "currency_gbp",
+    "currency_jpy",
+    "percent",
+    "compact",
+    "scientific",
+]
+"""Preset name for the chart's price formatter (used on crosshair price labels
+and last-value badges).
+
+Allowed values:
+
+- ``"currency_usd"`` — formatted as US dollars (``$1,234.56``).
+- ``"currency_eur"`` — formatted as Euros (``€1.234,56``).
+- ``"currency_gbp"`` — formatted as British pounds (``£1,234.56``).
+- ``"currency_jpy"`` — formatted as Japanese yen (``¥1,235``, no decimals).
+- ``"percent"`` — formatted as a percentage (``42.50%``).
+- ``"compact"`` — compact notation with magnitude suffix (``1.2K``, ``3.4M``).
+- ``"scientific"`` — scientific notation (``1.23e+3``).
+"""
+
+TickmarksPriceFormatter = Literal[
+    "currency_usd",
+    "currency_eur",
+    "currency_gbp",
+    "currency_jpy",
+    "percent",
+    "compact",
+    "scientific",
+]
+"""Preset name for the tickmarks (axis tick label) price formatter.
+
+Shares the same preset set as :data:`PriceFormatter` because both format the
+same kind of numeric price values, but applied to axis tick labels rather than
+crosshair / last-value labels.
+
+Allowed values:
+
+- ``"currency_usd"`` — US dollars (``$1,234.56``).
+- ``"currency_eur"`` — Euros (``€1.234,56``).
+- ``"currency_gbp"`` — British pounds (``£1,234.56``).
+- ``"currency_jpy"`` — Japanese yen (``¥1,235``).
+- ``"percent"`` — percentage (``42.50%``).
+- ``"compact"`` — compact magnitude (``1.2K``, ``3.4M``).
+- ``"scientific"`` — scientific notation (``1.23e+3``).
+"""
+
+PercentageFormatter = Literal[
+    "percent",
+    "percent_1dp",
+    "percent_0dp",
+    "decimal",
+]
+"""Preset name for the crosshair percentage formatter used when the price scale
+is in ``"percentage"`` mode.  TVL passes raw percentage values (``42.5`` means
+``42.5%``).
+
+Allowed values:
+
+- ``"percent"`` — ``"42.50%"`` (two decimal places).
+- ``"percent_1dp"`` — ``"42.5%"`` (one decimal place).
+- ``"percent_0dp"`` — ``"43%"`` (no decimals, rounded).
+- ``"decimal"`` — ``"0.4250"`` (raw ratio, no percent sign).
+"""
+
+TickmarksPercentageFormatter = Literal[
+    "percent",
+    "percent_1dp",
+    "percent_0dp",
+    "decimal",
+]
+"""Preset name for the tickmarks percentage formatter (axis tick labels when the
+price scale is in ``"percentage"`` mode).
+
+Allowed values:
+
+- ``"percent"`` — ``"42.50%"`` (two decimals).
+- ``"percent_1dp"`` — ``"42.5%"`` (one decimal).
+- ``"percent_0dp"`` — ``"43%"`` (no decimals).
+- ``"decimal"`` — ``"0.4250"`` (raw ratio).
+"""
+
+ChartType = Literal["standard", "yield_curve", "options", "custom_numeric"]
+"""Backend renderer / horizontal-scale selector for :func:`chart`.
+
+Allowed values:
+
+- ``"standard"`` — time-based x-axis via ``createChart``.  All series types
+  are valid.
+- ``"yield_curve"`` — numeric x-axis representing maturity in months via
+  ``createYieldCurveChart``.  Only Line and Area series are supported.
+- ``"options"`` — numeric x-axis via ``createOptionsChart``, originally for
+  options-strike charts but usable for any numeric x.  All series types are
+  valid.
+- ``"custom_numeric"`` — alias for ``"options"``; prefer this name when the
+  x-axis represents arbitrary numeric values (frequency, distance, etc.)
+  rather than option strikes.
+"""
+
+ColorSpace = Literal["srgb", "display-p3"]
+"""Canvas color space used by the chart.
+
+Allowed values:
+
+- ``"srgb"`` — standard sRGB color space (default).
+- ``"display-p3"`` — wide-gamut Display P3 color space for HDR / wide-gamut
+  displays.  Must be set at chart creation; cannot be changed later.
+"""
+
+PrecomputeConflationPriority = Literal["background", "user-visible", "user-blocking"]
+"""Scheduling priority for precomputed conflation when
+``precompute_conflation_on_init=True``.  Maps directly to the browser
+``Scheduler.postTask`` priorities.
+
+Allowed values:
+
+- ``"background"`` — runs in idle time; lowest priority.
+- ``"user-visible"`` — runs at normal task priority.
+- ``"user-blocking"`` — runs ahead of other tasks; use sparingly.
+
+Consumer: ``TimeScaleOptions.precomputeConflationPriority``.
+"""
+
+ColorType = Literal["solid", "gradient"]
+"""Background fill mode for the chart layout.
+
+Allowed values:
+
+- ``"solid"`` — single solid color (``layout.background.color``).
+- ``"gradient"`` — vertical gradient between ``topColor`` and ``bottomColor``.
+
+In the Python API this is selected implicitly: pass ``background_color`` for
+solid, or ``background_top_color`` + ``background_bottom_color`` together for
+a gradient.
+"""
+
+LastPriceAnimationMode = Literal["disabled", "continuous", "on_data_update"]
+"""Animation behavior of the last-price dot on Line, Area, and Baseline series.
+
+Allowed values:
+
+- ``"disabled"`` — no last-price animation (default).
+- ``"continuous"`` — pulsing animation runs continuously.
+- ``"on_data_update"`` — pulses once each time the series data updates.
+"""
+
+MarkerSign = Literal["negative", "neutral", "positive"]
+"""Optional per-marker sign annotation passed through to
+``SeriesMarker.sign``.
+
+Allowed values: ``"negative"``, ``"neutral"``, ``"positive"``.
+
+Mainly used by JS-side rendering hooks; included in the Python API for
+completeness.
+"""
+
+MismatchDirection = Literal["nearest_left", "none", "nearest_right"]
+"""Mismatch-direction selector used by ``ISeriesApi.dataByIndex()`` and
+``barsInLogicalRange()``.  Allowed values:
+
+- ``"nearest_left"`` — closest data point at or to the left of the index.
+- ``"none"`` — exact match only; returns null if no data at that index.
+- ``"nearest_right"`` — closest data point at or to the right of the index.
+
+These methods are JS-runtime only; the alias is exported for type-hint
+completeness and for any future bidirectional messaging work.
+"""
+
+PriceLineSource = Literal["last_bar", "last_visible"]
+"""Which bar drives the automatic last-price horizontal rule on a series.
+
+Allowed values:
+
+- ``"last_bar"`` — uses the very last bar in the data set (default).
+- ``"last_visible"`` — uses the last bar within the current viewport.
+
+Consumer: ``SeriesOptionsCommon.priceLineSource``.
+"""
+
+TickMarkType = Literal["year", "month", "day_of_month", "time", "time_with_seconds"]
+"""Tick-mark granularity passed to ``TimeScaleOptions.tickMarkFormatter``.
+
+Allowed values:
+
+- ``"year"`` — year boundary.
+- ``"month"`` — month boundary.
+- ``"day_of_month"`` — day boundary.
+- ``"time"`` — intra-day hours / minutes.
+- ``"time_with_seconds"`` — intra-day with seconds resolution.
+
+``tickMarkFormatter`` itself requires a JS callable and is not exposed from
+Python; this alias is provided for completeness.
+"""
+
+TrackingModeExitMode = Literal["on_touch_end", "on_next_tap"]
+"""When the touch-device tracking mode (crosshair stays where the user
+tapped) is exited.
+
+Allowed values:
+
+- ``"on_touch_end"`` — exit as soon as the touch is released.
+- ``"on_next_tap"`` — keep tracking until the user taps somewhere else.
+
+Consumer: ``ChartOptionsBase.trackingMode.exitMode``.
+"""
+
+# Map Python-friendly names to lightweight-charts enum values
+LINE_STYLE_MAP = {
+    "solid": 0,
+    "dotted": 1,
+    "dashed": 2,
+    "large_dashed": 3,
+    "sparse_dotted": 4,
+}
+
+LINE_TYPE_MAP = {
+    "simple": 0,
+    "with_steps": 1,
+    "curved": 2,
+}
+
+CROSSHAIR_MODE_MAP = {
+    "normal": 0,
+    "magnet": 1,
+    "hidden": 2,
+    "magnet_ohlc": 3,
+}
+
+PRICE_SCALE_MODE_MAP = {
+    "normal": 0,
+    "logarithmic": 1,
+    "percentage": 2,
+    "indexed_to_100": 3,
+}
+
+MARKER_POSITION_MAP = {
+    "above_bar": "aboveBar",
+    "below_bar": "belowBar",
+    "in_bar": "inBar",
+    "at_price_top": "atPriceTop",
+    "at_price_bottom": "atPriceBottom",
+    "at_price_middle": "atPriceMiddle",
+}
+
+MARKER_SHAPE_MAP = {
+    "circle": "circle",
+    "square": "square",
+    "arrow_up": "arrowUp",
+    "arrow_down": "arrowDown",
+}
+
+CHART_TYPE_MAP = {
+    "standard": "standard",
+    "yield_curve": "yieldCurve",
+    "options": "options",
+    "custom_numeric": "options",  # alias — same JS renderer
+}
+
+# NOTE: The TVL JS function createChartEx(container, horzScaleBehavior, options?)
+# cannot be mapped to Python.  The horzScaleBehavior argument is a JS object whose
+# methods (formatHorzItem, preprocessData, etc.) run in the browser at render time.
+# There is no mechanism to serialize arbitrary Python callables to browser-side JS
+# through the JSON message channel.  The built-in behaviors (yieldCurve, options)
+# are exposed as named chart types above.  Any user needing a custom behavior must
+# write a JS plugin extension.
+
+LAST_PRICE_ANIMATION_MODE_MAP = {
+    "disabled": 0,
+    "continuous": 1,
+    "on_data_update": 2,
+}
+
+PRICE_LINE_SOURCE_MAP = {
+    "last_bar": 0,
+    "last_visible": 1,
+}
+
+# MarkerSign, MismatchDirection, and TickMarkType are type-only (Literal aliases
+# for annotations). Their integer maps are omitted because these enums are only
+# consumed by JS runtime APIs not reachable from the Python static config layer.
+
+TRACKING_MODE_EXIT_MODE_MAP = {
+    "on_touch_end": 0,
+    "on_next_tap": 1,
+}
+
+
+class PriceFormat(TypedDict, total=False):
+    """Price format configuration (built-in formats only).
+
+    Keys match the TVL JS API exactly:
+      - type:      ``'price'`` | ``'volume'`` | ``'percent'``
+      - precision: number of decimal places
+      - minMove:   minimum price movement (e.g. 0.01 for cents)
+
+    Note:
+        The ``'custom'`` type from the TradingView JS API requires a JavaScript
+        formatter callback and cannot be expressed in this Python plugin. Passing
+        ``type='custom'`` will raise ``ValueError`` at chart-building time.
+    """
+
+    type: Literal["price", "volume", "percent"]
+    precision: int
+    minMove: float
+
+
+@dataclass
+class WatermarkLine:
+    """One line of a multi-line text watermark.
+
+    All fields except ``text`` are optional; omitted fields inherit TVL defaults
+    (fontSize=48, color='rgba(0,0,0,0.5)', lineHeight=1.2*fontSize).
+
+    Args:
+        text: The watermark text. Required (the line is skipped if empty).
+        color: CSS color string. Defaults to a theme-derived semi-transparent color.
+        font_size: Font size in pixels. Defaults to 48.
+        line_height: Line height in pixels. Defaults to 1.2 * font_size.
+        font_style: CSS font-style string, e.g. ``'italic'``. Defaults to ``''``.
+
+    Note:
+        font_family is intentionally omitted — we do not allow font customization.
+    """
+
+    text: str
+    color: Optional[Color] = None
+    font_size: Optional[int] = None
+    line_height: Optional[float] = None
+    font_style: Optional[str] = None
+
+    def to_dict(self) -> dict:
+        """Serialise to the JS WatermarkLineOptions shape (camelCase keys, None omitted)."""
+        return _watermark_line_to_dict(self)
+
+
+def _watermark_line_to_dict(line: WatermarkLine) -> dict:
+    """Convert a WatermarkLine to a camelCase dict, omitting None values."""
+    d: dict = {"text": line.text}
+    if line.color is not None:
+        d["color"] = line.color
+    if line.font_size is not None:
+        d["fontSize"] = line.font_size
+    if line.line_height is not None:
+        d["lineHeight"] = line.line_height
+    if line.font_style is not None:
+        d["fontStyle"] = line.font_style
+    return d
+
+
+def watermark_line(
+    text: str,
+    color: Optional[Color] = None,
+    font_size: Optional[int] = None,
+    line_height: Optional[float] = None,
+    font_style: Optional[str] = None,
+) -> WatermarkLine:
+    """Create one line of a multi-line text watermark.
+
+    Pass a list of ``watermark_line(...)`` results to
+    ``tvl.chart(..., watermark_lines=[...])`` to draw a stacked
+    multi-line watermark behind the chart.  All fields except ``text``
+    are optional; omitted fields inherit TVL defaults
+    (``font_size=48``, color a theme-derived semi-transparent value,
+    ``line_height=1.2 * font_size``, ``font_style=''``).
+
+    Args:
+        text (str): The watermark text.  Required (the line is skipped
+            if empty).
+        color (Optional[Color]): CSS color string.  Defaults to a
+            theme-derived semi-transparent color.
+        font_size (Optional[int]): Font size in pixels.  Defaults to
+            ``48``.
+        line_height (Optional[float]): Line height in pixels.  Defaults
+            to ``1.2 * font_size``.
+        font_style (Optional[str]): CSS font-style string, e.g.
+            ``"italic"``.  Defaults to ``""``.
+
+    Returns:
+        WatermarkLine: A :class:`WatermarkLine` instance suitable for
+        passing inside ``watermark_lines=[...]``.
+
+    Example:
+        >>> wl = tvl.watermark_line("AAPL", color="#888", font_size=72)
+    """
+    return WatermarkLine(
+        text=text,
+        color=color,
+        font_size=font_size,
+        line_height=line_height,
+        font_style=font_style,
+    )
+
+
+# PriceFormatCustom is intentionally not implemented.
+# The JS API defines:
+#   { type: 'custom'; formatter: (priceValue: BarPrice) => string; minMove?: number }
+# The 'formatter' field is a JavaScript callback. Since this plugin serializes
+# configuration to JSON, there is no way to express a Python callable as JS code.
+# See: notes/api-coverage-report.md §26.
+
+# customSeriesDefaultOptions is not implemented.
+# It is only meaningful in the context of custom series (ICustomSeriesView).
+# Custom series require user-supplied JavaScript ICustomSeriesView implementations,
+# which the Python plugin has no mechanism to accept or forward.
+# Implementation is blocked until custom series support is added.
+# See: notes/api-coverage-report.md §10, §27.
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/series.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/series.py
new file mode 100644
index 000000000..dd4695293
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/series.py
@@ -0,0 +1,1572 @@
+"""Series creation functions for TradingView Lightweight Charts."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any, Optional
+
+from .options import (
+    LastPriceAnimationMode,
+    LineStyle,
+    LineType,
+    LineWidth,
+    PriceFormat,
+    PriceLineSource,
+    PriceScaleMode,
+    LAST_PRICE_ANIMATION_MODE_MAP,
+    LINE_STYLE_MAP,
+    LINE_TYPE_MAP,
+    PRICE_LINE_SOURCE_MAP,
+    PRICE_SCALE_MODE_MAP,
+)
+from .markers import Marker, PriceLine, MarkerSpec
+from ._colors import Color
+
+# TODO: createUpDownMarkers plugin support — see notes/coverage-plan/18-utility-types-and-functions.md §3.3
+# When implementing, add up_down_markers, up_down_marker_up_color, up_down_marker_down_color
+# params to series creation functions and serialize as seriesOptions.upDownMarkers.
+
+
+def _validate_price_format(price_format: Optional[PriceFormat]) -> None:
+    """Raise ValueError if price_format uses the unsupported 'custom' type."""
+    if price_format is not None and price_format.get("type") == "custom":
+        raise ValueError(
+            "PriceFormatCustom (type='custom') is not supported by the Python plugin. "
+            "The TradingView JS API requires a JavaScript formatter callback which "
+            "cannot be serialized from Python. Use type='price', 'volume', or 'percent'."
+        )
+
+
+@dataclass
+class SeriesSpec:
+    """Specification for a single chart series.
+
+    Holds everything required to render one series on a TVL chart:
+    the source Deephaven table, the column-to-channel mapping, any
+    styling options, optional markers / price lines / table-driven
+    marker spec, and auto-bin (downsampling) controls.
+
+    Construct instances through one of the typed factories
+    (:func:`candlestick_series`, :func:`bar_series`,
+    :func:`line_series`, :func:`area_series`,
+    :func:`baseline_series`, :func:`histogram_series`) rather than
+    instantiating directly — the factories validate inputs and build
+    the camelCase JS-shaped ``options`` and ``price_scale_options``
+    dicts.
+
+    Attributes:
+        series_type: One of ``"Candlestick"``, ``"Bar"``, ``"Line"``,
+            ``"Area"``, ``"Baseline"``, ``"Histogram"``.
+        table: The source Deephaven table.
+        column_mapping: Dict mapping series channel names to table
+            column names (e.g.
+            ``{"time": "Timestamp", "open": "Open", "high": "High"}``).
+        options: camelCase JS-shaped series options dict.
+        markers: Optional list of static :class:`Marker` instances.
+        price_lines: Optional list of :class:`PriceLine` instances.
+        marker_spec: Optional table-driven :class:`MarkerSpec`.
+        price_scale_options: camelCase price-scale options for the
+            series' scale.
+        pane: Optional pane index (default ``0``).
+        auto_bin: Tri-state auto-bin control.  ``None`` (default) =
+            auto-detect by table size; ``True`` = force aggregation;
+            ``False`` = opt out and ship raw rows.
+        bin_width: Optional ISO 8601 duration override (e.g.
+            ``"PT1S"``, ``"PT5M"``).  Bypasses nice-duration snapping.
+        bin_count: Optional target bin count for the initial
+            aggregation (default ``5000``).
+        agg: Histogram-only per-bin aggregation: ``"sum"``,
+            ``"count"``, ``"avg"``, or ``"last"``.  Set by the
+            factory; not user-facing on non-histogram series.
+    """
+
+    series_type: str  # "Candlestick", "Bar", "Line", "Area", "Baseline", "Histogram"
+    table: Any  # Deephaven Table
+    column_mapping: dict  # {"time": "Timestamp", "open": "Open", ...}
+    options: dict = field(default_factory=dict)
+    markers: Optional[list[Marker]] = None
+    price_lines: Optional[list[PriceLine]] = None
+    marker_spec: Optional[MarkerSpec] = None
+    price_scale_options: dict = field(default_factory=dict)
+    pane: Optional[int] = None
+
+    # ---- Auto-bin (server-side time-bucket aggregation) ----
+    # Tri-state: None=auto-detect by table size, True=force on, False=opt out.
+    auto_bin: Optional[bool] = None
+    # ISO 8601 duration override (e.g. 'PT1S'). When set, overrides nice_bin_width.
+    bin_width: Optional[str] = None
+    # Override TARGET_BINS for the initial aggregation.
+    bin_count: Optional[int] = None
+    # Histogram-only aggregation mode: "sum" | "count" | "avg" | "last".
+    agg: Optional[str] = None
+
+    # ---- Partition-by-key (`by=`) ----
+    # When set, the source table is partitioned by this column and one
+    # runtime series is created per unique key. JS watches the partitioned
+    # table for new/dropped keys.
+    by: Optional[str] = None
+    # Resolved PartitionedTable from table.partition_by([by]). Set by the
+    # caller (unified constructors) so liveness can manage it.
+    partitioned_table: Any = None
+
+    def to_dict(
+        self, series_id: str, table_id: int, marker_table_id: int | None = None
+    ) -> dict:
+        """Serialize the series spec to a JSON-transport dict.
+
+        Args:
+            series_id: Stable string ID assigned to this series
+                (usually ``"series_<i>"``).
+            table_id: Wire-protocol integer reference for
+                :attr:`table`.
+            marker_table_id: Wire-protocol integer reference for the
+                :attr:`marker_spec` table, or ``None`` if no marker
+                spec is set.
+
+        Returns:
+            dict: JSON-serializable dict with ``id``, ``type``,
+            ``options``, ``dataMapping``, and (when set) ``markers``,
+            ``priceLines``, ``markerSpec``, ``priceScaleOptions``,
+            ``paneIndex``.
+        """
+        result = {
+            "id": series_id,
+            "type": self.series_type,
+            "options": self.options,
+            "dataMapping": {
+                "tableId": table_id,
+                "columns": self.column_mapping,
+            },
+        }
+        if self.markers:
+            result["markers"] = [m.to_dict() for m in self.markers]
+        if self.price_lines:
+            result["priceLines"] = [pl.to_dict() for pl in self.price_lines]
+        if self.marker_spec is not None and marker_table_id is not None:
+            result["markerSpec"] = self.marker_spec.to_dict(marker_table_id)
+        if self.price_scale_options:
+            result["priceScaleOptions"] = self.price_scale_options
+        if self.pane is not None:
+            result["paneIndex"] = self.pane
+        if self.by is not None:
+            # JS uses this to watch the partitioned table and spawn one
+            # runtime series per partition key, using `options`, `column_mapping`,
+            # and `priceScaleOptions` from this spec as the template.
+            result["partition"] = {"byColumn": self.by}
+        return result
+
+
+def _filter_none(d: dict) -> dict:
+    """Remove None values from a dict."""
+    return {k: v for k, v in d.items() if v is not None}
+
+
+def _resolve_line_style(style: Optional[LineStyle]) -> Optional[int]:
+    if style is None:
+        return None
+    if style not in LINE_STYLE_MAP:
+        raise ValueError(
+            f"Invalid line_style {style!r}. Must be one of {list(LINE_STYLE_MAP)}"
+        )
+    return LINE_STYLE_MAP[style]
+
+
+def _resolve_line_type(line_type: Optional[LineType]) -> Optional[int]:
+    if line_type is None:
+        return None
+    if line_type not in LINE_TYPE_MAP:
+        raise ValueError(
+            f"Invalid line_type {line_type!r}. Must be one of {list(LINE_TYPE_MAP)}"
+        )
+    return LINE_TYPE_MAP[line_type]
+
+
+def _resolve_last_price_animation(
+    mode: Optional[LastPriceAnimationMode],
+) -> Optional[int]:
+    if mode is None:
+        return None
+    if mode not in LAST_PRICE_ANIMATION_MODE_MAP:
+        raise ValueError(
+            f"Invalid last_price_animation {mode!r}. Must be one of {list(LAST_PRICE_ANIMATION_MODE_MAP)}"
+        )
+    return LAST_PRICE_ANIMATION_MODE_MAP[mode]
+
+
+def _build_price_scale_options(
+    auto_scale: Optional[bool],
+    scale_margin_top: Optional[float],
+    scale_margin_bottom: Optional[float],
+    mode: Optional[PriceScaleMode] = None,
+    invert_scale: Optional[bool] = None,
+    align_labels: Optional[bool] = None,
+    border_visible: Optional[bool] = None,
+    border_color: Optional[Color] = None,
+    text_color: Optional[Color] = None,
+    entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    ticks_visible: Optional[bool] = None,
+    minimum_width: Optional[int] = None,
+    ensure_edge_tick_marks_visible: Optional[bool] = None,
+) -> dict:
+    """Build priceScaleOptions dict from kwargs."""
+    opts = _filter_none(
+        {
+            "autoScale": auto_scale,
+            "mode": PRICE_SCALE_MODE_MAP.get(mode) if mode is not None else None,
+            "invertScale": invert_scale,
+            "alignLabels": align_labels,
+            "borderVisible": border_visible,
+            "borderColor": border_color,
+            "textColor": text_color,
+            "entireTextOnly": entire_text_only,
+            "visible": scale_visible,
+            "ticksVisible": ticks_visible,
+            "minimumWidth": minimum_width,
+            "ensureEdgeTickMarksVisible": ensure_edge_tick_marks_visible,
+        }
+    )
+    margins = _filter_none({"top": scale_margin_top, "bottom": scale_margin_bottom})
+    if margins:
+        opts["scaleMargins"] = margins
+    return opts
+
+
+def _build_common_options(
+    last_value_visible: Optional[bool],
+    title: Optional[str],
+    visible: Optional[bool],
+    price_scale_id: Optional[str],
+    price_format: Optional[PriceFormat],
+    price_line_visible: Optional[bool],
+    price_line_source: Optional[PriceLineSource],
+    price_line_width: Optional[LineWidth],
+    price_line_color: Optional[Color],
+    price_line_style: Optional[LineStyle],
+    base_line_visible: Optional[bool],
+    base_line_color: Optional[Color],
+    base_line_width: Optional[LineWidth],
+    base_line_style: Optional[LineStyle],
+) -> dict:
+    """Build the SeriesOptionsCommon portion of the series options dict.
+
+    Returns a dict with only non-None entries, ready to be merged into the
+    per-type options dict via ``{**_build_common_options(...), ...}``.
+
+        price_line_visible: Show the price line. Default True.
+        price_line_source:  "last_bar" or "last_visible". Default "last_bar".
+        price_line_width:   Line width 1-4 px. Default 1.
+        price_line_color:   CSS color string. Empty string uses series color.
+        price_line_style:   LineStyle value. Default "dashed".
+
+        base_line_visible: Show the baseline. Default True.
+        base_line_color:   CSS color string. Default "#B2B5BE".
+        base_line_width:   Line width 1-4 px. Default 1.
+        base_line_style:   LineStyle value. Default "solid".
+    """
+    return _filter_none(
+        {
+            "lastValueVisible": last_value_visible,
+            "title": title,
+            "visible": visible,
+            "priceScaleId": price_scale_id,
+            "priceFormat": price_format,
+            "priceLineVisible": price_line_visible,
+            "priceLineSource": (
+                PRICE_LINE_SOURCE_MAP.get(price_line_source)
+                if price_line_source is not None
+                else None
+            ),
+            "priceLineWidth": price_line_width,
+            "priceLineColor": price_line_color,
+            "priceLineStyle": _resolve_line_style(price_line_style),
+            "baseLineVisible": base_line_visible,
+            "baseLineColor": base_line_color,
+            "baseLineWidth": base_line_width,
+            "baseLineStyle": _resolve_line_style(base_line_style),
+        }
+    )
+
+
+def candlestick_series(
+    table: Any,
+    timestamp: str = "Timestamp",
+    open: str = "Open",
+    high: str = "High",
+    low: str = "Low",
+    close: str = "Close",
+    up_color: Optional[Color] = None,
+    down_color: Optional[Color] = None,
+    border_visible: Optional[bool] = None,
+    border_color: Optional[Color] = None,
+    border_up_color: Optional[Color] = None,
+    border_down_color: Optional[Color] = None,
+    wick_visible: Optional[bool] = None,
+    wick_color: Optional[Color] = None,
+    wick_up_color: Optional[Color] = None,
+    wick_down_color: Optional[Color] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    last_value_visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    color_column: Optional[str] = None,
+    border_color_column: Optional[str] = None,
+    wick_color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    auto_bin: Optional[bool] = None,
+    bin_width: Optional[str] = None,
+    bin_count: Optional[int] = None,
+) -> SeriesSpec:
+    """Create a candlestick series specification.
+
+    A candlestick series renders four channels (open, high, low,
+    close) per time bucket as a filled body with wicks.  When the
+    source table is large, auto-binning aggregates OHLC values
+    server-side before the data is shipped to the browser.
+
+    Args:
+        table (Any): The Deephaven table containing OHLC data.
+        timestamp (str): Column name for the time axis.
+        open (str): Column name for the opening price.
+        high (str): Column name for the bar high.
+        low (str): Column name for the bar low.
+        close (str): Column name for the closing price.
+        up_color (Optional[Color]): Body color for up-bars.
+        down_color (Optional[Color]): Body color for down-bars.
+        border_visible (Optional[bool]): Show the body border.
+        border_color (Optional[Color]): Border color for both directions.
+        border_up_color (Optional[Color]): Border color for up-bars
+            (overrides ``border_color`` for up).
+        border_down_color (Optional[Color]): Border color for down-bars.
+        wick_visible (Optional[bool]): Show wicks.
+        wick_color (Optional[Color]): Wick color for both directions.
+        wick_up_color (Optional[Color]): Wick color for up-bars.
+        wick_down_color (Optional[Color]): Wick color for down-bars.
+        title (Optional[str]): Title shown in the series tooltip /
+            legend.
+        visible (Optional[bool]): Whether the series is visible.
+        last_value_visible (Optional[bool]): Show the last-value
+            badge on the price scale.
+        price_scale_id (Optional[str]): ID of the price scale this
+            series uses (``"left"``, ``"right"``, or a custom overlay
+            ID).
+        price_format (Optional[PriceFormat]): Per-series price-format
+            dict; see :class:`PriceFormat`.
+        price_line_visible (Optional[bool]): Show the auto last-price
+            horizontal rule.
+        price_line_source (Optional[PriceLineSource]): Which bar
+            drives the price line; see :data:`PriceLineSource`.
+        price_line_width (Optional[LineWidth]): Price-line stroke
+            width (1–4 px).
+        price_line_color (Optional[Color]): Price-line color (empty
+            string uses series color).
+        price_line_style (Optional[LineStyle]): Price-line dash
+            pattern; see :data:`LineStyle`.
+        base_line_visible (Optional[bool]): Show the zero/index
+            baseline (in ``percentage`` / ``indexed_to_100`` price
+            modes).
+        base_line_color (Optional[Color]): Baseline color.
+        base_line_width (Optional[LineWidth]): Baseline stroke width.
+        base_line_style (Optional[LineStyle]): Baseline dash pattern.
+        auto_scale (Optional[bool]): Auto-fit the series' price scale.
+        scale_margin_top (Optional[float]): Top margin (fraction 0–1)
+            applied to the series' price scale.
+        scale_margin_bottom (Optional[float]): Bottom margin.
+        scale_mode (Optional[PriceScaleMode]): Price-scale mode; see
+            :data:`PriceScaleMode`.
+        scale_invert (Optional[bool]): Invert the price scale.
+        scale_align_labels (Optional[bool]): Align scale labels with
+            pixels.
+        scale_border_visible (Optional[bool]): Show the scale border.
+        scale_border_color (Optional[Color]): Scale border color.
+        scale_text_color (Optional[Color]): Scale label color.
+        scale_entire_text_only (Optional[bool]): Render only complete
+            labels.
+        scale_visible (Optional[bool]): Show the price scale.
+        scale_ticks_visible (Optional[bool]): Show tick marks.
+        scale_minimum_width (Optional[int]): Minimum scale width in
+            pixels.
+        scale_ensure_edge_tick_marks_visible (Optional[bool]): Force
+            edge tick marks.
+        color_column (Optional[str]): Column name supplying per-row
+            body color (overrides ``up_color`` / ``down_color``).
+        border_color_column (Optional[str]): Column name supplying
+            per-row border color.
+        wick_color_column (Optional[str]): Column name supplying
+            per-row wick color.
+        pane (Optional[int]): Pane index (default ``0``).
+        markers (Optional[list[Marker]]): Static markers.
+        price_lines (Optional[list[PriceLine]]): Horizontal price
+            lines.
+        marker_spec (Optional[MarkerSpec]): Table-driven marker spec.
+        auto_bin (Optional[bool]): Tri-state.  ``None`` (default)
+            auto-bins when the table exceeds the auto-bin threshold
+            (5000 rows); ``True`` forces aggregation even for small
+            tables; ``False`` ships the raw table.
+        bin_width (Optional[str]): ISO 8601 duration override (e.g.
+            ``"PT1S"``, ``"PT5M"``).
+        bin_count (Optional[int]): Target number of bins (default
+            ``5000``).
+
+    Returns:
+        SeriesSpec: A series specification suitable for passing to
+        :func:`chart`.
+
+    Note:
+        Auto-bin aggregation for OHLC: ``first(open)``, ``max(high)``,
+        ``min(low)``, ``last(close)``.  Four distinct OHLC columns are
+        required; passing the same column for more than one role will
+        raise at chart build time.
+
+    Example:
+        >>> s = tvl.candlestick_series(ohlc, timestamp="Timestamp",
+        ...                            open="Open", high="High",
+        ...                            low="Low", close="Close")
+    """
+    _validate_price_format(price_format)
+    options = {
+        **_build_common_options(
+            last_value_visible=last_value_visible,
+            title=title,
+            visible=visible,
+            price_scale_id=price_scale_id,
+            price_format=price_format,
+            price_line_visible=price_line_visible,
+            price_line_source=price_line_source,
+            price_line_width=price_line_width,
+            price_line_color=price_line_color,
+            price_line_style=price_line_style,
+            base_line_visible=base_line_visible,
+            base_line_color=base_line_color,
+            base_line_width=base_line_width,
+            base_line_style=base_line_style,
+        ),
+        **_filter_none(
+            {
+                "upColor": up_color,
+                "downColor": down_color,
+                "borderVisible": border_visible,
+                "borderColor": border_color,
+                "borderUpColor": border_up_color,
+                "borderDownColor": border_down_color,
+                "wickVisible": wick_visible,
+                "wickColor": wick_color,
+                "wickUpColor": wick_up_color,
+                "wickDownColor": wick_down_color,
+            }
+        ),
+    }
+    column_mapping = {
+        "time": timestamp,
+        "open": open,
+        "high": high,
+        "low": low,
+        "close": close,
+    }
+    if color_column is not None:
+        column_mapping["color"] = color_column
+    if border_color_column is not None:
+        column_mapping["borderColor"] = border_color_column
+    if wick_color_column is not None:
+        column_mapping["wickColor"] = wick_color_column
+    return SeriesSpec(
+        series_type="Candlestick",
+        table=table,
+        column_mapping=column_mapping,
+        options=options,
+        markers=markers,
+        price_lines=price_lines,
+        marker_spec=marker_spec,
+        price_scale_options=_build_price_scale_options(
+            auto_scale,
+            scale_margin_top,
+            scale_margin_bottom,
+            mode=scale_mode,
+            invert_scale=scale_invert,
+            align_labels=scale_align_labels,
+            border_visible=scale_border_visible,
+            border_color=scale_border_color,
+            text_color=scale_text_color,
+            entire_text_only=scale_entire_text_only,
+            scale_visible=scale_visible,
+            ticks_visible=scale_ticks_visible,
+            minimum_width=scale_minimum_width,
+            ensure_edge_tick_marks_visible=scale_ensure_edge_tick_marks_visible,
+        ),
+        pane=pane,
+        auto_bin=auto_bin,
+        bin_width=bin_width,
+        bin_count=bin_count,
+        agg="ohlc",
+    )
+
+
+def bar_series(
+    table: Any,
+    timestamp: str = "Timestamp",
+    open: str = "Open",
+    high: str = "High",
+    low: str = "Low",
+    close: str = "Close",
+    up_color: Optional[Color] = None,
+    down_color: Optional[Color] = None,
+    open_visible: Optional[bool] = None,
+    thin_bars: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    last_value_visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    auto_bin: Optional[bool] = None,
+    bin_width: Optional[str] = None,
+    bin_count: Optional[int] = None,
+) -> SeriesSpec:
+    """Create a bar (OHLC) series specification.
+
+    Bar series render each bucket as a vertical line with small
+    open/close ticks; contrast with :func:`candlestick_series` which
+    fills the body.  Same auto-bin behavior as candlestick.
+
+    Args:
+        table (Any): Deephaven table containing OHLC data.
+        timestamp (str): Column name for the time axis.
+        open (str): Column name for the opening price.
+        high (str): Column name for the bar high.
+        low (str): Column name for the bar low.
+        close (str): Column name for the closing price.
+        up_color (Optional[Color]): Bar color for up-bars.
+        down_color (Optional[Color]): Bar color for down-bars.
+        open_visible (Optional[bool]): Show the open tick (default
+            ``True``).
+        thin_bars (Optional[bool]): Use thin bar style.
+        title (Optional[str]): Title shown in the series tooltip /
+            legend.
+        visible (Optional[bool]): Series visibility.
+        last_value_visible (Optional[bool]): Show the last-value
+            badge.
+        price_scale_id (Optional[str]): Price-scale ID.
+        price_format (Optional[PriceFormat]): Per-series price format.
+        price_line_visible (Optional[bool]): Show the auto last-price
+            horizontal rule.
+        price_line_source (Optional[PriceLineSource]): Which bar
+            drives the auto price line.
+        price_line_width (Optional[LineWidth]): Price-line stroke
+            width.
+        price_line_color (Optional[Color]): Price-line color.
+        price_line_style (Optional[LineStyle]): Price-line dash
+            pattern.
+        base_line_visible (Optional[bool]): Show the zero/index
+            baseline.
+        base_line_color (Optional[Color]): Baseline color.
+        base_line_width (Optional[LineWidth]): Baseline stroke width.
+        base_line_style (Optional[LineStyle]): Baseline dash pattern.
+        auto_scale (Optional[bool]): Auto-fit the price scale.
+        scale_margin_top (Optional[float]): Top margin fraction.
+        scale_margin_bottom (Optional[float]): Bottom margin fraction.
+        scale_mode (Optional[PriceScaleMode]): Price-scale mode.
+        scale_invert (Optional[bool]): Invert the price scale.
+        scale_align_labels (Optional[bool]): Align labels with pixels.
+        scale_border_visible (Optional[bool]): Show scale border.
+        scale_border_color (Optional[Color]): Border color.
+        scale_text_color (Optional[Color]): Label color.
+        scale_entire_text_only (Optional[bool]): Only complete labels.
+        scale_visible (Optional[bool]): Show the price scale.
+        scale_ticks_visible (Optional[bool]): Show tick marks.
+        scale_minimum_width (Optional[int]): Minimum width in pixels.
+        scale_ensure_edge_tick_marks_visible (Optional[bool]): Force
+            edge ticks.
+        color_column (Optional[str]): Column name supplying per-row
+            bar color.
+        pane (Optional[int]): Pane index.
+        markers (Optional[list[Marker]]): Static markers.
+        price_lines (Optional[list[PriceLine]]): Horizontal price
+            lines.
+        marker_spec (Optional[MarkerSpec]): Table-driven marker spec.
+        auto_bin (Optional[bool]): Auto-bin tri-state.  See
+            :func:`candlestick_series` for full semantics.
+        bin_width (Optional[str]): ISO 8601 duration override.
+        bin_count (Optional[int]): Target number of bins.
+
+    Returns:
+        SeriesSpec: A bar-series specification.
+
+    Example:
+        >>> s = tvl.bar_series(ohlc, timestamp="Timestamp",
+        ...                    open="Open", high="High",
+        ...                    low="Low", close="Close")
+    """
+    _validate_price_format(price_format)
+    options = {
+        **_build_common_options(
+            last_value_visible=last_value_visible,
+            title=title,
+            visible=visible,
+            price_scale_id=price_scale_id,
+            price_format=price_format,
+            price_line_visible=price_line_visible,
+            price_line_source=price_line_source,
+            price_line_width=price_line_width,
+            price_line_color=price_line_color,
+            price_line_style=price_line_style,
+            base_line_visible=base_line_visible,
+            base_line_color=base_line_color,
+            base_line_width=base_line_width,
+            base_line_style=base_line_style,
+        ),
+        **_filter_none(
+            {
+                "upColor": up_color,
+                "downColor": down_color,
+                "openVisible": open_visible,
+                "thinBars": thin_bars,
+            }
+        ),
+    }
+    column_mapping = {
+        "time": timestamp,
+        "open": open,
+        "high": high,
+        "low": low,
+        "close": close,
+    }
+    if color_column is not None:
+        column_mapping["color"] = color_column
+    return SeriesSpec(
+        series_type="Bar",
+        table=table,
+        column_mapping=column_mapping,
+        options=options,
+        markers=markers,
+        price_lines=price_lines,
+        marker_spec=marker_spec,
+        price_scale_options=_build_price_scale_options(
+            auto_scale,
+            scale_margin_top,
+            scale_margin_bottom,
+            mode=scale_mode,
+            invert_scale=scale_invert,
+            align_labels=scale_align_labels,
+            border_visible=scale_border_visible,
+            border_color=scale_border_color,
+            text_color=scale_text_color,
+            entire_text_only=scale_entire_text_only,
+            scale_visible=scale_visible,
+            ticks_visible=scale_ticks_visible,
+            minimum_width=scale_minimum_width,
+            ensure_edge_tick_marks_visible=scale_ensure_edge_tick_marks_visible,
+        ),
+        pane=pane,
+        auto_bin=auto_bin,
+        bin_width=bin_width,
+        bin_count=bin_count,
+        agg="ohlc",
+    )
+
+
+def line_series(
+    table: Any,
+    timestamp: str = "Timestamp",
+    value: str = "Value",
+    color: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_type: Optional[LineType] = None,
+    line_visible: Optional[bool] = None,
+    point_markers_visible: Optional[bool] = None,
+    point_markers_radius: Optional[float] = None,
+    crosshair_marker_visible: Optional[bool] = None,
+    crosshair_marker_radius: Optional[float] = None,
+    crosshair_marker_border_color: Optional[Color] = None,
+    crosshair_marker_background_color: Optional[Color] = None,
+    crosshair_marker_border_width: Optional[float] = None,
+    last_price_animation: Optional[LastPriceAnimationMode] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+) -> SeriesSpec:
+    """Create a line series specification.
+
+    Args:
+        table (Any): Deephaven table with the data.
+        timestamp (str): Column name for the time axis.
+        value (str): Column name for the y-axis.
+        color (Optional[Color]): Line color (CSS string).
+        line_width (Optional[LineWidth]): Stroke width 1–4 px.
+        line_style (Optional[LineStyle]): Dash pattern; see
+            :data:`LineStyle`.
+        line_type (Optional[LineType]): Geometry between data points;
+            see :data:`LineType`.
+        line_visible (Optional[bool]): Show the line itself (set
+            ``False`` to render only crosshair / point markers).
+        point_markers_visible (Optional[bool]): Show point markers
+            at every data point.
+        point_markers_radius (Optional[float]): Point marker radius in
+            pixels.
+        crosshair_marker_visible (Optional[bool]): Show the crosshair
+            marker dot.
+        crosshair_marker_radius (Optional[float]): Crosshair marker
+            radius in pixels.
+        crosshair_marker_border_color (Optional[Color]): Crosshair
+            marker border color.
+        crosshair_marker_background_color (Optional[Color]): Crosshair
+            marker fill color.
+        crosshair_marker_border_width (Optional[float]): Crosshair
+            marker border width.
+        last_price_animation (Optional[LastPriceAnimationMode]):
+            Last-price dot animation; see :data:`LastPriceAnimationMode`.
+        last_value_visible (Optional[bool]): Show the last-value badge.
+        title (Optional[str]): Title in the series tooltip / legend.
+        visible (Optional[bool]): Series visibility.
+        price_scale_id (Optional[str]): Price-scale ID.
+        price_format (Optional[PriceFormat]): Per-series price format.
+        price_line_visible (Optional[bool]): Show the auto last-price
+            horizontal rule.
+        price_line_source (Optional[PriceLineSource]): Which bar
+            drives the auto price line.
+        price_line_width (Optional[LineWidth]): Price-line stroke
+            width.
+        price_line_color (Optional[Color]): Price-line color.
+        price_line_style (Optional[LineStyle]): Price-line dash
+            pattern.
+        base_line_visible (Optional[bool]): Show the baseline.
+        base_line_color (Optional[Color]): Baseline color.
+        base_line_width (Optional[LineWidth]): Baseline stroke width.
+        base_line_style (Optional[LineStyle]): Baseline dash pattern.
+        auto_scale (Optional[bool]): Auto-fit the price scale.
+        scale_margin_top (Optional[float]): Top margin fraction.
+        scale_margin_bottom (Optional[float]): Bottom margin fraction.
+        scale_mode (Optional[PriceScaleMode]): Price-scale mode.
+        scale_invert (Optional[bool]): Invert the scale.
+        scale_align_labels (Optional[bool]): Align labels with pixels.
+        scale_border_visible (Optional[bool]): Show scale border.
+        scale_border_color (Optional[Color]): Border color.
+        scale_text_color (Optional[Color]): Label color.
+        scale_entire_text_only (Optional[bool]): Only complete labels.
+        scale_visible (Optional[bool]): Show the price scale.
+        scale_ticks_visible (Optional[bool]): Show tick marks.
+        scale_minimum_width (Optional[int]): Minimum width in pixels.
+        scale_ensure_edge_tick_marks_visible (Optional[bool]): Force
+            edge ticks.
+        color_column (Optional[str]): Column name supplying per-row
+            line color.
+        pane (Optional[int]): Pane index.
+        markers (Optional[list[Marker]]): Static markers.
+        price_lines (Optional[list[PriceLine]]): Horizontal price
+            lines.
+        marker_spec (Optional[MarkerSpec]): Table-driven marker spec.
+
+    Returns:
+        SeriesSpec: A line-series specification.
+
+    Example:
+        >>> s = tvl.line_series(my_table, timestamp="Timestamp",
+        ...                     value="Price", color="#26a69a")
+    """
+    _validate_price_format(price_format)
+    options = {
+        **_build_common_options(
+            last_value_visible=last_value_visible,
+            title=title,
+            visible=visible,
+            price_scale_id=price_scale_id,
+            price_format=price_format,
+            price_line_visible=price_line_visible,
+            price_line_source=price_line_source,
+            price_line_width=price_line_width,
+            price_line_color=price_line_color,
+            price_line_style=price_line_style,
+            base_line_visible=base_line_visible,
+            base_line_color=base_line_color,
+            base_line_width=base_line_width,
+            base_line_style=base_line_style,
+        ),
+        **_filter_none(
+            {
+                "color": color,
+                "lineWidth": line_width,
+                "lineStyle": _resolve_line_style(line_style),
+                "lineType": _resolve_line_type(line_type),
+                "lineVisible": line_visible,
+                "pointMarkersVisible": point_markers_visible,
+                "pointMarkersRadius": point_markers_radius,
+                "crosshairMarkerVisible": crosshair_marker_visible,
+                "crosshairMarkerRadius": crosshair_marker_radius,
+                "crosshairMarkerBorderColor": crosshair_marker_border_color,
+                "crosshairMarkerBackgroundColor": crosshair_marker_background_color,
+                "crosshairMarkerBorderWidth": crosshair_marker_border_width,
+                "lastPriceAnimation": _resolve_last_price_animation(
+                    last_price_animation
+                ),
+            }
+        ),
+    }
+    column_mapping = {"time": timestamp, "value": value}
+    if color_column is not None:
+        column_mapping["color"] = color_column
+    return SeriesSpec(
+        series_type="Line",
+        table=table,
+        column_mapping=column_mapping,
+        options=options,
+        markers=markers,
+        price_lines=price_lines,
+        marker_spec=marker_spec,
+        price_scale_options=_build_price_scale_options(
+            auto_scale,
+            scale_margin_top,
+            scale_margin_bottom,
+            mode=scale_mode,
+            invert_scale=scale_invert,
+            align_labels=scale_align_labels,
+            border_visible=scale_border_visible,
+            border_color=scale_border_color,
+            text_color=scale_text_color,
+            entire_text_only=scale_entire_text_only,
+            scale_visible=scale_visible,
+            ticks_visible=scale_ticks_visible,
+            minimum_width=scale_minimum_width,
+            ensure_edge_tick_marks_visible=scale_ensure_edge_tick_marks_visible,
+        ),
+        pane=pane,
+    )
+
+
+def area_series(
+    table: Any,
+    timestamp: str = "Timestamp",
+    value: str = "Value",
+    line_color: Optional[Color] = None,
+    top_color: Optional[Color] = None,
+    bottom_color: Optional[Color] = None,
+    relative_gradient: Optional[bool] = None,
+    invert_filled_area: Optional[bool] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_type: Optional[LineType] = None,
+    line_visible: Optional[bool] = None,
+    point_markers_visible: Optional[bool] = None,
+    point_markers_radius: Optional[float] = None,
+    crosshair_marker_visible: Optional[bool] = None,
+    crosshair_marker_radius: Optional[float] = None,
+    crosshair_marker_border_color: Optional[Color] = None,
+    crosshair_marker_background_color: Optional[Color] = None,
+    crosshair_marker_border_width: Optional[float] = None,
+    last_price_animation: Optional[LastPriceAnimationMode] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    line_color_column: Optional[str] = None,
+    top_color_column: Optional[str] = None,
+    bottom_color_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+) -> SeriesSpec:
+    """Create an area series specification.
+
+    Renders a filled area between the value line and the bottom of
+    the chart, using a vertical gradient between ``top_color`` and
+    ``bottom_color``.
+
+    Args:
+        table (Any): Deephaven table with the data.
+        timestamp (str): Column name for the time axis.
+        value (str): Column name for the y-axis.
+        line_color (Optional[Color]): Line color at the top of the
+            filled area.
+        top_color (Optional[Color]): Gradient fill color at the top.
+        bottom_color (Optional[Color]): Gradient fill color at the
+            bottom (typically transparent).
+        relative_gradient (Optional[bool]): If ``True``, the gradient
+            is measured relative to the series values rather than the
+            chart bounds.
+        invert_filled_area (Optional[bool]): If ``True``, fill above
+            the line instead of below.
+        line_width (Optional[LineWidth]): Stroke width 1–4 px.
+        line_style (Optional[LineStyle]): Dash pattern; see
+            :data:`LineStyle`.
+        line_type (Optional[LineType]): Geometry between data points;
+            see :data:`LineType`.
+        line_visible (Optional[bool]): Show the line.
+        point_markers_visible (Optional[bool]): Show point markers
+            at every data point.
+        point_markers_radius (Optional[float]): Point marker radius.
+        crosshair_marker_visible (Optional[bool]): Show the crosshair
+            marker dot.
+        crosshair_marker_radius (Optional[float]): Crosshair marker
+            radius.
+        crosshair_marker_border_color (Optional[Color]): Crosshair
+            marker border color.
+        crosshair_marker_background_color (Optional[Color]): Crosshair
+            marker fill color.
+        crosshair_marker_border_width (Optional[float]): Crosshair
+            marker border width.
+        last_price_animation (Optional[LastPriceAnimationMode]):
+            Last-price dot animation.
+        last_value_visible (Optional[bool]): Show the last-value badge.
+        title (Optional[str]): Title.
+        visible (Optional[bool]): Series visibility.
+        price_scale_id (Optional[str]): Price-scale ID.
+        price_format (Optional[PriceFormat]): Per-series price format.
+        price_line_visible (Optional[bool]): Auto last-price line.
+        price_line_source (Optional[PriceLineSource]): Source bar.
+        price_line_width (Optional[LineWidth]): Price-line width.
+        price_line_color (Optional[Color]): Price-line color.
+        price_line_style (Optional[LineStyle]): Price-line dash.
+        base_line_visible (Optional[bool]): Show the baseline.
+        base_line_color (Optional[Color]): Baseline color.
+        base_line_width (Optional[LineWidth]): Baseline width.
+        base_line_style (Optional[LineStyle]): Baseline dash.
+        auto_scale (Optional[bool]): Auto-fit the price scale.
+        scale_margin_top (Optional[float]): Top margin fraction.
+        scale_margin_bottom (Optional[float]): Bottom margin fraction.
+        scale_mode (Optional[PriceScaleMode]): Scale mode.
+        scale_invert (Optional[bool]): Invert the scale.
+        scale_align_labels (Optional[bool]): Align labels with pixels.
+        scale_border_visible (Optional[bool]): Show scale border.
+        scale_border_color (Optional[Color]): Border color.
+        scale_text_color (Optional[Color]): Label color.
+        scale_entire_text_only (Optional[bool]): Only complete labels.
+        scale_visible (Optional[bool]): Show the scale.
+        scale_ticks_visible (Optional[bool]): Show tick marks.
+        scale_minimum_width (Optional[int]): Minimum width in pixels.
+        scale_ensure_edge_tick_marks_visible (Optional[bool]): Force
+            edge ticks.
+        line_color_column (Optional[str]): Per-row line color column.
+        top_color_column (Optional[str]): Per-row top-color column.
+        bottom_color_column (Optional[str]): Per-row bottom-color
+            column.
+        pane (Optional[int]): Pane index.
+        markers (Optional[list[Marker]]): Static markers.
+        price_lines (Optional[list[PriceLine]]): Horizontal price
+            lines.
+        marker_spec (Optional[MarkerSpec]): Table-driven marker spec.
+
+    Returns:
+        SeriesSpec: An area-series specification.
+
+    Example:
+        >>> s = tvl.area_series(my_table, timestamp="Timestamp",
+        ...                     value="Price",
+        ...                     top_color="rgba(38,166,154,0.4)",
+        ...                     bottom_color="rgba(38,166,154,0)")
+    """
+    _validate_price_format(price_format)
+    options = {
+        **_build_common_options(
+            last_value_visible=last_value_visible,
+            title=title,
+            visible=visible,
+            price_scale_id=price_scale_id,
+            price_format=price_format,
+            price_line_visible=price_line_visible,
+            price_line_source=price_line_source,
+            price_line_width=price_line_width,
+            price_line_color=price_line_color,
+            price_line_style=price_line_style,
+            base_line_visible=base_line_visible,
+            base_line_color=base_line_color,
+            base_line_width=base_line_width,
+            base_line_style=base_line_style,
+        ),
+        **_filter_none(
+            {
+                "lineColor": line_color,
+                "topColor": top_color,
+                "bottomColor": bottom_color,
+                "relativeGradient": relative_gradient,
+                "invertFilledArea": invert_filled_area,
+                "lineWidth": line_width,
+                "lineStyle": _resolve_line_style(line_style),
+                "lineType": _resolve_line_type(line_type),
+                "lineVisible": line_visible,
+                "pointMarkersVisible": point_markers_visible,
+                "pointMarkersRadius": point_markers_radius,
+                "crosshairMarkerVisible": crosshair_marker_visible,
+                "crosshairMarkerRadius": crosshair_marker_radius,
+                "crosshairMarkerBorderColor": crosshair_marker_border_color,
+                "crosshairMarkerBackgroundColor": crosshair_marker_background_color,
+                "crosshairMarkerBorderWidth": crosshair_marker_border_width,
+                "lastPriceAnimation": _resolve_last_price_animation(
+                    last_price_animation
+                ),
+            }
+        ),
+    }
+    column_mapping = {"time": timestamp, "value": value}
+    if line_color_column is not None:
+        column_mapping["lineColor"] = line_color_column
+    if top_color_column is not None:
+        column_mapping["topColor"] = top_color_column
+    if bottom_color_column is not None:
+        column_mapping["bottomColor"] = bottom_color_column
+    return SeriesSpec(
+        series_type="Area",
+        table=table,
+        column_mapping=column_mapping,
+        options=options,
+        markers=markers,
+        price_lines=price_lines,
+        marker_spec=marker_spec,
+        price_scale_options=_build_price_scale_options(
+            auto_scale,
+            scale_margin_top,
+            scale_margin_bottom,
+            mode=scale_mode,
+            invert_scale=scale_invert,
+            align_labels=scale_align_labels,
+            border_visible=scale_border_visible,
+            border_color=scale_border_color,
+            text_color=scale_text_color,
+            entire_text_only=scale_entire_text_only,
+            scale_visible=scale_visible,
+            ticks_visible=scale_ticks_visible,
+            minimum_width=scale_minimum_width,
+            ensure_edge_tick_marks_visible=scale_ensure_edge_tick_marks_visible,
+        ),
+        pane=pane,
+    )
+
+
+def baseline_series(
+    table: Any,
+    timestamp: str = "Timestamp",
+    value: str = "Value",
+    base_value: Optional[float] = None,
+    top_line_color: Optional[Color] = None,
+    top_fill_color1: Optional[Color] = None,
+    top_fill_color2: Optional[Color] = None,
+    bottom_line_color: Optional[Color] = None,
+    bottom_fill_color1: Optional[Color] = None,
+    bottom_fill_color2: Optional[Color] = None,
+    line_width: Optional[LineWidth] = None,
+    line_style: Optional[LineStyle] = None,
+    line_type: Optional[LineType] = None,
+    line_visible: Optional[bool] = None,
+    relative_gradient: Optional[bool] = None,
+    point_markers_visible: Optional[bool] = None,
+    point_markers_radius: Optional[float] = None,
+    crosshair_marker_visible: Optional[bool] = None,
+    crosshair_marker_radius: Optional[float] = None,
+    crosshair_marker_border_color: Optional[Color] = None,
+    crosshair_marker_background_color: Optional[Color] = None,
+    crosshair_marker_border_width: Optional[float] = None,
+    last_price_animation: Optional[LastPriceAnimationMode] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    top_line_color_column: Optional[str] = None,
+    top_fill_color1_column: Optional[str] = None,
+    top_fill_color2_column: Optional[str] = None,
+    bottom_line_color_column: Optional[str] = None,
+    bottom_fill_color1_column: Optional[str] = None,
+    bottom_fill_color2_column: Optional[str] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+) -> SeriesSpec:
+    """Create a baseline series specification.
+
+    A baseline series renders an area between the value line and a
+    horizontal "base value", with different gradient fills above
+    (top) and below (bottom) the baseline.  Useful for visualizing
+    diff-from-reference quantities (P&L vs 0, return vs index, etc.).
+
+    Args:
+        table (Any): Deephaven table with the data.
+        timestamp (str): Column name for the time axis.
+        value (str): Column name for the y-axis.
+        base_value (Optional[float]): The baseline price level.  The
+            fill color flips at this y-value.  Defaults to ``0.0``.
+        top_line_color (Optional[Color]): Line color above the baseline.
+        top_fill_color1 (Optional[Color]): Gradient stop 1 (closer to
+            line) for the area above the baseline.
+        top_fill_color2 (Optional[Color]): Gradient stop 2 (farther
+            from line) above the baseline.
+        bottom_line_color (Optional[Color]): Line color below the
+            baseline.
+        bottom_fill_color1 (Optional[Color]): Gradient stop 1 below.
+        bottom_fill_color2 (Optional[Color]): Gradient stop 2 below.
+        line_width (Optional[LineWidth]): Stroke width 1–4 px.
+        line_style (Optional[LineStyle]): Dash pattern.
+        line_type (Optional[LineType]): Geometry; see :data:`LineType`.
+        line_visible (Optional[bool]): Show the line.
+        relative_gradient (Optional[bool]): Gradient measured relative
+            to series values rather than chart bounds.
+        point_markers_visible (Optional[bool]): Show point markers.
+        point_markers_radius (Optional[float]): Point marker radius.
+        crosshair_marker_visible (Optional[bool]): Show crosshair
+            marker.
+        crosshair_marker_radius (Optional[float]): Crosshair marker
+            radius.
+        crosshair_marker_border_color (Optional[Color]): Crosshair
+            marker border color.
+        crosshair_marker_background_color (Optional[Color]): Crosshair
+            marker fill color.
+        crosshair_marker_border_width (Optional[float]): Crosshair
+            marker border width.
+        last_price_animation (Optional[LastPriceAnimationMode]):
+            Last-price dot animation.
+        last_value_visible (Optional[bool]): Show the last-value badge.
+        title (Optional[str]): Title.
+        visible (Optional[bool]): Series visibility.
+        price_scale_id (Optional[str]): Price-scale ID.
+        price_format (Optional[PriceFormat]): Per-series price format.
+        price_line_visible (Optional[bool]): Auto last-price line.
+        price_line_source (Optional[PriceLineSource]): Source bar.
+        price_line_width (Optional[LineWidth]): Price-line width.
+        price_line_color (Optional[Color]): Price-line color.
+        price_line_style (Optional[LineStyle]): Price-line dash.
+        base_line_visible (Optional[bool]): Show the secondary
+            baseline (TVL's built-in baseline at 0/index — not the
+            same as ``base_value``).
+        base_line_color (Optional[Color]): Secondary baseline color.
+        base_line_width (Optional[LineWidth]): Secondary baseline
+            width.
+        base_line_style (Optional[LineStyle]): Secondary baseline
+            dash.
+        auto_scale (Optional[bool]): Auto-fit the price scale.
+        scale_margin_top (Optional[float]): Top margin fraction.
+        scale_margin_bottom (Optional[float]): Bottom margin fraction.
+        scale_mode (Optional[PriceScaleMode]): Scale mode.
+        scale_invert (Optional[bool]): Invert the scale.
+        scale_align_labels (Optional[bool]): Align labels with pixels.
+        scale_border_visible (Optional[bool]): Show scale border.
+        scale_border_color (Optional[Color]): Border color.
+        scale_text_color (Optional[Color]): Label color.
+        scale_entire_text_only (Optional[bool]): Only complete labels.
+        scale_visible (Optional[bool]): Show the scale.
+        scale_ticks_visible (Optional[bool]): Show tick marks.
+        scale_minimum_width (Optional[int]): Minimum width in pixels.
+        scale_ensure_edge_tick_marks_visible (Optional[bool]): Force
+            edge ticks.
+        top_line_color_column (Optional[str]): Per-row top line color
+            column.
+        top_fill_color1_column (Optional[str]): Per-row top gradient
+            stop 1 column.
+        top_fill_color2_column (Optional[str]): Per-row top gradient
+            stop 2 column.
+        bottom_line_color_column (Optional[str]): Per-row bottom line
+            color column.
+        bottom_fill_color1_column (Optional[str]): Per-row bottom
+            gradient stop 1 column.
+        bottom_fill_color2_column (Optional[str]): Per-row bottom
+            gradient stop 2 column.
+        pane (Optional[int]): Pane index.
+        markers (Optional[list[Marker]]): Static markers.
+        price_lines (Optional[list[PriceLine]]): Horizontal price
+            lines.
+        marker_spec (Optional[MarkerSpec]): Table-driven marker spec.
+
+    Returns:
+        SeriesSpec: A baseline-series specification.
+
+    Example:
+        >>> s = tvl.baseline_series(pnl, timestamp="Timestamp",
+        ...                         value="Pnl", base_value=0.0)
+    """
+    _validate_price_format(price_format)
+    options = {
+        **_build_common_options(
+            last_value_visible=last_value_visible,
+            title=title,
+            visible=visible,
+            price_scale_id=price_scale_id,
+            price_format=price_format,
+            price_line_visible=price_line_visible,
+            price_line_source=price_line_source,
+            price_line_width=price_line_width,
+            price_line_color=price_line_color,
+            price_line_style=price_line_style,
+            base_line_visible=base_line_visible,
+            base_line_color=base_line_color,
+            base_line_width=base_line_width,
+            base_line_style=base_line_style,
+        ),
+        **_filter_none(
+            {
+                **(
+                    {"baseValue": {"type": "price", "price": base_value}}
+                    if base_value is not None
+                    else {}
+                ),
+                "topLineColor": top_line_color,
+                "topFillColor1": top_fill_color1,
+                "topFillColor2": top_fill_color2,
+                "bottomLineColor": bottom_line_color,
+                "bottomFillColor1": bottom_fill_color1,
+                "bottomFillColor2": bottom_fill_color2,
+                "lineWidth": line_width,
+                "lineStyle": _resolve_line_style(line_style),
+                "lineType": _resolve_line_type(line_type),
+                "lineVisible": line_visible,
+                "relativeGradient": relative_gradient,
+                "pointMarkersVisible": point_markers_visible,
+                "pointMarkersRadius": point_markers_radius,
+                "crosshairMarkerVisible": crosshair_marker_visible,
+                "crosshairMarkerRadius": crosshair_marker_radius,
+                "crosshairMarkerBorderColor": crosshair_marker_border_color,
+                "crosshairMarkerBackgroundColor": crosshair_marker_background_color,
+                "crosshairMarkerBorderWidth": crosshair_marker_border_width,
+                "lastPriceAnimation": _resolve_last_price_animation(
+                    last_price_animation
+                ),
+            }
+        ),
+    }
+    column_mapping = {"time": timestamp, "value": value}
+    if top_line_color_column is not None:
+        column_mapping["topLineColor"] = top_line_color_column
+    if top_fill_color1_column is not None:
+        column_mapping["topFillColor1"] = top_fill_color1_column
+    if top_fill_color2_column is not None:
+        column_mapping["topFillColor2"] = top_fill_color2_column
+    if bottom_line_color_column is not None:
+        column_mapping["bottomLineColor"] = bottom_line_color_column
+    if bottom_fill_color1_column is not None:
+        column_mapping["bottomFillColor1"] = bottom_fill_color1_column
+    if bottom_fill_color2_column is not None:
+        column_mapping["bottomFillColor2"] = bottom_fill_color2_column
+    return SeriesSpec(
+        series_type="Baseline",
+        table=table,
+        column_mapping=column_mapping,
+        options=options,
+        markers=markers,
+        price_lines=price_lines,
+        marker_spec=marker_spec,
+        price_scale_options=_build_price_scale_options(
+            auto_scale,
+            scale_margin_top,
+            scale_margin_bottom,
+            mode=scale_mode,
+            invert_scale=scale_invert,
+            align_labels=scale_align_labels,
+            border_visible=scale_border_visible,
+            border_color=scale_border_color,
+            text_color=scale_text_color,
+            entire_text_only=scale_entire_text_only,
+            scale_visible=scale_visible,
+            ticks_visible=scale_ticks_visible,
+            minimum_width=scale_minimum_width,
+            ensure_edge_tick_marks_visible=scale_ensure_edge_tick_marks_visible,
+        ),
+        pane=pane,
+    )
+
+
+def histogram_series(
+    table: Any,
+    timestamp: str = "Timestamp",
+    value: str = "Value",
+    color: Optional[Color] = None,
+    base: Optional[float] = None,
+    color_column: Optional[str] = None,
+    last_value_visible: Optional[bool] = None,
+    title: Optional[str] = None,
+    visible: Optional[bool] = None,
+    price_scale_id: Optional[str] = None,
+    price_format: Optional[PriceFormat] = None,
+    price_line_visible: Optional[bool] = None,
+    price_line_source: Optional[PriceLineSource] = None,
+    price_line_width: Optional[LineWidth] = None,
+    price_line_color: Optional[Color] = None,
+    price_line_style: Optional[LineStyle] = None,
+    base_line_visible: Optional[bool] = None,
+    base_line_color: Optional[Color] = None,
+    base_line_width: Optional[LineWidth] = None,
+    base_line_style: Optional[LineStyle] = None,
+    auto_scale: Optional[bool] = None,
+    scale_margin_top: Optional[float] = None,
+    scale_margin_bottom: Optional[float] = None,
+    scale_mode: Optional[PriceScaleMode] = None,
+    scale_invert: Optional[bool] = None,
+    scale_align_labels: Optional[bool] = None,
+    scale_border_visible: Optional[bool] = None,
+    scale_border_color: Optional[Color] = None,
+    scale_text_color: Optional[Color] = None,
+    scale_entire_text_only: Optional[bool] = None,
+    scale_visible: Optional[bool] = None,
+    scale_ticks_visible: Optional[bool] = None,
+    scale_minimum_width: Optional[int] = None,
+    scale_ensure_edge_tick_marks_visible: Optional[bool] = None,
+    pane: Optional[int] = None,
+    markers: Optional[list[Marker]] = None,
+    price_lines: Optional[list[PriceLine]] = None,
+    marker_spec: Optional[MarkerSpec] = None,
+    auto_bin: Optional[bool] = None,
+    bin_width: Optional[str] = None,
+    bin_count: Optional[int] = None,
+    agg: str = "sum",
+) -> SeriesSpec:
+    """Create a histogram series specification.
+
+    A histogram series renders one vertical bar per time bucket with
+    height equal to the per-bin aggregated value.  Use the ``agg``
+    parameter to select the reduction (sum / count / avg / last).
+
+    Args:
+        table (Any): Deephaven table with the data.
+        timestamp (str): Column name for the time axis.
+        value (str): Column name supplying the bar height value.
+        color (Optional[Color]): Fixed bar color (CSS color).
+        base (Optional[float]): Baseline value from which bars are
+            drawn (default ``0``).
+        color_column (Optional[str]): Per-row bar color column.
+        last_value_visible (Optional[bool]): Show the last-value
+            badge.
+        title (Optional[str]): Title shown in the series tooltip /
+            legend.
+        visible (Optional[bool]): Series visibility.
+        price_scale_id (Optional[str]): Price-scale ID.
+        price_format (Optional[PriceFormat]): Per-series price format.
+        price_line_visible (Optional[bool]): Auto last-price line.
+        price_line_source (Optional[PriceLineSource]): Source bar.
+        price_line_width (Optional[LineWidth]): Price-line width.
+        price_line_color (Optional[Color]): Price-line color.
+        price_line_style (Optional[LineStyle]): Price-line dash.
+        base_line_visible (Optional[bool]): Show the baseline.
+        base_line_color (Optional[Color]): Baseline color.
+        base_line_width (Optional[LineWidth]): Baseline width.
+        base_line_style (Optional[LineStyle]): Baseline dash.
+        auto_scale (Optional[bool]): Auto-fit the price scale.
+        scale_margin_top (Optional[float]): Top margin fraction.
+        scale_margin_bottom (Optional[float]): Bottom margin fraction.
+        scale_mode (Optional[PriceScaleMode]): Scale mode.
+        scale_invert (Optional[bool]): Invert the scale.
+        scale_align_labels (Optional[bool]): Align labels with pixels.
+        scale_border_visible (Optional[bool]): Show scale border.
+        scale_border_color (Optional[Color]): Border color.
+        scale_text_color (Optional[Color]): Label color.
+        scale_entire_text_only (Optional[bool]): Only complete labels.
+        scale_visible (Optional[bool]): Show the scale.
+        scale_ticks_visible (Optional[bool]): Show tick marks.
+        scale_minimum_width (Optional[int]): Minimum width in pixels.
+        scale_ensure_edge_tick_marks_visible (Optional[bool]): Force
+            edge ticks.
+        pane (Optional[int]): Pane index.
+        markers (Optional[list[Marker]]): Static markers.
+        price_lines (Optional[list[PriceLine]]): Horizontal price
+            lines.
+        marker_spec (Optional[MarkerSpec]): Table-driven marker spec.
+        auto_bin (Optional[bool]): Tri-state auto-bin control.
+            ``None`` (default) auto-bins when the table exceeds 5000
+            rows; ``True`` forces aggregation even for small tables;
+            ``False`` ships the raw table.
+        bin_width (Optional[str]): ISO 8601 duration override (e.g.
+            ``"PT1S"``, ``"PT5M"``, ``"P1D"``).  Bypasses
+            nice-duration snapping.
+        bin_count (Optional[int]): Target number of bins for the
+            initial aggregation (default ``5000``).
+        agg (str): Per-bin reduction for the value column.  One of
+            ``"sum"`` (default), ``"count"``, ``"avg"``, ``"last"``.
+
+    Returns:
+        SeriesSpec: A histogram-series specification.
+
+    Raises:
+        ValueError: If ``agg`` is not one of the supported values.
+
+    Example:
+        >>> s = tvl.histogram_series(volumes, timestamp="Timestamp",
+        ...                          value="Volume", agg="sum")
+    """
+    _validate_price_format(price_format)
+    options = {
+        **_build_common_options(
+            last_value_visible=last_value_visible,
+            title=title,
+            visible=visible,
+            price_scale_id=price_scale_id,
+            price_format=price_format,
+            price_line_visible=price_line_visible,
+            price_line_source=price_line_source,
+            price_line_width=price_line_width,
+            price_line_color=price_line_color,
+            price_line_style=price_line_style,
+            base_line_visible=base_line_visible,
+            base_line_color=base_line_color,
+            base_line_width=base_line_width,
+            base_line_style=base_line_style,
+        ),
+        **_filter_none(
+            {
+                "color": color,
+                "base": base,
+            }
+        ),
+    }
+    column_mapping = {"time": timestamp, "value": value}
+    if color_column is not None:
+        column_mapping["color"] = color_column
+    from .auto_bin import HIST_AGGS as _HIST_AGGS
+
+    if agg not in _HIST_AGGS:
+        raise ValueError(f"agg must be one of {sorted(_HIST_AGGS)}, got {agg!r}")
+    return SeriesSpec(
+        series_type="Histogram",
+        table=table,
+        column_mapping=column_mapping,
+        options=options,
+        markers=markers,
+        price_lines=price_lines,
+        marker_spec=marker_spec,
+        price_scale_options=_build_price_scale_options(
+            auto_scale,
+            scale_margin_top,
+            scale_margin_bottom,
+            mode=scale_mode,
+            invert_scale=scale_invert,
+            align_labels=scale_align_labels,
+            border_visible=scale_border_visible,
+            border_color=scale_border_color,
+            text_color=scale_text_color,
+            entire_text_only=scale_entire_text_only,
+            scale_visible=scale_visible,
+            ticks_visible=scale_ticks_visible,
+            minimum_width=scale_minimum_width,
+            ensure_edge_tick_marks_visible=scale_ensure_edge_tick_marks_visible,
+        ),
+        pane=pane,
+        auto_bin=auto_bin,
+        bin_width=bin_width,
+        bin_count=bin_count,
+        agg=agg,
+    )
diff --git a/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/utils.py b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/utils.py
new file mode 100644
index 000000000..d379eee5c
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/deephaven/plot/tradingview_lightweight/utils.py
@@ -0,0 +1,70 @@
+"""Utility functions for the TradingView Lightweight Charts plugin.
+
+These mirror the top-level utility functions in the JavaScript library.
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+
+def is_business_day(time: Any) -> bool:
+    """Return True if *time* is a BusinessDay dict.
+
+    A BusinessDay is a dict with integer keys ``year``, ``month``, and ``day``.
+    This mirrors the JS ``isBusinessDay()`` type guard.
+
+    Args:
+        time: A time value -- either a BusinessDay dict, a numeric UTC timestamp,
+            or an ISO date string.
+
+    Returns:
+        ``True`` if *time* is a ``dict`` containing ``year``, ``month``, and
+        ``day`` integer keys; ``False`` otherwise.
+
+    Example::
+
+        from deephaven.plot.tradingview_lightweight import is_business_day
+
+        is_business_day({"year": 2024, "month": 3, "day": 15})  # True
+        is_business_day(1710460800)                              # False
+        is_business_day("2024-03-15")                           # False
+    """
+    # Explicitly exclude bool: in Python, bool is a subclass of int
+    return (
+        isinstance(time, dict)
+        and isinstance(time.get("year"), int)
+        and not isinstance(time.get("year"), bool)
+        and isinstance(time.get("month"), int)
+        and not isinstance(time.get("month"), bool)
+        and isinstance(time.get("day"), int)
+        and not isinstance(time.get("day"), bool)
+    )
+
+
+def is_utc_timestamp(time: Any) -> bool:
+    """Return True if *time* is a numeric UTC timestamp.
+
+    A UTCTimestamp is a Unix epoch timestamp (seconds since 1970-01-01 UTC)
+    expressed as an ``int`` or ``float``. This mirrors the JS ``isUTCTimestamp()``
+    type guard.
+
+    Args:
+        time: A time value -- either a BusinessDay dict, a numeric UTC timestamp,
+            or an ISO date string.
+
+    Returns:
+        ``True`` if *time* is an ``int`` or ``float`` (but not a ``bool``);
+        ``False`` otherwise.
+
+    Example::
+
+        from deephaven.plot.tradingview_lightweight import is_utc_timestamp
+
+        is_utc_timestamp(1710460800)                              # True
+        is_utc_timestamp(1710460800.5)                           # True
+        is_utc_timestamp({"year": 2024, "month": 3, "day": 15}) # False
+        is_utc_timestamp("2024-03-15")                           # False
+    """
+    # Explicitly exclude bool: in Python, bool is a subclass of int
+    return isinstance(time, (int, float)) and not isinstance(time, bool)
diff --git a/plugins/tradingview-lightweight/src/js/--selector b/plugins/tradingview-lightweight/src/js/--selector
new file mode 100644
index 000000000..a586e5617
Binary files /dev/null and b/plugins/tradingview-lightweight/src/js/--selector differ
diff --git a/plugins/tradingview-lightweight/src/js/e2e/.eslintrc.cjs b/plugins/tradingview-lightweight/src/js/e2e/.eslintrc.cjs
new file mode 100644
index 000000000..553f6a264
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/.eslintrc.cjs
@@ -0,0 +1,12 @@
+// The Playwright e2e suite uses test idioms the plugin's src/ rules forbid
+// (sequential awaits in loops, non-null assertions on locator results) and
+// imports @playwright/test, which is a repo-root devDependency rather than a
+// plugin dependency. Relax those here, scoped to e2e/.
+module.exports = {
+  rules: {
+    'import/no-extraneous-dependencies': 'off',
+    'no-restricted-syntax': 'off',
+    'no-await-in-loop': 'off',
+    '@typescript-eslint/no-non-null-assertion': 'off',
+  },
+};
diff --git a/plugins/tradingview-lightweight/src/js/e2e/app.d/tooltip.app b/plugins/tradingview-lightweight/src/js/e2e/app.d/tooltip.app
new file mode 100644
index 000000000..9bf85e9dc
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/app.d/tooltip.app
@@ -0,0 +1,6 @@
+type=script
+scriptType=python
+enabled=true
+id=tvl.e2e.tooltip
+name=TVL Tooltip E2E
+file_0=tooltip_demo.py
diff --git a/plugins/tradingview-lightweight/src/js/e2e/app.d/tooltip_demo.py b/plugins/tradingview-lightweight/src/js/e2e/app.d/tooltip_demo.py
new file mode 100644
index 000000000..da4f7a068
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/app.d/tooltip_demo.py
@@ -0,0 +1,25 @@
+"""E2E fixture: a two-series line chart with the tracking tooltip enabled.
+
+Loaded as a Deephaven Application-mode field (see ``tooltip.app``) so the chart
+auto-opens as a panel when the e2e server boots. The Playwright spec hovers the
+chart and asserts the ``data-tvl-tooltip`` DOM seam.
+"""
+from deephaven import empty_table
+from deephaven.time import to_j_instant
+from deephaven.plot import tradingview_lightweight as tvl  # type: ignore[attr-defined]
+
+_start = to_j_instant("2024-01-01T00:00:00 ET")
+_t = empty_table(500).update(
+    [
+        "Timestamp = _start + (long)(ii * 86_400_000_000_000L)",
+        "Price = 100 + Math.sin(ii * 0.05) * 20",
+        "Ema = 100 + Math.sin(ii * 0.05 - 0.4) * 16",
+    ]
+)
+
+tooltip_chart = tvl.chart(
+    tvl.line(_t, timestamp="Timestamp", value="Price", title="Price"),
+    tvl.line(_t, timestamp="Timestamp", value="Ema", title="EMA"),
+    tooltip_visible=True,
+    tooltip_value_precision=2,
+)
diff --git a/plugins/tradingview-lightweight/src/js/e2e/playwright.config.ts b/plugins/tradingview-lightweight/src/js/e2e/playwright.config.ts
new file mode 100644
index 000000000..4064f7829
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/playwright.config.ts
@@ -0,0 +1,69 @@
+/**
+ * Playwright config for the TVL end-to-end suite.
+ *
+ * Unlike the unit tests (jest, jsdom), these run the REAL plugin inside a real
+ * Deephaven IDE in Chromium, so they catch wiring/serialization/render bugs the
+ * unit tests can't. The Deephaven server is booted and torn down automatically
+ * by the `webServer` block below — you just run `npm run test:e2e`.
+ *
+ * Prerequisite (one-time): `bash e2e/setup-venv.sh` to provision a venv with
+ * deephaven-server + the plugin installed. See ../../../AGENTS.md.
+ */
+import { existsSync } from 'node:fs';
+import { defineConfig, devices } from '@playwright/test';
+
+const PORT = process.env.TVL_E2E_PORT ?? '10000';
+const baseURL = `http://localhost:${PORT}/ide/`;
+
+// Browser resolution: prefer an explicit TVL_E2E_CHROMIUM, then a system
+// Chromium (handy in sandboxes where `playwright install` can't reach the
+// network), else fall back to Playwright's bundled browser (the CI path after
+// `npx playwright install chromium`).
+const systemChromium = process.env.TVL_E2E_CHROMIUM ?? '/usr/bin/chromium';
+const executablePath = existsSync(systemChromium) ? systemChromium : undefined;
+
+const isCI = process.env.CI != null && process.env.CI !== '';
+
+export default defineConfig({
+  testDir: '.',
+  testMatch: /.*\.spec\.ts$/,
+  fullyParallel: false,
+  workers: 1,
+  timeout: 120 * 1000,
+  expect: { timeout: 20 * 1000 },
+  forbidOnly: isCI,
+  retries: 0,
+  reporter: [['list']],
+  use: {
+    baseURL,
+    navigationTimeout: 60 * 1000,
+    trace: 'retain-on-failure',
+    screenshot: 'only-on-failure',
+    launchOptions: {
+      executablePath,
+      // --no-sandbox: required when running Chromium as root in the sandbox.
+      args: ['--no-sandbox'],
+    },
+  },
+  projects: [
+    {
+      name: 'chromium',
+      use: {
+        ...devices['Desktop Chrome'],
+        viewport: { width: 1600, height: 1000 },
+      },
+    },
+  ],
+  webServer: {
+    // cwd defaults to this config's directory (e2e/), and start-server.sh
+    // resolves its own paths via BASH_SOURCE, so it is cwd-independent.
+    command: 'bash start-server.sh',
+    url: baseURL,
+    timeout: 150 * 1000,
+    // Reuse a server you already have up locally for fast iteration; in CI
+    // always boot a fresh one.
+    reuseExistingServer: !isCI,
+    stdout: 'pipe',
+    stderr: 'pipe',
+  },
+});
diff --git a/plugins/tradingview-lightweight/src/js/e2e/setup-venv.sh b/plugins/tradingview-lightweight/src/js/e2e/setup-venv.sh
new file mode 100755
index 000000000..3b19fc836
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/setup-venv.sh
@@ -0,0 +1,38 @@
+#!/usr/bin/env bash
+#
+# One-time provisioning for the Playwright e2e suite.
+#
+# Creates a Python venv with deephaven-server and installs this plugin into it
+# (so the DH server can serve the TVL JS bundle). Run once; afterwards
+# `npm run test:e2e` boots the server and runs the tests on its own.
+#
+# Re-run this only when the Python deps change. After *JS* changes you do NOT
+# need to re-run it — `npm run test:e2e` rebuilds the bundle and start-server.sh
+# syncs it into the venv on every run.
+#
+# Override the venv location with TVL_E2E_VENV (defaults to <plugin>/.venv).
+set -euo pipefail
+
+HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PLUGIN_ROOT="$(cd "$HERE/../../.." && pwd)"   # e2e -> js -> src -> <plugin root>
+VENV="${TVL_E2E_VENV:-$PLUGIN_ROOT/.venv}"
+
+if ! command -v uv >/dev/null 2>&1; then
+  echo "[e2e:setup] 'uv' is required (https://docs.astral.sh/uv/). Aborting." >&2
+  exit 1
+fi
+
+echo "[e2e:setup] venv: $VENV"
+uv venv "$VENV" >/dev/null 2>&1 || true
+
+echo "[e2e:setup] installing deephaven-server + plugin runtime deps..."
+uv pip install --python "$VENV/bin/python" \
+  deephaven-server "deephaven-plugin-utilities>=0.0.2"
+
+echo "[e2e:setup] building the JS bundle..."
+npm run build --prefix "$PLUGIN_ROOT/src/js"
+
+echo "[e2e:setup] installing the plugin into the venv..."
+uv pip install --python "$VENV/bin/python" --force-reinstall --no-deps "$PLUGIN_ROOT"
+
+echo "[e2e:setup] done. Run the suite with:  npm run test:e2e  (from src/js)"
diff --git a/plugins/tradingview-lightweight/src/js/e2e/start-server.sh b/plugins/tradingview-lightweight/src/js/e2e/start-server.sh
new file mode 100755
index 000000000..e53ed0c89
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/start-server.sh
@@ -0,0 +1,42 @@
+#!/usr/bin/env bash
+#
+# Boot a Deephaven server for the Playwright e2e suite. Invoked by Playwright's
+# `webServer` config; not meant to be run by hand (though it works).
+#
+# Two sandbox-specific quirks are handled here, both load-bearing:
+#   1. stdin must stay OPEN. The `deephaven` CLI prints "Press Control-C to
+#      exit" and reads stdin; on stdin EOF (which is what a backgrounded /
+#      non-TTY process gets) it aborts immediately. `tail -f /dev/null |` feeds
+#      it an endless, dataless stdin so it never sees EOF.
+#   2. stdout must be a PIPE, not a file. `| cat` keeps it a pipe.
+#
+# It also syncs the freshly built JS bundle into the installed package, because
+# uv's build isolation can package a stale bundle — without this the server
+# could serve old JS and the tests would pass/fail against the wrong code.
+set -uo pipefail
+
+HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PLUGIN_ROOT="$(cd "$HERE/../../.." && pwd)"   # e2e -> js -> src -> <plugin root>
+VENV="${TVL_E2E_VENV:-$PLUGIN_ROOT/.venv}"
+DEEPHAVEN="$VENV/bin/deephaven"
+PORT="${TVL_E2E_PORT:-10000}"
+
+if [[ ! -x "$DEEPHAVEN" ]]; then
+  echo "[e2e] deephaven-server not found in $VENV." >&2
+  echo "[e2e] Provision it once with:  bash $HERE/setup-venv.sh" >&2
+  exit 1
+fi
+
+# Sync the current bundle into the installed package so the e2e exercises HEAD.
+DEST=$(ls -d "$VENV"/lib/python*/site-packages/deephaven/plot/tradingview_lightweight/_js/dist 2>/dev/null | head -1)
+if [[ -n "${DEST:-}" && -d "$PLUGIN_ROOT/src/js/dist" ]]; then
+  cp -rf "$PLUGIN_ROOT/src/js/dist/." "$DEST"/
+  echo "[e2e] synced freshly built JS bundle into the installed package"
+else
+  echo "[e2e] WARNING: could not sync JS bundle (built dist or install missing)" >&2
+fi
+
+echo "[e2e] starting deephaven server on :$PORT (anonymous auth, app.d=$HERE/app.d)"
+tail -f /dev/null | "$DEEPHAVEN" server --no-browser --port "$PORT" \
+  --jvm-args "-Ddeephaven.application.dir=$HERE/app.d -DAuthHandlers=io.deephaven.auth.AnonymousAuthenticationHandler" \
+  2>&1 | cat
diff --git a/plugins/tradingview-lightweight/src/js/e2e/tooltip.spec.ts b/plugins/tradingview-lightweight/src/js/e2e/tooltip.spec.ts
new file mode 100644
index 000000000..5f9fd4794
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/e2e/tooltip.spec.ts
@@ -0,0 +1,114 @@
+import { test, expect, type Page } from '@playwright/test';
+
+/**
+ * End-to-end coverage for the tracking tooltip. The `tooltip_chart` field from
+ * e2e/app.d/tooltip_demo.py is opened from the Panels menu; we hover its canvas
+ * and read the `data-tvl-tooltip` DOM seam (the same seam the unit tests use).
+ */
+
+const CHART = '.dh-tvl-chart';
+const TOOLTIP = '.tvl-tooltip';
+const FIELD = 'tooltip_chart'; // the Application-mode field name from app.d
+
+async function waitForLoad(page: Page) {
+  await expect(page.locator('.loading-spinner')).toHaveCount(0);
+}
+
+/** Open an Application-mode field as a panel via the Panels menu. */
+async function openPanel(page: Page, name: string) {
+  const panels = page.getByRole('button', { name: 'Panels', exact: true });
+  await expect(panels).toBeEnabled();
+  const before = await page.locator('.dh-panel').count();
+  await panels.click();
+  const search = page.getByRole('searchbox', {
+    name: 'Find Table, Plot or Widget',
+    exact: true,
+  });
+  await search.fill(name);
+  const target = page.getByRole('button', { name, exact: true });
+  await expect(target).toBeEnabled();
+  await target.click();
+  await page.mouse.move(0, 0);
+  await expect(page.locator('.dh-panel')).toHaveCount(before + 1);
+  await waitForLoad(page);
+}
+
+/** Load the IDE and open the tooltip demo chart with data painted. */
+async function openChart(page: Page) {
+  await page.goto('/ide/');
+  await expect(
+    page.getByRole('progressbar', { name: 'Loading...', exact: true })
+  ).toHaveCount(0);
+  await waitForLoad(page);
+  await openPanel(page, FIELD);
+  await page.waitForSelector(CHART, { state: 'visible', timeout: 60 * 1000 });
+  await page.waitForTimeout(3000); // let series data arrive + paint
+}
+
+/** Hover a fraction across the chart and read the tooltip seam after it settles. */
+async function hoverAndRead(page: Page, frac: number) {
+  const box = await page.locator(CHART).boundingBox();
+  if (!box) throw new Error('chart has no bounding box');
+  const x = Math.round(box.x + box.width * frac);
+  const y = Math.round(box.y + box.height * 0.45);
+  await page.mouse.move(x, y);
+  await page.waitForTimeout(500); // let subscribeCrosshairMove fire + render
+  return page.evaluate(sel => {
+    const t = document.querySelector(sel) as HTMLElement | null;
+    if (!t) return null;
+    const title = t.querySelector('.tvl-tooltip-title') as HTMLElement | null;
+    return {
+      display: t.style.display,
+      data: t.getAttribute('data-tvl-tooltip') ?? '',
+      title: title?.textContent ?? '',
+      titleColor: title?.style.color ?? '',
+    };
+  }, TOOLTIP);
+}
+
+test('tracking tooltip shows the focused series on hover', async ({ page }) => {
+  await openChart(page);
+
+  // The tooltip element exists but is hidden until the cursor is over the chart.
+  await expect(page.locator(TOOLTIP)).toHaveCount(1);
+  expect(
+    await page
+      .locator(TOOLTIP)
+      .evaluate(el => (el as HTMLElement).style.display)
+  ).toBe('none');
+
+  const reading = await hoverAndRead(page, 0.5);
+  expect(reading, 'tooltip element should be present').not.toBeNull();
+  expect(reading!.display).toBe('block');
+  // Title is one of our two series, tinted with the series color.
+  expect(['Price', 'EMA']).toContain(reading!.title);
+  expect(reading!.titleColor).toMatch(/rgb|#/);
+  // Seam carries title | value | date; value reflects precision=2.
+  expect(reading!.data).toMatch(/\d+\.\d{2}/);
+  expect(reading!.data).toContain(reading!.title);
+});
+
+test('tooltip tracks across the chart and hides off-chart', async ({
+  page,
+}) => {
+  await openChart(page);
+
+  const titles = new Set<string>();
+  for (const frac of [0.2, 0.4, 0.6, 0.8]) {
+    const r = await hoverAndRead(page, frac);
+    expect(r!.display, `visible at frac=${frac}`).toBe('block');
+    expect(r!.data, `non-empty at frac=${frac}`).not.toBe('');
+    titles.add(r!.title);
+  }
+  // Every focused title is a real series title.
+  for (const t of titles) expect(['Price', 'EMA']).toContain(t);
+
+  // Moving the cursor far off the chart hides the tooltip.
+  await page.mouse.move(5, 5);
+  await page.waitForTimeout(400);
+  expect(
+    await page
+      .locator(TOOLTIP)
+      .evaluate(el => (el as HTMLElement).style.display)
+  ).toBe('none');
+});
diff --git a/plugins/tradingview-lightweight/src/js/jest.config.cjs b/plugins/tradingview-lightweight/src/js/jest.config.cjs
new file mode 100644
index 000000000..1766e62ef
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/jest.config.cjs
@@ -0,0 +1,28 @@
+const path = require('path');
+const baseConfig = require('../../../../jest.config.base.cjs');
+
+module.exports = {
+  ...baseConfig,
+  displayName: '@deephaven/js-plugin-tradingview-lightweight',
+  // The Playwright e2e specs under e2e/ are *.spec.ts (jest's default glob
+  // would otherwise collect them); they import @playwright/test and need a
+  // live server, so they belong to `npm run test:e2e`, not jest.
+  testPathIgnorePatterns: [...(baseConfig.testPathIgnorePatterns ?? []), '/e2e/'],
+  moduleNameMapper: {
+    ...baseConfig.moduleNameMapper,
+    '^lightweight-charts$': path.join(
+      __dirname,
+      'src/__mocks__/lightweight-charts.js'
+    ),
+    // Vite's `?inline` CSS import has no meaning under jest — stub to a string.
+    '\\.css\\?inline$': path.join(__dirname, 'src/__mocks__/styleMock.js'),
+  },
+  setupFilesAfterEach: [
+    ...(baseConfig.setupFilesAfterEach ?? []),
+    path.join(__dirname, 'jest.setup.ts'),
+  ],
+  setupFiles: [
+    ...(baseConfig.setupFiles ?? []),
+    path.join(__dirname, 'jest.setup.ts'),
+  ],
+};
diff --git a/plugins/tradingview-lightweight/src/js/jest.setup.ts b/plugins/tradingview-lightweight/src/js/jest.setup.ts
new file mode 100644
index 000000000..8e072efe7
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/jest.setup.ts
@@ -0,0 +1,17 @@
+/**
+ * jsdom doesn't implement the CSS.supports() global, but
+ * @deephaven/components' resolveCssVariablesInRecord calls it to detect
+ * whether a resolved value parses as a color. Stub it so color-resolution
+ * code paths can be exercised under jsdom (we don't need the answer to be
+ * correct in unit tests — the renderer just needs the call to succeed).
+ */
+if (typeof window !== 'undefined') {
+  const css = (window as unknown as { CSS?: typeof CSS }).CSS;
+  if (css == null || typeof css.supports !== 'function') {
+    Object.defineProperty(window, 'CSS', {
+      configurable: true,
+      writable: true,
+      value: { ...(css ?? {}), supports: () => true },
+    });
+  }
+}
diff --git a/plugins/tradingview-lightweight/src/js/package.json b/plugins/tradingview-lightweight/src/js/package.json
new file mode 100644
index 000000000..27238f159
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/package.json
@@ -0,0 +1,74 @@
+{
+  "name": "@deephaven/js-plugin-tradingview-lightweight",
+  "version": "0.1.0",
+  "description": "Deephaven TradingView Lightweight Charts plugin",
+  "keywords": [
+    "Deephaven",
+    "plugin",
+    "deephaven-js-plugin",
+    "tradingview",
+    "lightweight-charts"
+  ],
+  "author": "Deephaven Data Labs LLC",
+  "license": "Apache-2.0",
+  "main": "dist/bundle/index.js",
+  "type": "module",
+  "exports": {
+    ".": {
+      "import": "./dist/index.js",
+      "require": "./dist/bundle/index.js",
+      "default": "./dist/bundle/index.js"
+    },
+    "./*.js": "./dist/*.js",
+    "./*": "./dist/*.js"
+  },
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/deephaven/deephaven-plugins"
+  },
+  "bugs": {
+    "url": "https://github.com/deephaven/deephaven-plugins/issues"
+  },
+  "homepage": "https://github.com/deephaven/deephaven-plugins",
+  "scripts": {
+    "start": "vite build --watch",
+    "build": "run-s build:*",
+    "build:transpile": "tsc",
+    "build:bundle": "vite build",
+    "test:e2e": "run-s build test:e2e:run",
+    "test:e2e:run": "playwright test -c e2e/playwright.config.ts",
+    "test:e2e:setup": "bash e2e/setup-venv.sh",
+    "update-dh-packages": "node ../../../../tools/update-dh-packages.mjs"
+  },
+  "devDependencies": {
+    "@deephaven/dashboard-core-plugins": "^0.85.42",
+    "@deephaven/jsapi-types": "^1.0.0-dev0.39.5",
+    "@deephaven/test-utils": "0.105.0",
+    "@types/react": "^17.0.2",
+    "react": "^17.0.2",
+    "react-dom": "^17.0.2",
+    "typescript": "^5.9.3"
+  },
+  "peerDependencies": {
+    "react": "^17.0.2",
+    "react-dom": "^17.0.2"
+  },
+  "dependencies": {
+    "@deephaven/components": "^1.2.0",
+    "@deephaven/dashboard": "^1.2.0",
+    "@deephaven/icons": "^1.2.0",
+    "@deephaven/jsapi-bootstrap": "1.2.0",
+    "@deephaven/log": "1.1.0",
+    "@deephaven/plugin": "^1.2.0",
+    "@deephaven/redux": "^1.2.0",
+    "@deephaven/utils": "^1.1.0",
+    "lightweight-charts": "^5.2.0",
+    "react-redux": "^7.2.9"
+  },
+  "publishConfig": {
+    "access": "public"
+  },
+  "files": [
+    "dist"
+  ]
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewChart.css b/plugins/tradingview-lightweight/src/js/src/TradingViewChart.css
new file mode 100644
index 000000000..933196b3b
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewChart.css
@@ -0,0 +1,126 @@
+/* Ensure WidgetPanel's LoadingOverlay sits above the chart container */
+.dh-tvl-panel > .fill-parent-absolute {
+  z-index: 50;
+}
+
+/* ---- Tracking tooltip (cursor-following overlay) ---- */
+
+.tvl-tooltip {
+  position: absolute;
+  display: none;
+  box-sizing: border-box;
+  top: 12px;
+  left: 12px;
+  padding: 6px 8px;
+  font-size: 12px;
+  line-height: 1.3;
+  text-align: left;
+  white-space: nowrap;
+  pointer-events: none;
+  /* Above the downsample scrim (10) and status bar (30); below the
+     WidgetPanel LoadingOverlay (50) so disconnect/error overlays win. */
+  z-index: 40;
+  background: var(--dh-color-content-bg, #2d2a2e);
+  color: var(--dh-color-fg, #f0f0ee);
+  border: 1px solid var(--dh-color-gray-500, #555);
+  border-radius: 2px;
+}
+
+.tvl-tooltip-title {
+  font-weight: 600;
+  /* Color is set inline to the focused series' color; falls back to `fg`. */
+}
+
+.tvl-tooltip-value {
+  font-size: 16px;
+  margin: 2px 0;
+}
+
+.tvl-tooltip-date {
+  color: var(--dh-color-gray-700, #888);
+}
+
+/* ---- Pending downsample scrim ---- */
+
+.tvl-pending-scrim {
+  position: absolute;
+  top: 0;
+  left: 0;
+  right: 0;
+  height: 0;
+  background: linear-gradient(
+    to bottom,
+    color-mix(in srgb, var(--dh-color-grid-scrim, #000) 40%, transparent),
+    color-mix(in srgb, var(--dh-color-grid-scrim, #000) 40%, transparent) calc(100% - 25px),
+    transparent 100%
+  );
+  transition: height 150ms ease-out;
+  pointer-events: none;
+  z-index: 10;
+}
+
+.tvl-pending-scrim.show {
+  height: calc(100% + 25px);
+}
+
+/* ---- Pending status bar (bottom-left, matches iris-grid) ---- */
+
+.tvl-pending-status {
+  display: flex;
+  position: absolute;
+  bottom: 0;
+  left: 0;
+  z-index: 30;
+  min-width: min(320px, 100%);
+  pointer-events: none;
+  opacity: 0;
+  transition: opacity 150ms ease-in;
+}
+
+.tvl-pending-status.show {
+  opacity: 1;
+}
+
+.tvl-pending-status-bar {
+  position: relative;
+  padding: 5px;
+  background: var(--dh-color-content-bg, #2d2a2e);
+  color: var(--dh-color-gray-700, #888);
+  border-top: 1px solid var(--dh-color-gray-500, #555);
+  border-right: 1px solid var(--dh-color-gray-500, #555);
+  overflow: hidden;
+  word-wrap: break-word;
+  z-index: 2;
+  flex-grow: 1;
+  font-size: 12px;
+}
+
+.tvl-pending-status-bar::after {
+  content: '';
+  position: absolute;
+  bottom: 0;
+  left: 0;
+  width: 100%;
+  height: 2px;
+  z-index: -1;
+  background: var(--dh-color-accent-bg, #4c90f0);
+  transform-origin: 0% 50%;
+  opacity: 0;
+}
+
+.tvl-pending-status.show .tvl-pending-status-bar::after {
+  opacity: 1;
+  animation: 1.5s tvl-indeterminate infinite linear;
+}
+
+@keyframes tvl-indeterminate {
+  0% {
+    transform: translateX(-50%) scaleX(0.5);
+  }
+  50% {
+    transform: translateX(0) scaleX(0.5);
+  }
+  100% {
+    transform: translateX(100%) scaleX(0.2);
+  }
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewChart.tsx b/plugins/tradingview-lightweight/src/js/src/TradingViewChart.tsx
new file mode 100644
index 000000000..ba65dacab
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewChart.tsx
@@ -0,0 +1,1311 @@
+import React, { useCallback, useEffect, useRef, useState } from 'react';
+import { useSelector } from 'react-redux';
+import { useApi } from '@deephaven/jsapi-bootstrap';
+import { getTimeZone, type RootState } from '@deephaven/redux';
+import type { dh as DhType } from '@deephaven/jsapi-types';
+import type { WidgetComponentProps } from '@deephaven/plugin';
+import Log from '@deephaven/log';
+import type { MouseEventParams } from 'lightweight-charts';
+import TradingViewChartModel from './TradingViewChartModel';
+import TradingViewChartRenderer from './TradingViewChartRenderer';
+import { buildPressEventPayload } from './TradingViewEventPayload';
+import {
+  useDHChartTheme,
+  chartThemeToOptions,
+  getColorway,
+  getOhlcColors,
+} from './TradingViewTheme';
+import {
+  transformTableData,
+  deduplicateByTime,
+  buildMarkersFromTableData,
+  convertTime,
+  unconvertTime,
+} from './TradingViewUtils';
+import type {
+  TvlChartType,
+  TvlFigureData,
+  ModelEvent,
+} from './TradingViewTypes';
+// eslint-disable-next-line @typescript-eslint/ban-ts-comment
+// @ts-ignore Vite ?inline import returns CSS as string
+import tvlStyles from './TradingViewChart.css?inline';
+
+const log = Log.module('TradingViewChart');
+
+/**
+ * Recursively deep-merge two plain objects. Nested objects are merged
+ * so that e.g. crosshair.vertLine from theme and from user options combine.
+ * Arrays are replaced, not merged.
+ */
+function deepMerge(
+  base: Record<string, unknown>,
+  overrides: Record<string, unknown>
+): Record<string, unknown> {
+  const result: Record<string, unknown> = { ...base };
+  Object.entries(overrides).forEach(([key, val]) => {
+    if (
+      typeof val === 'object' &&
+      val !== null &&
+      !Array.isArray(val) &&
+      typeof result[key] === 'object' &&
+      result[key] !== null &&
+      !Array.isArray(result[key])
+    ) {
+      result[key] = deepMerge(
+        result[key] as Record<string, unknown>,
+        val as Record<string, unknown>
+      );
+    } else {
+      result[key] = val;
+    }
+  });
+  return result;
+}
+
+/** Props for TradingViewChart when used inside a panel wrapper. */
+export interface TradingViewChartProps
+  extends WidgetComponentProps<DhType.Widget> {
+  /** Called when loading state changes (for panel-level LoadingOverlay). */
+  onLoadingChange?: (loading: boolean) => void;
+  /** Called when an error occurs (for panel-level error display). */
+  onError?: (error: string | null) => void;
+}
+
+function TradingViewChart(props: TradingViewChartProps): JSX.Element | null {
+  const dh = useApi();
+  const { fetch, onLoadingChange, onError } = props;
+  // Source the timezone from the user's Deephaven setting so the chart
+  // re-renders when the user changes their timezone in Settings — matching
+  // the plotly-express plugin. NOTE: `@deephaven/redux` must be BUNDLED (it is
+  // intentionally absent from vite.config externals), not externalized — the
+  // DH client's plugin require shim does not provide it, so externalizing it
+  // breaks plugin loading. Falls back to the browser timezone when unset.
+  const settingsTimeZone = useSelector(getTimeZone<RootState>);
+  const timeZone =
+    settingsTimeZone != null && settingsTimeZone !== ''
+      ? settingsTimeZone
+      : Intl.DateTimeFormat().resolvedOptions().timeZone;
+  const chartTheme = useDHChartTheme();
+  const chartThemeRef = useRef(chartTheme);
+  chartThemeRef.current = chartTheme;
+  const containerRef = useRef<HTMLDivElement>(null);
+  // lightweight-charts mounts here, NOT on `containerRef`. This host is
+  // `position: absolute` (out of normal flow), so the chart's own element —
+  // which LWC keeps explicitly sized via `autoSize` — never contributes to
+  // the outer flex item's content-based min-height. Without it, the chart's
+  // pixel height pins the flex item open and it refuses to shrink when the
+  // panel/sibling shrinks (mirrors how plotly's inner containers and
+  // iris-grid's canvas are taken out of flow for the same reason).
+  const chartHostRef = useRef<HTMLDivElement>(null);
+  const rendererRef = useRef<TradingViewChartRenderer | null>(null);
+  const modelRef = useRef<TradingViewChartModel | null>(null);
+  const [error, setErrorState] = useState<string | null>(null);
+  const [debugInfo, setDebugInfoRaw] = useState<string>('loading...');
+  const [isLoading, setIsLoadingState] = useState(true);
+
+  const setIsLoading = useCallback(
+    (loading: boolean) => {
+      setIsLoadingState(loading);
+      onLoadingChange?.(loading);
+    },
+    [onLoadingChange]
+  );
+
+  const setError = useCallback(
+    (err: string | null) => {
+      setErrorState(err);
+      onError?.(err);
+    },
+    [onError]
+  );
+  const [pendingDs, setPendingDs] = useState(false);
+  const [showScrim, setShowScrim] = useState(false);
+  const [showStatus, setShowStatus] = useState(false);
+
+  // Progressive reveal: scrim after 200ms, status bar after 500ms
+  useEffect(() => {
+    if (!pendingDs) {
+      setShowScrim(false);
+      setShowStatus(false);
+      return undefined;
+    }
+    const scrimTimer = setTimeout(() => setShowScrim(true), 200);
+    const statusTimer = setTimeout(() => setShowStatus(true), 500);
+    return () => {
+      clearTimeout(scrimTimer);
+      clearTimeout(statusTimer);
+    };
+  }, [pendingDs]);
+
+  const userOptionsRef = useRef<Record<string, unknown>>({});
+  const chartTypeRef = useRef<TvlChartType>('standard');
+
+  // ---- Downsample interaction state ----
+
+  /**
+   * True while we are programmatically calling setData / setVisibleRange.
+   * Range-change events during this window are ignored.
+   */
+  const suppressRef = useRef(false);
+  const suppressTimerRef = useRef<ReturnType<typeof setTimeout> | null>(null);
+
+  /**
+   * The visible range to restore after new downsample data arrives.
+   * Set just before calling performDownsample (zoom/pan), read in
+   * handleDataUpdate. Null means "fitContent" (initial / reset).
+   */
+  const restoreRangeRef = useRef<{ from: number; to: number } | null>(null);
+
+  /**
+   * The downsample range we last requested [from, to] in TZ-shifted seconds.
+   * Null means full range. Used to compute scaffold density ratio.
+   */
+  const lastDsRangeRef = useRef<[number, number] | null>(null);
+
+  /** True while the user is actively dragging (pointer down on chart). */
+  const draggingRef = useRef(false);
+
+  /**
+   * False until the user expresses a viewport preference (zoom/pan).
+   * While false, every data update re-fits content so late-arriving tables
+   * (lazy agg_by snapshots, multi-table panels, ticks) keep extending the
+   * visible range. The dblclick reset clears it; user zoom/pan sets it.
+   */
+  const userInteractedRef = useRef(false);
+
+  /** Cleanup for downsample subscriptions. */
+  const dsCleanupRef = useRef<(() => void) | null>(null);
+
+  /** Unsubscribe fns for user event handlers (press / doublePress). */
+  const eventUnsubsRef = useRef<Array<() => void>>([]);
+
+  // ---- Debug helpers ----
+
+  function buildStateJson(
+    model: TradingViewChartModel | null,
+    renderer: TradingViewChartRenderer | null
+  ): string {
+    if (!model) return '{}';
+    let tableSize = 0;
+    let colDataRows = 0;
+    // Sample any resampled table for size/colDataRows; fall back to all tables
+    // if neither downsample nor auto-bin is active.
+    const sampleTableIds: number[] = [];
+    model.getDownsampledTableIds().forEach(tid => sampleTableIds.push(tid));
+    Object.keys(model.getAutoBinMeta()).forEach(refStr =>
+      sampleTableIds.push(Number(refStr))
+    );
+    sampleTableIds.forEach(tid => {
+      const t = model.getTable(tid);
+      if (t) tableSize = t.size;
+      const cd = model.getColumnData(tid);
+      if (cd) {
+        const first = cd.keys().next().value;
+        if (first != null) colDataRows = cd.get(first)?.length ?? 0;
+      }
+    });
+    let visRange: [number, number] | null = null;
+    if (renderer) {
+      try {
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        const vr = renderer.getChart().timeScale().getVisibleRange() as any;
+        if (vr != null) visRange = [vr.from as number, vr.to as number];
+      } catch {
+        // chart may not be ready
+      }
+    }
+    // Auto-bin summary: pick the smallest binWidthNs across all binned tables.
+    const autoBinMeta = model.getAutoBinMeta();
+    const autoBinKeys = Object.keys(autoBinMeta);
+    let binWidthNs: number | null = null;
+    let aggType: string | null = null;
+    let rangeNs: [number, number] | null = null;
+    if (autoBinKeys.length > 0) {
+      const widths = autoBinKeys.map(k => autoBinMeta[k].binWidthNs);
+      binWidthNs = Math.min(...widths);
+      // Pick the agg from the first series of the first auto-binned table.
+      const first = autoBinMeta[autoBinKeys[0]];
+      const firstSeriesId = Object.keys(first.series)[0];
+      if (firstSeriesId) {
+        aggType = first.series[firstSeriesId].agg;
+      }
+      // Body range from the first auto-binned table; null means full source.
+      rangeNs = model.getAutoBinBodyRange(Number(autoBinKeys[0]));
+    }
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const m = model as any;
+    const pendingDs =
+      (m.pendingDownsample as boolean) || (m.pendingAutoBin as boolean);
+    return JSON.stringify({
+      // Snapshot-relevant readiness signal: true once every known series
+      // has its first row of data. Polled by the image-snapshotter so it
+      // can take a stable screenshot without hard-coded waits — especially
+      // important for `by`-partitioned charts where series are pushed in
+      // asynchronously after the container box has already stabilized.
+      dataReady: model.isReady(),
+      seriesCount: model.getFigureData()?.series.length ?? 0,
+      jsDs: model.isDownsampled(),
+      tableSize,
+      colDataRows,
+      pendingDs,
+      visRange,
+      autoBin: model.isAutoBinned(),
+      binWidthNs,
+      aggType,
+      rangeNs,
+      resampleSeq: (m.resampleSeq as number) ?? 0,
+    });
+  }
+
+  function updateDebugState(
+    text: string | ((prev: string) => string),
+    model: TradingViewChartModel | null,
+    renderer: TradingViewChartRenderer | null
+  ): void {
+    setDebugInfoRaw(text);
+    if (containerRef.current) {
+      containerRef.current.setAttribute(
+        'data-tvl-state',
+        buildStateJson(model, renderer)
+      );
+      // Generic readiness signal for plugin-agnostic consumers (the docs
+      // image-snapshotter polls this). True once every known series has
+      // its first row of data AND nothing is mid-resample.
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      const m = model as any;
+      const pendingDs = model
+        ? ((m.pendingDownsample as boolean) ||
+          (m.pendingAutoBin as boolean))
+        : true;
+      const ready = !!model && model.isReady() && !pendingDs;
+      containerRef.current.setAttribute(
+        'data-snapshot-ready',
+        ready ? 'true' : 'false'
+      );
+    }
+  }
+
+  function gatherDebug(
+    label: string,
+    model: TradingViewChartModel | null,
+    renderer: TradingViewChartRenderer | null
+  ): string {
+    const lines: string[] = [`--- ${label} ---`];
+    if (!model) {
+      lines.push('model: null');
+      return lines.join('\n');
+    }
+    lines.push(`jsDs: ${model.isDownsampled()}`);
+    model.getDownsampledTableIds().forEach(tid => {
+      const t = model.getTable(tid);
+      lines.push(`table[${tid}]: size=${t?.size ?? '?'}`);
+    });
+    lines.push(`pendingDs: ${(model as any).pendingDownsample}`);
+    if (renderer) {
+      try {
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        const vr = renderer.getChart().timeScale().getVisibleRange() as any;
+        if (vr != null) {
+          const fromD = new Date((vr.from as number) * 1000)
+            .toISOString()
+            .slice(0, 10);
+          const toD = new Date((vr.to as number) * 1000)
+            .toISOString()
+            .slice(0, 10);
+          const dur = ((vr.to as number) - (vr.from as number)) / 86400;
+          lines.push(`visRange: ${fromD} → ${toD} (${dur.toFixed(0)}d)`);
+        }
+      } catch {
+        // chart may not be ready
+      }
+    }
+    return lines.join('\n');
+  }
+
+  // ---- Scaffold ----
+
+  /**
+   * Update the scaffold with the correct density.
+   *
+   * runChartDownsample with a range returns:
+   *   ~5 sparse HEAD rows | dense BODY rows | ~5 sparse TAIL rows
+   *
+   * The scaffold must cover the FULL extent (head-to-tail) at a density
+   * that matches the BODY region. This ensures the sparse head/tail
+   * points get placed at correct time-proportional positions.
+   *
+   * Density calculation:
+   *   bodyDensity ≈ width * 2 points per bodyDuration
+   *   scaffoldCount = bodyDensity * totalDuration
+   *                 = width * 2 * (totalDuration / bodyDuration)
+   *   capped at 30K
+   *
+   * For full range (no head/tail), just use width * 2.
+   */
+  function updateScaffold(
+    renderer: TradingViewChartRenderer,
+    model: TradingViewChartModel
+  ): void {
+    if (!renderer.isScaffoldEnabled()) return;
+
+    const figure = model.getFigureData();
+    if (!figure) return;
+
+    // Dense scaffold path: covers both downsample (line/area) and autobin
+    // (histogram). For autobin, the body+anchors agg only spans the
+    // visible window; the scaffold's bookends must reach the source's
+    // full extent so panning past the body lands on time-proportional
+    // empty space and clamps to fixLeftEdge/fixRightEdge against the
+    // anchor rows.
+    let dataMin = Infinity;
+    let dataMax = -Infinity;
+    figure.series.forEach(series => {
+      const colData = model.getColumnData(series.dataMapping.tableId);
+      if (!colData) return;
+      const timeCol = colData.get(series.dataMapping.columns.time);
+      if (!timeCol || timeCol.length === 0) return;
+      const first = timeCol[0] as number;
+      const last = timeCol[timeCol.length - 1] as number;
+      if (first < dataMin) dataMin = first;
+      if (last > dataMax) dataMax = last;
+    });
+
+    // Union with autobin source extents (in case the body window has
+    // contracted inside fullRangeNs since the last data update).
+    if (model.isAutoBinned()) {
+      const tz = model.getTimeZone();
+      const meta = model.getAutoBinMeta();
+      Object.values(meta).forEach(m => {
+        const startSec = convertTime(m.fullRangeNs[0], tz);
+        const endSec = convertTime(m.fullRangeNs[1], tz);
+        if (startSec < dataMin) dataMin = startSec;
+        if (endSec > dataMax) dataMax = endSec;
+      });
+    }
+
+    if (dataMin >= dataMax) return;
+
+    const totalDuration = dataMax - dataMin;
+    const width = renderer.getTimeScaleWidth();
+    const dsRange = lastDsRangeRef.current;
+
+    let count: number;
+    if (dsRange != null) {
+      // Zoomed: scale density so body region gets ~width*2 points,
+      // and the full extent (including head/tail) is proportionally dense
+      const bodyDuration = Math.max(1, dsRange[1] - dsRange[0]);
+      const ratio = totalDuration / bodyDuration;
+      count = Math.min(30000, Math.max(1000, Math.ceil(width * 2 * ratio)));
+    } else {
+      // Full range: no head/tail, just need body density
+      count = Math.min(30000, Math.max(1000, width * 2));
+    }
+
+    renderer.setScaffoldData(dataMin, dataMax, count);
+  }
+
+  // ---- Series data helpers ----
+
+  function renderAllSeriesData(
+    renderer: TradingViewChartRenderer,
+    model: TradingViewChartModel,
+    figure: TvlFigureData
+  ): void {
+    const ct = renderer.getChartType();
+    figure.series.forEach(series => {
+      const colData = model.getColumnData(series.dataMapping.tableId);
+      if (colData) {
+        const data = transformTableData(series, colData, ct);
+        const deduped = deduplicateByTime(data as Record<string, unknown>[]);
+        renderer.setSeriesData(series.id, deduped as never[]);
+        if (series.markerSpec) {
+          const markerColData = model.getColumnData(
+            series.markerSpec.tableId
+          );
+          if (markerColData) {
+            const tableMarkers = buildMarkersFromTableData(
+              series.markerSpec,
+              markerColData,
+              ct,
+              renderer.getTextColor()
+            );
+            renderer.setSeriesMarkers(series.id, tableMarkers);
+          }
+        } else if (series.markers) {
+          renderer.setSeriesMarkers(series.id, series.markers);
+        }
+        renderer.updateDynamicPriceLines(series.id, colData);
+      }
+    });
+  }
+
+  const replayAllData = useCallback(
+    (renderer: TradingViewChartRenderer, model: TradingViewChartModel) => {
+      const figure = model.getFigureData();
+      if (!figure) return;
+
+      // Scaffold is a hidden LineSeries that anchors the chart's time
+      // scale. Two roles depending on the resampling path:
+      //   - JS-downsample: dense (~width*2 whitespace points) so the line
+      //     lays out proportionally across head/body/tail densities.
+      //   - Server autobin: just two bookend whitespace points at
+      //     fullRangeNs[0]/[1], so the chart's time extent covers the
+      //     full source even when the histogram's viewport only loads a
+      //     window. Without bookends, panning past the viewport would
+      //     hit ``fixLeftEdge``/``fixRightEdge`` and the user couldn't
+      //     trigger the next viewport shift.
+      renderer.configureSeries(
+        figure.series,
+        getColorway(chartTheme),
+        getOhlcColors(chartTheme),
+        model.isResampling()
+      );
+      if (figure.paneStretchFactors) {
+        renderer.applyPaneStretchFactors(figure.paneStretchFactors);
+      }
+      renderAllSeriesData(renderer, model, figure);
+      if (model.isResampling()) {
+        updateScaffold(renderer, model);
+      }
+      renderer.fitContent();
+    },
+    [chartTheme]
+  );
+
+  // Initialize model and renderer once.
+  useEffect(() => {
+    let cancelled = false;
+
+    function handleFigureUpdate(
+      renderer: TradingViewChartRenderer,
+      model: TradingViewChartModel,
+      figure: TvlFigureData
+    ) {
+      renderer.configureSeries(
+        figure.series,
+        getColorway(chartThemeRef.current),
+        getOhlcColors(chartThemeRef.current),
+        model.isResampling()
+      );
+      if (figure.paneStretchFactors) {
+        renderer.applyPaneStretchFactors(figure.paneStretchFactors);
+      }
+      renderAllSeriesData(renderer, model, figure);
+      if (model.isResampling()) {
+        updateScaffold(renderer, model);
+      }
+      renderer.fitContent();
+    }
+
+    /**
+     * Handle DATA_UPDATED from the model.
+     *
+     * For downsampled tables after a zoom/pan/reset:
+     * 1. Suppress range-change events
+     * 2. Update scaffold (correct density for head/body/tail)
+     * 3. setData for all affected series
+     * 4. Restore the saved visible range (zoom/pan) or fitContent (reset/init)
+     * 5. Un-suppress after a delay
+     *
+     * For non-downsampled or ticking updates: normal incremental path.
+     */
+    function handleDataUpdate(
+      renderer: TradingViewChartRenderer,
+      model: TradingViewChartModel,
+      event: Extract<ModelEvent, { type: 'DATA_UPDATED' }>
+    ) {
+      const {
+        tableId,
+        isInitialLoad,
+        isResetView,
+        isDownsampleSwap,
+        addedCount,
+        removedCount,
+        modifiedCount,
+      } = event;
+      const figure = model.getFigureData();
+      if (!figure) return;
+
+      const colData = model.getColumnData(tableId);
+      if (!colData) return;
+
+      const ct = renderer.getChartType();
+      const chart = renderer.getChart();
+      let dragRange: { from: number; to: number } | null = null;
+      if (draggingRef.current) {
+        try {
+          // eslint-disable-next-line @typescript-eslint/no-explicit-any
+          const vr = chart.timeScale().getVisibleRange() as any;
+          if (vr != null) {
+            dragRange = {
+              from: vr.from as number,
+              to: vr.to as number,
+            };
+          }
+        } catch {
+          // chart may not be ready
+        }
+      }
+
+      // isDownsampleSwap = first data from a fresh runChartDownsample call.
+      // Only suppress range events for actual data swaps, NOT for ticks.
+      if (isDownsampleSwap) {
+        suppressRef.current = true;
+      }
+
+      // --- Update series data ---
+      figure.series.forEach(series => {
+        if (series.dataMapping.tableId !== tableId) return;
+
+        const isAppendOnly =
+          addedCount > 0 &&
+          removedCount === 0 &&
+          !isInitialLoad &&
+          modifiedCount === 0;
+
+        // Data swap or initial load: full setData (data shape changed).
+        // Ticks on downsampled tables: incremental (just appending new rows).
+        if (isDownsampleSwap || removedCount > 0 || isInitialLoad) {
+          const data = transformTableData(series, colData, ct);
+          const deduped = deduplicateByTime(data as Record<string, unknown>[]);
+          renderer.setSeriesData(series.id, deduped as never[]);
+        } else if (isAppendOnly) {
+          const timeColName = series.dataMapping.columns.time;
+          const timeCol = colData.get(timeColName);
+          const totalRows = timeCol?.length ?? 0;
+          const start = Math.max(0, totalRows - addedCount);
+          const data = transformTableData(series, colData, ct, start);
+          for (let i = 0; i < data.length; i += 1) {
+            renderer.updateSeriesPoint(series.id, data[i]);
+          }
+        } else if (modifiedCount > 0) {
+          const data = transformTableData(series, colData, ct);
+          const deduped = deduplicateByTime(data as Record<string, unknown>[]);
+          renderer.setSeriesData(series.id, deduped as never[]);
+        }
+
+        if (!series.markerSpec && series.markers) {
+          renderer.setSeriesMarkers(series.id, series.markers);
+        }
+        renderer.updateDynamicPriceLines(series.id, colData);
+      });
+
+      // Table-driven markers
+      figure.series.forEach(series => {
+        if (series.markerSpec?.tableId !== tableId) return;
+        const markerColData = model.getColumnData(tableId);
+        if (!markerColData) return;
+        const tableMarkers = buildMarkersFromTableData(
+          series.markerSpec,
+          markerColData,
+          ct,
+          renderer.getTextColor()
+        );
+        renderer.setSeriesMarkers(series.id, tableMarkers);
+      });
+
+      // --- Update scaffold on data swap ---
+      if (isDownsampleSwap) {
+        updateScaffold(renderer, model);
+      }
+
+      // --- Viewport control ---
+      if (
+        isResetView === true ||
+        isInitialLoad === true ||
+        (!userInteractedRef.current && !draggingRef.current)
+      ) {
+        // Reset, initial load, or pre-interaction tick / late-arriving table:
+        // keep the visible range glued to the full data extent. Once the user
+        // zooms or pans, userInteractedRef flips and we stop re-fitting.
+        restoreRangeRef.current = null;
+        renderer.fitContent();
+      } else if (isDownsampleSwap) {
+        // Zoom/pan data swap: restore the exact visible range the user had
+        const rangeToRestore = dragRange ?? restoreRangeRef.current;
+        try {
+          if (rangeToRestore != null) {
+            chart.timeScale().setVisibleRange({
+              from: rangeToRestore.from,
+              to: rangeToRestore.to,
+            } as never);
+          }
+        } catch {
+          // chart may not be ready
+        }
+      } else if (addedCount > 0 && !isInitialLoad && !draggingRef.current) {
+        // Ticking: snap-to-live if right edge is near latest data
+        try {
+          // eslint-disable-next-line @typescript-eslint/no-explicit-any
+          const vr = chart.timeScale().getVisibleRange() as any;
+          if (vr != null) {
+            const visFrom = vr.from as number;
+            const visTo = vr.to as number;
+            const visDur = visTo - visFrom;
+            const timeColName = figure.series[0]?.dataMapping.columns.time;
+            const timeArr = timeColName ? colData.get(timeColName) : undefined;
+            if (timeArr && timeArr.length > 0 && visDur > 0) {
+              const lastTime = timeArr[timeArr.length - 1] as number;
+              const gap = lastTime - visTo;
+              if (gap > 0 && gap < visDur * 0.01) {
+                chart.timeScale().setVisibleRange({
+                  from: visFrom + gap,
+                  to: lastTime,
+                } as never);
+              }
+            }
+          }
+        } catch {
+          // chart may not be ready
+        }
+      }
+
+      // --- Un-suppress after delay (only for data swaps) ---
+      // 600ms gives the chart time to settle after fitContent before we let
+      // range-change events trigger another resample. Auto-bin's RESET path
+      // is sensitive to this — a too-short window lets a buffered-full-range
+      // ZOOM race the RESET and re-aggregate at the previous (zoomed) width.
+      if (isDownsampleSwap) {
+        if (suppressTimerRef.current) clearTimeout(suppressTimerRef.current);
+        suppressTimerRef.current = setTimeout(() => {
+          suppressRef.current = false;
+        }, 600);
+      }
+    }
+
+    /**
+     * Create or reconnect the model. Reuses the existing renderer.
+     */
+    async function connectModel(
+      renderer: TradingViewChartRenderer
+    ): Promise<void> {
+      if (modelRef.current) {
+        dsCleanupRef.current?.();
+        dsCleanupRef.current = null;
+        eventUnsubsRef.current.forEach(unsub => unsub());
+        eventUnsubsRef.current = [];
+        modelRef.current.close();
+        modelRef.current = null;
+      }
+
+      const widget = await fetch();
+      const exported = widget.exportedObjects;
+      const dataString = widget.getDataAsString();
+      if (cancelled) return;
+
+      const model = new TradingViewChartModel(dh, widget);
+      modelRef.current = model;
+
+      const message = JSON.parse(dataString);
+      const userOptions = message.figure?.chartOptions ?? {};
+      userOptionsRef.current = userOptions;
+      const ct = message.figure?.chartType ?? 'standard';
+      chartTypeRef.current = ct;
+
+      // The renderer was constructed with the default chartType ('standard')
+      // before the figure message was available — switch it now so options /
+      // yieldCurve / custom_numeric charts get their numeric horzScale and
+      // tick formatters. No-op on reconnect when ct already matches.
+      renderer.setChartType(ct);
+
+      if (Object.keys(userOptions).length > 0) {
+        const themeOptions = chartThemeToOptions(chartThemeRef.current);
+        const mergedOptions = deepMerge(
+          themeOptions as Record<string, unknown>,
+          userOptions
+        );
+        renderer.applyOptions(mergedOptions);
+      }
+
+      model.subscribe((event: ModelEvent) => {
+        if (cancelled) return;
+
+        switch (event.type) {
+          case 'FIGURE_UPDATED':
+            handleFigureUpdate(renderer, model, event.figure);
+            updateDebugState(
+              gatherDebug('FIGURE_UPDATED', model, renderer),
+              model,
+              renderer
+            );
+            break;
+          case 'DATA_UPDATED':
+            if (event.isInitialLoad) setIsLoading(false);
+            if (!event.isInitialLoad) setPendingDs(false);
+            handleDataUpdate(renderer, model, event);
+            updateDebugState(
+              gatherDebug(
+                `DATA tid=${event.tableId} init=${event.isInitialLoad} reset=${event.isResetView} add=${event.addedCount}`,
+                model,
+                renderer
+              ),
+              model,
+              renderer
+            );
+            break;
+          case 'DOWNSAMPLE_PENDING':
+            if (event.pending) {
+              setPendingDs(true);
+            } else {
+              setPendingDs(false);
+            }
+            // Refresh data-tvl-state so consumers (Playwright) see the
+            // up-to-date pendingDs without waiting for a DATA_UPDATED.
+            if (containerRef.current) {
+              containerRef.current.setAttribute(
+                'data-tvl-state',
+                buildStateJson(model, renderer)
+              );
+            }
+            break;
+          case 'DISCONNECTED':
+            if (!event.connected) {
+              setError('Chart disconnected');
+            } else {
+              log.info('Table reconnected, re-initializing model');
+              setError(null);
+              setIsLoading(true);
+              connectModel(renderer).catch(e => {
+                log.error('Reconnection failed', e);
+                setIsLoading(false);
+                setError(`Reconnection failed: ${String(e)}`);
+              });
+            }
+            break;
+          case 'ERROR':
+            setIsLoading(false);
+            setError(event.message);
+            break;
+          default:
+            break;
+        }
+      });
+
+      model.setTimeZone(timeZone);
+      model.setChartType(ct);
+      model.setDebugFn(msg => {
+        updateDebugState(
+          prev => {
+            const lines = prev.split('\n');
+            lines.push(msg);
+            return lines.slice(-15).join('\n');
+          },
+          model,
+          renderer
+        );
+      });
+
+      // Initial downsample is full range (null) — no sparse ends
+      lastDsRangeRef.current = null;
+      restoreRangeRef.current = null;
+
+      await model.init(exported, dataString);
+      updateDebugState(
+        gatherDebug('INIT', model, renderer),
+        model,
+        renderer
+      );
+
+      if (!cancelled && model.isResampling()) {
+        setupDownsampleSubscriptions(renderer, model);
+      }
+
+      if (!cancelled) {
+        setupEventHandlers(renderer, model);
+      }
+
+      // Tracking tooltip (cursor-following overlay). Set up after series exist
+      // so the tooltip can read per-series colors. Cleanup is torn down with
+      // the other event subscriptions.
+      if (!cancelled && renderer.hasTooltip()) {
+        eventUnsubsRef.current.push(renderer.setupTooltip());
+      }
+    }
+
+    /**
+     * Wire user event handlers (press / doublePress) advertised by the figure.
+     * On fire, builds a JSON-safe payload, sends it to Python, and publishes
+     * it to the `data-tvl-last-event` DOM seam for Playwright assertions.
+     */
+    function setupEventHandlers(
+      renderer: TradingViewChartRenderer,
+      model: TradingViewChartModel
+    ) {
+      function onPress(
+        type: 'press' | 'doublePress',
+        params: MouseEventParams
+      ) {
+        const payload = buildPressEventPayload(
+          type,
+          params,
+          s => renderer.getSeriesIdForApi(s),
+          s => renderer.getSeriesTitleForApi(s),
+          model.getTimeZone()
+        );
+        model.sendEvent(type, payload);
+        // Test seam: always publish the built payload to the DOM.
+        containerRef.current?.setAttribute(
+          'data-tvl-last-event',
+          JSON.stringify(payload)
+        );
+      }
+
+      const enabled = model.getEnabledHandlers();
+      enabled.forEach(id => {
+        if (id === 'press') {
+          eventUnsubsRef.current.push(
+            renderer.subscribeClick(params => onPress('press', params))
+          );
+        } else if (id === 'doublePress') {
+          eventUnsubsRef.current.push(
+            renderer.subscribeDblClick(params => onPress('doublePress', params))
+          );
+        }
+      });
+
+      // Test-only inversion-oracle hook: lets Playwright compute the exact
+      // click pixel for a (series, time, price) so its independently-derived
+      // coordinate can be checked against LWC's native hit test. Tiny and
+      // inert; only meaningful when a test reads it. Torn down with the chart.
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any, no-underscore-dangle
+      (window as any).__tvlTestHook = {
+        timeToCoordinate: (t: number) => renderer.timeToCoordinate(t),
+        // Convert a real UTC-seconds time through the same convertTime the
+        // data pipeline uses (applies the session-tz shift), then to an x
+        // coordinate — so a test can address a known data point regardless
+        // of the session timezone.
+        timeToCoordinateUtc: (utcSec: number) =>
+          renderer.timeToCoordinate(convertTime(utcSec, model.getTimeZone())),
+        priceToCoordinate: (seriesId: string, p: number) =>
+          renderer.priceToCoordinate(seriesId, p),
+        getSeriesIds: () => renderer.getSeriesIds(),
+      };
+      eventUnsubsRef.current.push(() => {
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any, no-underscore-dangle
+        delete (window as any).__tvlTestHook;
+      });
+    }
+
+    async function init() {
+      if (!containerRef.current || !chartHostRef.current) return;
+
+      const themeOptions = chartThemeToOptions(chartThemeRef.current);
+      const ct = chartTypeRef.current;
+      const renderer = new TradingViewChartRenderer(
+        chartHostRef.current,
+        themeOptions as Record<string, unknown>,
+        ct
+      );
+      rendererRef.current = renderer;
+
+      try {
+        await connectModel(renderer);
+      } catch (e) {
+        if (!cancelled) {
+          log.error('Failed to initialize TradingView chart', e);
+          setIsLoading(false);
+          setError(String(e));
+        }
+      }
+    }
+
+    // ================================================================
+    // Zoom / Pan / Reset detection — rewritten from scratch
+    // ================================================================
+
+    function setupDownsampleSubscriptions(
+      renderer: TradingViewChartRenderer,
+      model: TradingViewChartModel
+    ) {
+      const chart = renderer.getChart();
+      const timeScale = chart.timeScale();
+      const container = containerRef.current;
+      if (!container) return;
+
+      let debounceTimer: ReturnType<typeof setTimeout> | null = null;
+      let settled = false;
+      // Wall-clock deadline — processRangeChange and the resize listener
+      // ignore events while ``Date.now() < dblClickGuardUntil``. Set in
+      // onDblClick to a value ~1.5s in the future, blocks post-fit reflow
+      // events from racing the in-flight RESET.
+      let dblClickGuardUntil = 0;
+
+      // Baseline: the range we last sent a downsample request for.
+      // Used to detect whether the user has zoomed/panned enough to
+      // warrant a new downsample. Starts null — captured after settle.
+      let baselineFrom: number | null = null;
+      let baselineTo: number | null = null;
+
+      // Let the chart settle for 1s after init (fitContent, resize, etc.)
+      // before we start listening to range changes.
+      setTimeout(() => {
+        settled = true;
+        try {
+          // eslint-disable-next-line @typescript-eslint/no-explicit-any
+          const vr = timeScale.getVisibleRange() as any;
+          if (vr != null) {
+            baselineFrom = vr.from as number;
+            baselineTo = vr.to as number;
+          }
+        } catch {
+          // chart may not be ready
+        }
+        // Initial RETRIEVE is server-initiated and has no chart width to
+        // base target_bins on, so it falls back to a constant default. Now
+        // that the chart has laid out, send one AUTOBIN_RESET with the real
+        // width so bars on small dashboard panels widen to the MIN_BAR_PX
+        // floor. userInteractedRef is still false here, so the resulting
+        // AUTOBIN_FIGURE response re-fits to full data extent automatically.
+        if (model.isAutoBinned()) {
+          const w = timeScale.width();
+          if (w > 0) {
+            model.performAutoBin(null, w);
+          }
+        }
+      }, 1000);
+
+      // --- Pointer tracking ---
+      // During a drag (pan), range changes fire continuously.
+      // We defer processing until pointerup to avoid firing many
+      // downsample requests mid-drag.
+      let needsProcessAfterDrag = false;
+      const onDown = () => {
+        draggingRef.current = true;
+      };
+      const onUp = () => {
+        draggingRef.current = false;
+        if (needsProcessAfterDrag) {
+          needsProcessAfterDrag = false;
+          processRangeChange();
+        }
+      };
+      container.addEventListener('pointerdown', onDown, true);
+      window.addEventListener('pointerup', onUp, true);
+      window.addEventListener('pointercancel', onUp, true);
+
+      /**
+       * Core logic: compare current visible range against baseline.
+       * If zoomed (>10% duration change) or panned (>20% center shift),
+       * request a new downsample with the visible range + 50% buffer.
+       */
+      function processRangeChange(): void {
+        if (suppressRef.current) return;
+        if (Date.now() < dblClickGuardUntil) return;
+
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        const vr = timeScale.getVisibleRange() as any;
+        if (vr == null) return;
+        const visFrom = vr.from as number;
+        const visTo = vr.to as number;
+        const visDur = visTo - visFrom;
+        if (visDur < 1) return;
+
+        // Capture baseline on first event
+        if (baselineFrom == null || baselineTo == null) {
+          baselineFrom = visFrom;
+          baselineTo = visTo;
+          return;
+        }
+
+        const baseDur = baselineTo - baselineFrom;
+        const durChange =
+          baseDur > 0
+            ? Math.abs(visDur - baseDur) / Math.max(visDur, baseDur)
+            : 1;
+        const centerShift =
+          visDur > 0
+            ? Math.abs(
+                (visFrom + visTo) / 2 - (baselineFrom + baselineTo) / 2
+              ) / visDur
+            : 0;
+
+        const isZoom = durChange > 0.1;
+        const isPanOnly = !isZoom && centerShift > 0.2;
+        if (isZoom || isPanOnly) {
+          // User-initiated zoom/pan: from now on the chart respects their
+          // viewport choice, so handleDataUpdate stops auto-fitting.
+          userInteractedRef.current = true;
+          // Update baseline to current visible range
+          baselineFrom = visFrom;
+          baselineTo = visTo;
+
+          // Buffer the visible window for the resample request. Tracks
+          // the 20% pan-detection threshold above so a fresh build's
+          // body covers the next pan-detection window without a
+          // round-trip.
+          const buf = visDur * 0.2;
+          const dsFrom = visFrom - buf;
+          const dsTo = visTo + buf;
+
+          // Save visible range to restore after data swap
+          restoreRangeRef.current = { from: visFrom, to: visTo };
+          lastDsRangeRef.current = [dsFrom, dsTo];
+
+          updateDebugState(
+            gatherDebug(isZoom ? 'ZOOM' : 'PAN', model, renderer),
+            model,
+            renderer
+          );
+
+          // Pan and zoom both rebuild server-side (for autobin) and
+          // re-downsample (for line/area). The autobin viewport-shift
+          // path is gone — the body always covers the visible window.
+          model.performResample([dsFrom, dsTo], timeScale.width());
+        }
+
+        // Refresh state attribute for tests
+        if (containerRef.current) {
+          containerRef.current.setAttribute(
+            'data-tvl-state',
+            buildStateJson(model, renderer)
+          );
+        }
+      }
+
+      // Subscribe to visible range changes (fires on zoom, pan, fitContent).
+      const unsubRange = renderer.subscribeVisibleLogicalRangeChange(() => {
+        if (!settled || suppressRef.current) return;
+        if (draggingRef.current) {
+          userInteractedRef.current = true;
+          needsProcessAfterDrag = true;
+          return;
+        }
+        // Debounce for wheel zoom (fires many events quickly)
+        if (debounceTimer) clearTimeout(debounceTimer);
+        debounceTimer = setTimeout(processRangeChange, 200);
+      });
+
+      // Disable LWC's native axis double-click reset (we handle it).
+      // Fix edges so panning can't scroll past data extent.
+      chart.applyOptions({
+        handleScale: { axisDoubleClickReset: { time: false, price: false } },
+        timeScale: { fixLeftEdge: true, fixRightEdge: true },
+      } as never);
+
+      // --- Double-click reset ---
+      // Full range downsample (null range) + fitContent + reset price scales.
+      // dblClickGuardUntil is consulted by processRangeChange and the resize
+      // listener so post-fit reflow events can't race the in-flight RESET
+      // back into a zoomed state.
+      const onDblClick = () => {
+        if (!settled) return;
+        // Dblclick is a "snap back to full" gesture — re-arm auto-fit so
+        // late ticks keep extending the visible range until the user zooms.
+        userInteractedRef.current = false;
+        baselineFrom = null;
+        baselineTo = null;
+        restoreRangeRef.current = null; // fitContent, not restore
+        lastDsRangeRef.current = null; // full range
+        renderer.resetPriceScales();
+        dblClickGuardUntil = Date.now() + 1500;
+        updateDebugState(
+          gatherDebug('DBLCLICK → RESET', model, renderer),
+          model,
+          renderer
+        );
+        model.performResample(null, timeScale.width());
+      };
+      container.addEventListener('dblclick', onDblClick);
+
+      // --- Resize ---
+      // Re-downsample at new width. Pre-interaction we resample at full
+      // range (so target_bins refines for the new pixel count); post-
+      // interaction we preserve the user's visible range and only refresh
+      // density.
+      let lastWidth = timeScale.width();
+      const unsubSize = renderer.subscribeSizeChange(() => {
+        if (!settled || suppressRef.current) return;
+        if (Date.now() < dblClickGuardUntil) return;
+        const newWidth = timeScale.width();
+        if (newWidth <= 0 || newWidth === lastWidth) return;
+        lastWidth = newWidth;
+
+        if (!userInteractedRef.current) {
+          restoreRangeRef.current = null;
+          lastDsRangeRef.current = null;
+          model.performResample(null, newWidth);
+          return;
+        }
+
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        const visRange = timeScale.getVisibleRange() as any;
+        const from = visRange?.from as number | undefined;
+        const to = visRange?.to as number | undefined;
+        if (from != null && to != null) {
+          restoreRangeRef.current = { from, to };
+          const buf = (to - from) * 0.2;
+          lastDsRangeRef.current = [from - buf, to + buf];
+          model.performResample([from - buf, to + buf], newWidth);
+        }
+      });
+
+      dsCleanupRef.current = () => {
+        unsubRange();
+        container.removeEventListener('dblclick', onDblClick);
+        unsubSize();
+        if (debounceTimer) clearTimeout(debounceTimer);
+        container.removeEventListener('pointerdown', onDown, true);
+        window.removeEventListener('pointerup', onUp, true);
+        window.removeEventListener('pointercancel', onUp, true);
+      };
+    }
+
+    init();
+
+    return () => {
+      cancelled = true;
+      if (suppressTimerRef.current) clearTimeout(suppressTimerRef.current);
+      dsCleanupRef.current?.();
+      dsCleanupRef.current = null;
+      eventUnsubsRef.current.forEach(unsub => unsub());
+      eventUnsubsRef.current = [];
+      modelRef.current?.close();
+      modelRef.current = null;
+      rendererRef.current?.dispose();
+      rendererRef.current = null;
+    };
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [dh, fetch]);
+
+  // Respond to client-side timezone changes without tearing down the
+  // model/renderer. The model re-subscribes its tables so time columns
+  // re-convert in the new timezone (see TradingViewChartModel.setTimeZone).
+  // If the user had zoomed/panned, re-anchor the viewport to the same
+  // wall-clock window by re-projecting the visible range through the old and
+  // new timezone shifts so the same data stays in view.
+  useEffect(() => {
+    const renderer = rendererRef.current;
+    const model = modelRef.current;
+    if (!renderer || !model) return;
+
+    const oldTimeZone = model.getTimeZone();
+    if (oldTimeZone === timeZone) return;
+
+    if (userInteractedRef.current) {
+      try {
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        const vr = renderer.getChart().timeScale().getVisibleRange() as any;
+        if (vr != null) {
+          const remap = (shifted: number): number =>
+            convertTime(unconvertTime(shifted, oldTimeZone), timeZone);
+          restoreRangeRef.current = {
+            from: remap(vr.from as number),
+            to: remap(vr.to as number),
+          };
+        }
+      } catch {
+        // chart may not be ready — fall back to fitContent on data swap
+      }
+    }
+
+    model.setTimeZone(timeZone);
+  }, [timeZone]);
+
+  // Apply theme changes without tearing down the model/renderer.
+  useEffect(() => {
+    const renderer = rendererRef.current;
+    const model = modelRef.current;
+    if (!renderer || !model) return;
+
+    const themeOptions = chartThemeToOptions(chartTheme);
+    const mergedOptions = deepMerge(
+      themeOptions as Record<string, unknown>,
+      userOptionsRef.current
+    );
+
+    renderer.applyOptions(mergedOptions);
+    replayAllData(renderer, model);
+  }, [chartTheme, replayAllData]);
+
+  // Handle container resize (CSS layout).
+  useEffect(() => {
+    const container = containerRef.current;
+    if (!container) return undefined;
+
+    const observer = new ResizeObserver(entries => {
+      entries.forEach(entry => {
+        const { width, height } = entry.contentRect;
+        if (width === 0 || height === 0) return;
+        rendererRef.current?.resize(width, height);
+        if (modelRef.current?.isResampling() !== true) {
+          rendererRef.current?.fitContent();
+        }
+      });
+    });
+
+    observer.observe(container);
+    return () => observer.disconnect();
+  }, []);
+
+  return (
+    <div
+      ref={containerRef}
+      // `chart-wrapper` is the class plotly-express's chart root uses, which
+      // deephaven.ui targets (e.g. styles.scss strips panel padding when a
+      // `.chart-wrapper` is a panel's only child). Carrying it lets the tvl
+      // chart get the same host-side treatment. `dh-tvl-chart` stays first —
+      // the plugin's own CSS and the e2e/unit selectors key on it.
+      className="dh-tvl-chart chart-wrapper"
+      data-snapshot-ready="false"
+      style={{
+        // Match the plotly-express chart root (`h-100 w-100`): a plain
+        // 100%-of-parent box with no flex-item overrides. lightweight-charts
+        // has no intrinsic size and paints exactly its container's measured
+        // box, so the earlier `flex-basis:0` + `min-height:0`/`min-width:0`
+        // let the element collapse to zero when used as a bare `ui.flex`
+        // child (plotly papers over this by self-sizing to a default height;
+        // lightweight-charts does not). Sizing like dx keeps it visible both
+        // inline and inside the standalone panel.
+        width: '100%',
+        height: '100%',
+        position: 'relative',
+        overflow: 'hidden',
+      }}
+    >
+      {/* eslint-disable-next-line react/no-danger */}
+      <style dangerouslySetInnerHTML={{ __html: tvlStyles }} />
+      {/* lightweight-charts mounts into this absolutely-positioned host so its
+          explicitly-sized element stays out of the outer flex item's flow —
+          see chartHostRef. */}
+      <div
+        ref={chartHostRef}
+        className="dh-tvl-chart-host"
+        style={{ position: 'absolute', inset: 0 }}
+      />
+      {pendingDs && (
+        <>
+          <div className={`tvl-pending-scrim${showScrim ? ' show' : ''}`} />
+          <div className={`tvl-pending-status${showStatus ? ' show' : ''}`}>
+            <div className="tvl-pending-status-bar">
+              Downsampling data&hellip;
+            </div>
+          </div>
+        </>
+      )}
+      <div
+        data-testid="tvl-debug"
+        style={{
+          position: 'absolute',
+          top: 4,
+          left: 4,
+          zIndex: 9999,
+          background: 'rgba(0,0,0,0.75)',
+          color: '#0f0',
+          fontFamily: 'monospace',
+          fontSize: 11,
+          padding: '4px 8px',
+          whiteSpace: 'pre',
+          pointerEvents: 'none',
+          maxWidth: '50%',
+          overflow: 'hidden',
+          display: 'none',
+        }}
+      >
+        {debugInfo}
+      </div>
+    </div>
+  );
+}
+
+export default TradingViewChart;
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewChartModel.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewChartModel.ts
new file mode 100644
index 000000000..830b32a53
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewChartModel.ts
@@ -0,0 +1,1413 @@
+import type { dh as DhType } from '@deephaven/jsapi-types';
+import Log from '@deephaven/log';
+import type {
+  AutoBinFigureMessage,
+  TvlAutoBinMeta,
+  TvlChartType,
+  TvlDownsampleMeta,
+  TvlFigureData,
+  TvlSeriesConfig,
+  ModelEvent,
+  ModelEventListener,
+  NewFigureMessage,
+} from './TradingViewTypes';
+import {
+  getAllColumnsForTable,
+  convertTime,
+  unconvertTime,
+} from './TradingViewUtils';
+
+const log = Log.module('TradingViewChartModel');
+
+const DOWNSAMPLE_THRESHOLD = 1000;
+
+/**
+ * Manages the data flow between Deephaven tables and the chart renderer.
+ * Uses table.subscribe() and ChartData for efficient delta-based updates,
+ * matching the pattern used by PlotlyExpressChartModel.
+ *
+ * Downsampling is performed entirely in JS via
+ * dh.plot.Downsample.runChartDownsample (same approach as plotly-express).
+ */
+class TradingViewChartModel {
+  private dh: typeof DhType;
+
+  private widget: DhType.Widget;
+
+  private listeners: Set<ModelEventListener> = new Set();
+
+  private figureData: TvlFigureData | null = null;
+
+  /** Tables currently subscribed to (may be original or downsampled). */
+  private tables: Map<number, DhType.Table> = new Map();
+
+  /**
+   * Active subscriptions, keyed by tableId. All paths (downsample,
+   * autobin, and direct) use a full table.subscribe() — autobin tables
+   * are server-side scoped to a body+anchors aggregation that's already
+   * small enough to subscribe to wholesale.
+   */
+  private tableSubscriptionMap: Map<number, DhType.TableSubscription> =
+    new Map();
+
+  /** ChartData objects that handle delta updates efficiently. */
+  private chartDataMap: Map<number, DhType.plot.ChartData> = new Map();
+
+  /** Full column data arrays, updated incrementally via ChartData. */
+  private tableDataMap: Map<number, Record<string, unknown[]>> = new Map();
+
+  /** Cleanup functions for event listeners. */
+  private subscriptionCleanupMap: Map<number, Set<() => void>> = new Map();
+
+  private widgetListenerCleanup: (() => void) | null = null;
+
+  private revision = 0;
+
+  /** Track whether initial data has loaded for fitContent. */
+  private initialLoadComplete = false;
+
+  /** Set to true when close() is called; prevents stale async callbacks. */
+  private closed = false;
+
+  /** Next table ID for dynamically added partition tables. */
+  private nextTableId = 0;
+
+  /** Per-template partition watcher state, keyed by template series id. */
+  private partitionWatchers: Map<
+    string,
+    {
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      partitionedTable: any;
+      cleanup: () => void;
+      seenKeys: Set<string>;
+    }
+  > = new Map();
+
+  /** IANA timezone string (e.g. "America/New_York") for time column conversion. */
+  private timeZone = '';
+
+  getTimeZone(): string {
+    return this.timeZone;
+  }
+
+  /** Chart type — determines whether time columns need TZ conversion. */
+  private chartType: TvlChartType = 'standard';
+
+  // ---- JS-side downsample state ----
+
+  /** Original (full) tables stored for re-downsampling on zoom/pan. */
+  private originalTableMap: Map<number, DhType.Table> = new Map();
+
+  /** Current live downsampled tables (replaced on each re-downsample). */
+  private downsampledTableMap: Map<number, DhType.Table> = new Map();
+
+  /** Table IDs that are JS-downsampled. */
+  private jsDownsampledTableIds: Set<number> = new Set();
+
+  /** Metadata from Python about which tables are eligible. */
+  private downsampleMeta: Record<string, TvlDownsampleMeta> = {};
+
+  /** True while waiting for a downsample operation to complete. */
+  pendingDownsample = false;
+
+  /** If a new zoom was requested while waiting, store it here. */
+  private pendingZoomParams: {
+    range: [number, number] | null;
+    width: number;
+  } | null = null;
+
+  // ---- Server-side auto-bin state ----
+
+  /** Tables that were auto-binned server-side. */
+  private autoBinnedTableIds: Set<number> = new Set();
+
+  /** Per-table auto-bin metadata from the server. */
+  private autoBinMeta: Record<string, TvlAutoBinMeta> = {};
+
+  /**
+   * Per-table currently-scoped body range in UTC nanoseconds, or null when
+   * the full source is in use. Updated when AUTOBIN_ZOOM/RESET is sent so
+   * tests and debug overlays can read the current scope.
+   */
+  private autoBinBodyRange: Record<string, [number, number] | null> = {};
+
+  /** True while waiting for an AUTOBIN_FIGURE response from the server. */
+  pendingAutoBin = false;
+
+  /**
+   * True if the in-flight auto-bin request was triggered by a RESET
+   * (double-click), not a zoom/pan. The server's AUTOBIN_FIGURE response
+   * doesn't distinguish, so the model carries the flag forward to plumb
+   * isResetView into the resulting DATA_UPDATED event.
+   */
+  private autoBinPendingIsReset = false;
+
+  /**
+   * Monotonic counter incremented every time a resample request is issued
+   * (downsample or auto-bin). Tests use this to assert race-condition
+   * invariants ("N rapid zooms produce exactly N seq increments").
+   */
+  resampleSeq = 0;
+
+  /** If a new auto-bin zoom was requested while pending, store it here. */
+  private pendingAutoBinParams: {
+    range: [number, number] | null;
+    width?: number;
+  } | null = null;
+
+  /** Tables that should trigger fitContent on next DATA_UPDATED. */
+  private resetPendingForTable: Set<number> = new Set();
+
+  /**
+   * Tables that have just been re-subscribed after a downsample and
+   * are awaiting their first DATA_UPDATED. Used to distinguish a
+   * bulk data swap from a normal tick update.
+   */
+  private freshDownsampleTables: Set<number> = new Set();
+
+  /** Debug callback for overlay. */
+  private debugFn: ((msg: string) => void) | null = null;
+
+  /**
+   * Set pendingDownsample and emit a DOWNSAMPLE_PENDING event
+   * so the view layer can show/hide the loading scrim.
+   */
+  private setPendingDownsample(pending: boolean): void {
+    if (this.pendingDownsample === pending) return;
+    this.pendingDownsample = pending;
+    this.emit({ type: 'DOWNSAMPLE_PENDING', pending });
+  }
+
+  /** Same UX signal as setPendingDownsample but for the auto-bin path. */
+  private setPendingAutoBin(pending: boolean): void {
+    if (this.pendingAutoBin === pending) return;
+    this.pendingAutoBin = pending;
+    this.emit({ type: 'DOWNSAMPLE_PENDING', pending });
+  }
+
+  /**
+   * Stable translator for value columns. ChartData caches per function
+   * identity, so this must be a fixed reference (not a new lambda per call).
+   */
+  private readonly valueTranslator = (val: unknown): unknown =>
+    this.unwrapValue(val);
+
+  /**
+   * Stable translator for time columns. Produces TZ-adjusted epoch seconds
+   * directly, so the view layer never needs to call convertTime.
+   */
+  private readonly timeTranslator = (val: unknown): unknown => {
+    const unwrapped = this.unwrapValue(val);
+    if (unwrapped == null || typeof unwrapped !== 'number') return 0;
+    // Numeric-scale charts (yieldCurve, options) use raw x values
+    if (this.chartType === 'yieldCurve' || this.chartType === 'options') {
+      return unwrapped;
+    }
+    // Standard charts: convert millis → TZ-adjusted epoch seconds
+    return convertTime(unwrapped, this.timeZone);
+  };
+
+  constructor(dh: typeof DhType, widget: DhType.Widget) {
+    this.dh = dh;
+    this.widget = widget;
+  }
+
+  subscribe(listener: ModelEventListener): () => void {
+    this.listeners.add(listener);
+    return () => this.listeners.delete(listener);
+  }
+
+  private emit(event: ModelEvent): void {
+    this.listeners.forEach(listener => {
+      try {
+        listener(event);
+      } catch (e) {
+        log.error('Error in model listener', e);
+      }
+    });
+  }
+
+  /**
+   * Set the timezone used for time column conversion.
+   *
+   * Called once before init with the user's Deephaven timezone setting, and
+   * again whenever that setting changes. Before init (no live subscriptions)
+   * the value is simply stored and picked up when tables are first
+   * subscribed. After init, every active table is re-subscribed so its time
+   * columns re-convert through timeTranslator in the new timezone — mirroring
+   * PlotlyExpressChartModel.fireTimeZoneUpdated, which re-subscribes tables
+   * on a timezone change rather than tearing the whole chart down.
+   */
+  setTimeZone(tz: string): void {
+    const next = tz ?? '';
+    if (next === this.timeZone) return;
+    this.timeZone = next;
+    if (this.tableSubscriptionMap.size === 0) return;
+    this.resubscribeForTimeZone();
+  }
+
+  /**
+   * Tear down and re-create every active table subscription so time columns
+   * are re-extracted through timeTranslator using the current timezone. Each
+   * table is flagged as a fresh data swap so the view replaces (rather than
+   * appends) its series data and can re-anchor the viewport. The currently
+   * subscribed table (original, downsampled, or auto-binned) is reused, so
+   * the existing downsample / auto-bin scope is preserved across the change.
+   */
+  private resubscribeForTimeZone(): void {
+    const tableIds = Array.from(this.tableSubscriptionMap.keys());
+    tableIds.forEach(tableId => {
+      const table = this.tables.get(tableId);
+      if (!table) return;
+      this.cleanupSubscriptions(tableId);
+      this.chartDataMap.delete(tableId);
+      this.tableDataMap.delete(tableId);
+      this.freshDownsampleTables.add(tableId);
+      this.subscribeTable(tableId, table);
+    });
+  }
+
+  /**
+   * Set the chart type (standard, yieldCurve, options). Determines whether
+   * time columns receive TZ conversion or are passed through as raw numbers.
+   */
+  setChartType(ct: TvlChartType): void {
+    this.chartType = ct;
+  }
+
+  /**
+   * Collect the set of column names that serve as time/x-axis columns
+   * for any series or marker spec on the given table.
+   */
+  private getTimeColumnsForTable(tableId: number): Set<string> {
+    const timeCols = new Set<string>();
+    this.figureData?.series.forEach(s => {
+      if (s.dataMapping.tableId === tableId) {
+        timeCols.add(s.dataMapping.columns.time);
+      }
+      if (s.markerSpec?.tableId === tableId && s.markerSpec.columns.time) {
+        timeCols.add(s.markerSpec.columns.time);
+      }
+    });
+    return timeCols;
+  }
+
+  /**
+   * Initialize the model with widget data from fetch().
+   */
+  async init(
+    exportedObjects: DhType.WidgetExportedObject[],
+    dataString: string
+  ): Promise<void> {
+    const message: NewFigureMessage = JSON.parse(dataString);
+
+    if (message.type !== 'NEW_FIGURE') {
+      log.error('Unexpected initial message type:', message.type);
+      return;
+    }
+
+    this.figureData = message.figure;
+    this.revision = message.revision;
+
+    // Read downsample metadata from Python
+    if (this.figureData.downsampleMeta) {
+      this.downsampleMeta = this.figureData.downsampleMeta;
+    }
+    // Read auto-bin metadata from Python
+    if (this.figureData.autoBinMeta) {
+      this.autoBinMeta = this.figureData.autoBinMeta;
+      Object.keys(this.autoBinMeta).forEach(refStr => {
+        this.autoBinnedTableIds.add(Number(refStr));
+      });
+    }
+
+    // Collect partition refs and source table refs used only by partition
+    // templates. A large `by=` chart should not subscribe/downsample the raw
+    // source table directly; it only needs per-key constituent tables.
+    const partitionRefIndices = new Set<number>();
+    const partitionTemplateTableIds = new Set<number>();
+    const directSeriesTableIds = new Set<number>();
+    this.figureData.series.forEach(s => {
+      if (s.partition?.refIndex != null) {
+        partitionRefIndices.add(s.partition.refIndex);
+      }
+      if (s.partition != null) {
+        partitionTemplateTableIds.add(s.dataMapping.tableId);
+      } else {
+        directSeriesTableIds.add(s.dataMapping.tableId);
+      }
+      if (s.markerSpec?.tableId != null) {
+        directSeriesTableIds.add(s.markerSpec.tableId);
+      }
+    });
+
+    // Fetch all referenced tables (skip PartitionedTable refs)
+    const tablePromises: Promise<void>[] = [];
+    message.new_references.forEach(refIdx => {
+      if (partitionRefIndices.has(refIdx)) return; // handled below
+      if (
+        partitionTemplateTableIds.has(refIdx) &&
+        !directSeriesTableIds.has(refIdx) &&
+        this.downsampleMeta[String(refIdx)] != null
+      ) {
+        return;
+      }
+      if (refIdx < exportedObjects.length) {
+        const exported = exportedObjects[refIdx];
+        tablePromises.push(
+          exported.fetch().then((table: unknown) => {
+            this.tables.set(refIdx, table as DhType.Table);
+          })
+        );
+      }
+    });
+    await Promise.all(tablePromises);
+
+    // Set nextTableId past the highest used ref index to avoid collisions
+    this.nextTableId =
+      message.new_references.length > 0
+        ? Math.max(...message.new_references) + 1
+        : 0;
+
+    // Determine which tables need JS-side downsampling
+    const downsamplePromises: Promise<void>[] = [];
+    this.tables.forEach((table, tableId) => {
+      const meta = this.downsampleMeta[String(tableId)];
+      if (meta) {
+        // Store original for re-downsample on zoom/pan
+        this.originalTableMap.set(tableId, table);
+        this.jsDownsampledTableIds.add(tableId);
+        // Initial full-range downsample
+        downsamplePromises.push(
+          this.downsampleTable(tableId).catch(err => {
+            log.warn(
+              'Initial downsample failed for table',
+              tableId,
+              err
+            );
+            // Fall back to subscribing to original table directly
+            this.jsDownsampledTableIds.delete(tableId);
+            this.originalTableMap.delete(tableId);
+            this.subscribeTable(tableId, table);
+          })
+        );
+      } else {
+        // Non-downsampled (including server-side autobin): subscribe directly.
+        // Autobin tables are scoped server-side to body + anchors so the
+        // full aggregation is small enough for a regular subscription.
+        this.subscribeTable(tableId, table);
+      }
+    });
+    await Promise.all(downsamplePromises);
+
+    // For each series that's a partition template, fetch its
+    // PartitionedTable and start watching for keys.
+    const partitionPromises: Promise<void>[] = [];
+    this.figureData.series.forEach(template => {
+      const ref = template.partition?.refIndex;
+      if (ref != null && ref < exportedObjects.length) {
+        partitionPromises.push(
+          this.setupPartitionWatcher(template, exportedObjects[ref])
+        );
+      }
+    });
+    await Promise.all(partitionPromises);
+
+    // Listen for widget config updates
+    this.widgetListenerCleanup = this.listenToWidget();
+
+    // Emit initial figure config
+    this.emit({
+      type: 'FIGURE_UPDATED',
+      figure: this.figureData,
+      tables: Array.from(this.tables.values()),
+    });
+  }
+
+  // ---- JS-side downsample API ----
+
+  /** Whether JS-side downsampling is active for any table. */
+  isDownsampled(): boolean {
+    return this.jsDownsampledTableIds.size > 0;
+  }
+
+  /** Whether server-side auto-bin is active for any table. */
+  isAutoBinned(): boolean {
+    return this.autoBinnedTableIds.size > 0;
+  }
+
+  /** Whether any resampling path is active (downsample or auto-bin). */
+  isResampling(): boolean {
+    return this.isDownsampled() || this.isAutoBinned();
+  }
+
+  /** Get the auto-bin metadata from Python. */
+  getAutoBinMeta(): Record<string, TvlAutoBinMeta> {
+    return this.autoBinMeta;
+  }
+
+  /**
+   * Currently-scoped body range (UTC ns) for the given auto-binned table,
+   * or null when at full source. Returns null when the table is unknown.
+   */
+  getAutoBinBodyRange(tableRef: number): [number, number] | null {
+    return this.autoBinBodyRange[String(tableRef)] ?? null;
+  }
+
+  /** Get the downsample metadata from Python. */
+  getDownsampleMeta(): Record<string, TvlDownsampleMeta> {
+    return this.downsampleMeta;
+  }
+
+  /** Set debug callback for overlay output. */
+  setDebugFn(fn: (msg: string) => void): void {
+    this.debugFn = fn;
+  }
+
+  private dbg(msg: string): void {
+    this.debugFn?.(msg);
+  }
+
+  /**
+   * Downsample a single table using dh.plot.Downsample.runChartDownsample.
+   * Closes old downsampled table, installs new one, subscribes.
+   *
+   * @param tableId The table ID to downsample
+   * @param range Optional [fromSec, toSec] in TZ-shifted epoch seconds. Null = full range.
+   * @param width Optional chart width in pixels for target output size.
+   * @param isReset True if this is a reset (double-click) — triggers fitContent on data arrival.
+   */
+  private async downsampleTable(
+    tableId: number,
+    range?: [number, number] | null,
+    width?: number,
+    isReset = false
+  ): Promise<void> {
+    const meta = this.downsampleMeta[String(tableId)];
+    if (!meta) return;
+
+    const originalTable = this.originalTableMap.get(tableId);
+    if (!originalTable) return;
+
+    // Convert TZ-shifted seconds to DateWrapper range
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    let dsRange: any[] | undefined;
+    if (range != null) {
+      const fromUtcSec = unconvertTime(range[0], this.timeZone);
+      const toUtcSec = unconvertTime(range[1], this.timeZone);
+      dsRange = [
+        this.dh.DateWrapper.ofJsDate(new Date(fromUtcSec * 1000)),
+        this.dh.DateWrapper.ofJsDate(new Date(toUtcSec * 1000)),
+      ];
+    }
+
+    const targetWidth = width ?? 1000;
+
+    this.dbg(
+      `downsampleTable tid=${tableId} range=${range ? `[${range[0]},${range[1]}]` : 'null'} w=${targetWidth} reset=${isReset}`
+    );
+
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const newTable = await (this.dh as any).plot.Downsample.runChartDownsample(
+      originalTable,
+      meta.timeCol,
+      meta.valueCols,
+      targetWidth,
+      dsRange
+    );
+
+    if (this.closed) {
+      try {
+        newTable.close();
+      } catch {
+        // ignore
+      }
+      return;
+    }
+
+    this.dbg(`downsampleTable tid=${tableId} result: ${newTable.size} rows`);
+
+    // Tear down old subscription FIRST — this prevents the old
+    // subscription from firing ticks that consume the reset flag.
+    this.cleanupSubscriptions(tableId);
+    this.chartDataMap.delete(tableId);
+    this.tableDataMap.delete(tableId);
+
+    // Close old downsampled table (not the original!)
+    const oldDs = this.downsampledTableMap.get(tableId);
+    if (oldDs) {
+      try {
+        oldDs.close();
+      } catch {
+        // May already be closed
+      }
+    }
+
+    // Install new downsampled table
+    this.downsampledTableMap.set(tableId, newTable);
+    this.tables.set(tableId, newTable);
+
+    // Set flags AFTER cleanup, BEFORE subscribe — race-free.
+    // The old subscription is gone, so it can't consume these.
+    this.freshDownsampleTables.add(tableId);
+    if (isReset) {
+      this.resetPendingForTable.add(tableId);
+    }
+
+    // Subscribe — first EVENT_UPDATED will see the flags above
+    this.subscribeTable(tableId, newTable);
+  }
+
+  /**
+   * Perform a downsample operation for all JS-downsampled tables.
+   * Called by the view on zoom/pan/reset.
+   *
+   * @param range [fromSec, toSec] in TZ-shifted epoch seconds, or null for full range (reset).
+   * @param width Chart width in pixels.
+   */
+  async performDownsample(
+    range: [number, number] | null,
+    width: number
+  ): Promise<void> {
+    if (!this.isDownsampled()) return;
+
+    // Queue if already pending
+    if (this.pendingDownsample) {
+      this.pendingZoomParams = { range, width };
+      return;
+    }
+
+    this.setPendingDownsample(true);
+    this.resampleSeq += 1;
+
+    const isReset = range == null;
+
+    try {
+      const promises: Promise<void>[] = [];
+      this.jsDownsampledTableIds.forEach(tableId => {
+        promises.push(
+          this.downsampleTable(tableId, range, width, isReset).catch(err => {
+            log.warn('Re-downsample failed for table', tableId, err);
+            // On failure, fall back to original table
+            const orig = this.originalTableMap.get(tableId);
+            if (orig) {
+              this.cleanupSubscriptions(tableId);
+              this.chartDataMap.delete(tableId);
+              this.tableDataMap.delete(tableId);
+              this.tables.set(tableId, orig);
+              this.subscribeTable(tableId, orig);
+            }
+          })
+        );
+      });
+      await Promise.all(promises);
+    } finally {
+      this.setPendingDownsample(false);
+    }
+
+    // Drain pending queue
+    if (this.pendingZoomParams != null) {
+      const p = this.pendingZoomParams;
+      this.pendingZoomParams = null;
+      this.performDownsample(p.range, p.width);
+    }
+  }
+
+  // ---- Server-side auto-bin API ----
+
+  /**
+   * Request a re-aggregation for the visible range. Sends AUTOBIN_ZOOM
+   * (or AUTOBIN_RESET if range is null) to the server. The server
+   * responds asynchronously with AUTOBIN_FIGURE which is handled in
+   * listenToWidget.
+   */
+  performAutoBin(range: [number, number] | null, width?: number): void {
+    if (!this.isAutoBinned()) return;
+
+    if (this.pendingAutoBin) {
+      this.pendingAutoBinParams = { range, width };
+      return;
+    }
+
+    this.setPendingAutoBin(true);
+    this.resampleSeq += 1;
+    this.autoBinPendingIsReset = range == null;
+
+    // Round chart width up to the nearest 1000 px so the server's derived
+    // bin width lands on a small set of common values across sessions —
+    // makes the engine's `upperBin(time, w)` results cache-friendly. The
+    // raw width is sent alongside as `actualWidthPx` so the server can
+    // floor `target_bins` to keep each bar at least MIN_BAR_PX wide,
+    // regardless of how much the rounding overshoots.
+    const actualWidthPx =
+      width != null && width > 0 ? Math.round(width) : undefined;
+    const widthPx =
+      actualWidthPx != null
+        ? Math.max(1000, Math.ceil(actualWidthPx / 1000) * 1000)
+        : undefined;
+
+    this.autoBinnedTableIds.forEach(tableRef => {
+      if (range == null) {
+        this.autoBinBodyRange[String(tableRef)] = null;
+        this.sendWidgetMessage({
+          type: 'AUTOBIN_RESET',
+          tableRef,
+          widthPx,
+          actualWidthPx,
+        });
+        return;
+      }
+      // Range comes in as TZ-shifted epoch seconds (matching the chart's
+      // visible range). Convert to UTC nanoseconds for the server.
+      const fromUtcSec = unconvertTime(range[0], this.timeZone);
+      const toUtcSec = unconvertTime(range[1], this.timeZone);
+      const fromNs = Math.floor(fromUtcSec * 1e9);
+      const toNs = Math.floor(toUtcSec * 1e9);
+      // atLiveEdge: visible range's right edge is at or past the source's
+      // full extent. Server then extends the body's right bound past the
+      // tail anchor so live ticks land in the body's last bin.
+      const meta = this.autoBinMeta[String(tableRef)];
+      const atLiveEdge = meta != null && toNs >= meta.fullRangeNs[1];
+      this.autoBinBodyRange[String(tableRef)] = [fromNs, toNs];
+      this.sendWidgetMessage({
+        type: 'AUTOBIN_ZOOM',
+        tableRef,
+        fromNs,
+        toNs,
+        widthPx,
+        actualWidthPx,
+        atLiveEdge,
+      });
+    });
+  }
+
+  /** Unified resample router: dispatches to downsample and auto-bin paths. */
+  performResample(range: [number, number] | null, width: number): void {
+    if (this.isDownsampled()) {
+      this.performDownsample(range, width).catch(err => {
+        log.warn('performDownsample failed', err);
+      });
+    }
+    if (this.isAutoBinned()) {
+      this.performAutoBin(range, width);
+    }
+  }
+
+  /**
+   * Send a user event (press / doublePress) back to Python via the widget
+   * channel. Fire-and-forget; the server produces no client response.
+   */
+  sendEvent(handler: string, payload: unknown): void {
+    this.sendWidgetMessage({ type: 'EVENT', handler, payload });
+  }
+
+  /** Handler ids advertised by the figure (subset of press / doublePress). */
+  getEnabledHandlers(): string[] {
+    return this.figureData?.enabledHandlers ?? [];
+  }
+
+  private sendWidgetMessage(msg: Record<string, unknown>): void {
+    try {
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      (this.widget as any).sendMessage(JSON.stringify(msg), []);
+    } catch (e) {
+      log.error('Failed to send widget message', msg.type, e);
+      this.setPendingAutoBin(false);
+    }
+  }
+
+  /** Handle an AUTOBIN_FIGURE message from the server. */
+  private async handleAutoBinFigure(
+    msg: AutoBinFigureMessage,
+    exportedObjects: DhType.WidgetExportedObject[]
+  ): Promise<void> {
+    try {
+      // Update meta first so the renderer reflects the new bin width.
+      this.autoBinMeta = msg.autoBinMeta;
+      if (this.figureData) {
+        this.figureData.autoBinMeta = msg.autoBinMeta;
+      }
+      this.revision = msg.revision;
+
+      if (msg.noop === true || msg.new_references.length === 0) {
+        this.setPendingAutoBin(false);
+        this.drainPendingAutoBin();
+        return;
+      }
+
+      // Fetch the swapped-in aggregated table for the affected ref.
+      const { tableRef } = msg;
+      if (tableRef >= exportedObjects.length) {
+        log.warn(
+          'AUTOBIN_FIGURE tableRef out of range',
+          tableRef,
+          exportedObjects.length
+        );
+        this.setPendingAutoBin(false);
+        this.drainPendingAutoBin();
+        return;
+      }
+
+      const newTable = (await exportedObjects[
+        tableRef
+      ].fetch()) as DhType.Table;
+      if (this.closed) {
+        try {
+          newTable.close();
+        } catch {
+          // ignore
+        }
+        return;
+      }
+
+      // Tear down old subscription before swapping.
+      this.cleanupSubscriptions(tableRef);
+      this.chartDataMap.delete(tableRef);
+      this.tableDataMap.delete(tableRef);
+
+      const oldTable = this.tables.get(tableRef);
+      if (oldTable && oldTable !== newTable) {
+        try {
+          oldTable.close();
+        } catch {
+          // ignore
+        }
+      }
+
+      this.tables.set(tableRef, newTable);
+      this.freshDownsampleTables.add(tableRef);
+      if (this.autoBinPendingIsReset) {
+        this.resetPendingForTable.add(tableRef);
+      }
+      // Server-side scoped: subscribe to the entire (small) agg table.
+      this.subscribeTable(tableRef, newTable);
+    } catch (err) {
+      log.error('Error handling AUTOBIN_FIGURE', err);
+    } finally {
+      this.setPendingAutoBin(false);
+      this.drainPendingAutoBin();
+    }
+  }
+
+  private drainPendingAutoBin(): void {
+    if (this.pendingAutoBinParams != null) {
+      const p = this.pendingAutoBinParams;
+      this.pendingAutoBinParams = null;
+      this.performAutoBin(p.range, p.width);
+    }
+  }
+
+  // ---- Partition handling ----
+
+  /**
+   * Add a single partition key for a given template series: fetch its
+   * constituent table, subscribe, clone the template into a runtime
+   * series, and push it to the figure.
+   */
+  private async addPartitionKey(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    pt: any,
+    key: unknown,
+    template: TvlSeriesConfig
+  ): Promise<void> {
+    const watcher = this.partitionWatchers.get(template.id);
+    if (!watcher) return;
+    const keyStr = String(key);
+    if (watcher.seenKeys.has(keyStr)) {
+      return; // Duplicate key — already added
+    }
+    watcher.seenKeys.add(keyStr);
+
+    const table = await pt.getTable(key);
+    if (!table) {
+      log.warn('getTable returned null for key:', key);
+      watcher.seenKeys.delete(keyStr);
+      return;
+    }
+
+    const newTableId = this.nextTableId;
+    this.nextTableId += 1;
+    this.tables.set(newTableId, table as DhType.Table);
+
+    // Clone the template into a runtime series. Preserve options,
+    // type, paneIndex, priceScaleOptions, columns; give it a unique id
+    // and a per-key title.
+    const newSeries: TvlSeriesConfig = {
+      id: `${template.id}_${keyStr}`,
+      type: template.type,
+      options: { ...(template.options ?? {}), title: keyStr },
+      dataMapping: {
+        tableId: newTableId,
+        columns: { ...template.dataMapping.columns },
+      },
+      paneIndex: template.paneIndex,
+      priceScaleOptions: template.priceScaleOptions,
+    };
+
+    // Push the series config BEFORE subscribing so that
+    // getAllColumnsForTable() can find the column names for this tableId.
+    if (this.figureData) {
+      this.figureData.series.push(newSeries);
+      log.debug(
+        'Added series for key:',
+        keyStr,
+        'template:',
+        template.id,
+        'total:',
+        this.figureData.series.length
+      );
+    }
+
+    if (this.shouldDownsamplePartitionTable(template, table as DhType.Table)) {
+      this.addPartitionDownsampleMeta(
+        newTableId,
+        template,
+        table as DhType.Table
+      );
+      try {
+        await this.downsampleTable(newTableId);
+      } catch (err) {
+        log.warn(
+          'Initial partition downsample failed for table',
+          newTableId,
+          err
+        );
+        this.removePartitionDownsampleMeta(newTableId);
+        this.tables.set(newTableId, table as DhType.Table);
+        this.subscribeTable(newTableId, table as DhType.Table);
+      }
+    } else {
+      this.subscribeTable(newTableId, table as DhType.Table);
+    }
+  }
+
+  private shouldDownsamplePartitionTable(
+    template: TvlSeriesConfig,
+    table: DhType.Table
+  ): boolean {
+    if (this.downsampleMeta[String(template.dataMapping.tableId)] == null) {
+      return false;
+    }
+    const size =
+      typeof table.size === 'number'
+        ? table.size
+        : this.downsampleMeta[String(template.dataMapping.tableId)].tableSize;
+    return size > DOWNSAMPLE_THRESHOLD;
+  }
+
+  private addPartitionDownsampleMeta(
+    tableId: number,
+    template: TvlSeriesConfig,
+    table: DhType.Table
+  ): void {
+    const sourceMeta =
+      this.downsampleMeta[String(template.dataMapping.tableId)];
+    if (sourceMeta == null) return;
+    const meta = {
+      ...sourceMeta,
+      tableSize:
+        typeof table.size === 'number' ? table.size : sourceMeta.tableSize,
+    };
+    this.downsampleMeta[String(tableId)] = meta;
+    if (this.figureData != null) {
+      this.figureData.downsampleMeta = {
+        ...(this.figureData.downsampleMeta ?? {}),
+        [String(tableId)]: meta,
+      };
+    }
+    this.originalTableMap.set(tableId, table);
+    this.jsDownsampledTableIds.add(tableId);
+  }
+
+  private removePartitionDownsampleMeta(tableId: number): void {
+    this.jsDownsampledTableIds.delete(tableId);
+    this.originalTableMap.delete(tableId);
+    delete this.downsampleMeta[String(tableId)];
+    if (this.figureData?.downsampleMeta) {
+      delete this.figureData.downsampleMeta[String(tableId)];
+    }
+  }
+
+  /**
+   * Fetch the PartitionedTable for a template series, discover all
+   * existing keys, subscribe to each, and listen for new keys.
+   *
+   * Per the DH JSAPI contract, the keyadded listener must be attached
+   * BEFORE :meth:`getKeys` is read so no keys are missed between snapshot
+   * and listener-attach. The per-template seenKeys dedup handles the
+   * overlap between the listener firing and the initial getKeys() sweep.
+   */
+  private async setupPartitionWatcher(
+    template: TvlSeriesConfig,
+    exported: DhType.WidgetExportedObject
+  ): Promise<void> {
+    try {
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      const pt = (await exported.fetch()) as any;
+
+      // Resolve the keyadded event name from the DH namespace; fall back to
+      // the literal string if the constant isn't surfaced.
+      let eventName = 'keyadded';
+      try {
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        const dhPT = (this.dh as any).PartitionedTable;
+        if (dhPT?.EVENT_KEYADDED) {
+          eventName = dhPT.EVENT_KEYADDED;
+        }
+      } catch {
+        // PartitionedTable not on dh namespace, use string fallback
+      }
+
+      // Pre-register the watcher entry so addPartitionKey can dedup.
+      this.partitionWatchers.set(template.id, {
+        partitionedTable: pt,
+        cleanup: () => {},
+        seenKeys: new Set<string>(),
+      });
+
+      // Attach the listener FIRST so any keys delivered between fetch() and
+      // our getKeys() sweep are still picked up.
+      const cleanup = pt.addEventListener(
+        eventName,
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        async (event: any) => {
+          try {
+            await this.addPartitionKey(pt, event.detail, template);
+            if (this.figureData) {
+              this.emit({
+                type: 'FIGURE_UPDATED',
+                figure: this.figureData,
+                tables: Array.from(this.tables.values()),
+              });
+            }
+          } catch (err) {
+            log.error('Error handling new partition key', err);
+          }
+        }
+      );
+      const entry = this.partitionWatchers.get(template.id);
+      if (entry) entry.cleanup = cleanup;
+
+      // Discover existing keys.
+      const rawKeys: unknown = pt.getKeys();
+      const existingKeys =
+        rawKeys != null && typeof (rawKeys as Promise<unknown>).then === 'function'
+          ? ((await rawKeys) as Set<unknown> | null | undefined)
+          : (rawKeys as Set<unknown> | null | undefined);
+      const initialCount = existingKeys?.size ?? 0;
+      log.debug(
+        'Existing partition keys for template',
+        template.id,
+        ':',
+        initialCount
+      );
+      if (existingKeys && initialCount > 0) {
+        const keyPromises: Promise<void>[] = [];
+        existingKeys.forEach((key: unknown) => {
+          keyPromises.push(this.addPartitionKey(pt, key, template));
+        });
+        await Promise.all(keyPromises);
+        if (this.figureData) {
+          this.emit({
+            type: 'FIGURE_UPDATED',
+            figure: this.figureData,
+            tables: Array.from(this.tables.values()),
+          });
+        }
+      }
+
+      log.debug(
+        'Partition watcher set up for',
+        template.id,
+        'with',
+        initialCount,
+        'initial keys'
+      );
+    } catch (err) {
+      log.error(
+        'Failed to set up partition watcher for template',
+        template.id,
+        err
+      );
+      this.emit({
+        type: 'ERROR',
+        message: `Partition watcher failed: ${String(err)}`,
+      });
+    }
+  }
+
+  // ---- Subscription ----
+
+  /**
+   * Clean up subscriptions and event listeners for a specific table.
+   */
+  private cleanupSubscriptions(tableId: number): void {
+    const cleanupSet = this.subscriptionCleanupMap.get(tableId);
+    if (cleanupSet) {
+      cleanupSet.forEach(cleanup => cleanup());
+      this.subscriptionCleanupMap.delete(tableId);
+    }
+    const sub = this.tableSubscriptionMap.get(tableId);
+    if (sub) {
+      sub.close();
+      this.tableSubscriptionMap.delete(tableId);
+    }
+  }
+
+  /**
+   * Subscribe to a table using full table.subscribe() with ChartData
+   * for delta updates. All tables (both original and downsampled) use
+   * this path — downsampled tables are small enough for full subscribe.
+   */
+  private subscribeTable(tableId: number, table: DhType.Table): void {
+    if (!this.figureData) return;
+
+    const columnNames = getAllColumnsForTable(this.figureData.series, tableId);
+    const columns = table.columns.filter((col: DhType.Column) =>
+      columnNames.includes(col.name)
+    );
+    if (columns.length === 0) return;
+
+    if (!this.subscriptionCleanupMap.has(tableId)) {
+      this.subscriptionCleanupMap.set(tableId, new Set());
+    }
+    // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
+    const cleanupSet = this.subscriptionCleanupMap.get(tableId)!;
+
+    // Full subscription with ChartData for delta updates
+    if (this.tableSubscriptionMap.has(tableId)) return;
+
+    this.chartDataMap.set(tableId, new this.dh.plot.ChartData(table));
+    this.tableDataMap.set(tableId, {});
+
+    const subscription = table.subscribe(columns);
+    this.tableSubscriptionMap.set(tableId, subscription);
+
+    cleanupSet.add(
+      // prettier-ignore
+      subscription.addEventListener(
+        this.dh.Table.EVENT_UPDATED,
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        ((e: any) => {
+          this.handleTableUpdate(
+            e as DhType.Event<DhType.SubscriptionTableData>,
+            tableId
+          );
+        }) as unknown as Parameters<typeof subscription.addEventListener>[1]
+      )
+    );
+
+    // Listen for table disconnect / reconnect
+    cleanupSet.add(
+      table.addEventListener(
+        this.dh.Table.EVENT_DISCONNECT,
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        (() => {
+          log.warn('Table disconnected:', tableId);
+          this.emit({ type: 'DISCONNECTED', connected: false });
+        }) as unknown as Parameters<typeof table.addEventListener>[1]
+      )
+    );
+    cleanupSet.add(
+      table.addEventListener(
+        this.dh.Table.EVENT_RECONNECT,
+        // eslint-disable-next-line @typescript-eslint/no-explicit-any
+        (() => {
+          log.info('Table reconnected:', tableId);
+          this.emit({ type: 'DISCONNECTED', connected: true });
+        }) as unknown as Parameters<typeof table.addEventListener>[1]
+      )
+    );
+  }
+
+  // ---- Data update handler ----
+
+  /**
+   * Handle subscription update for a table.
+   * Uses ChartData for delta processing; emits incremental info.
+   */
+  private handleTableUpdate(
+    event: DhType.Event<DhType.SubscriptionTableData>,
+    tableId: number
+  ): void {
+    const chartData = this.chartDataMap.get(tableId);
+    const tableData = this.tableDataMap.get(tableId);
+
+    if (chartData == null || tableData == null) {
+      log.warn('No chartData/tableData for table', tableId);
+      return;
+    }
+
+    const { detail: updateEvent } = event;
+
+    // Apply delta to ChartData
+    chartData.update(updateEvent);
+
+    // Extract full column arrays via translators (stable refs for caching)
+    const timeCols = this.getTimeColumnsForTable(tableId);
+    updateEvent.columns.forEach((column: DhType.Column) => {
+      const translator = timeCols.has(column.name)
+        ? this.timeTranslator
+        : this.valueTranslator;
+      tableData[column.name] = chartData.getColumn(
+        column.name,
+        translator,
+        updateEvent
+      );
+    });
+
+    const isFirstLoad = !this.initialLoadComplete;
+    if (isFirstLoad) {
+      this.initialLoadComplete = true;
+    }
+
+    // Check if this is the first data from a fresh downsample
+    const isDownsampleSwap = this.freshDownsampleTables.has(tableId);
+    if (isDownsampleSwap) {
+      this.freshDownsampleTables.delete(tableId);
+    }
+
+    // Check if this table has a pending reset (from double-click)
+    const isResetView = this.resetPendingForTable.has(tableId);
+    if (isResetView) {
+      this.resetPendingForTable.delete(tableId);
+    }
+
+    const addedCount = updateEvent.added != null ? updateEvent.added.size : 0;
+    const removedCount =
+      updateEvent.removed != null ? updateEvent.removed.size : 0;
+    const modifiedCount =
+      updateEvent.modified != null ? updateEvent.modified.size : 0;
+
+    this.emit({
+      type: 'DATA_UPDATED',
+      tableId,
+      isInitialLoad: isFirstLoad,
+      addedCount,
+      removedCount,
+      modifiedCount,
+      isResetView,
+      isDownsampleSwap,
+    });
+  }
+
+  // ---- Widget & utility methods ----
+
+  private listenToWidget(): () => void {
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const handler = ((event: any) => {
+      try {
+        const data = event.detail;
+        const dataStr = data.getDataAsString();
+        const msg = JSON.parse(dataStr);
+        this.dbg(`widget msg: type=${msg.type}`);
+
+        if (msg.type === 'NEW_FIGURE' && msg.revision > this.revision) {
+          this.revision = msg.revision;
+          this.figureData = msg.figure;
+
+          this.emit({
+            type: 'FIGURE_UPDATED',
+            figure: this.figureData!,
+            tables: Array.from(this.tables.values()),
+          });
+        } else if (msg.type === 'AUTOBIN_FIGURE') {
+          const exported = (data.exportedObjects ??
+            []) as DhType.WidgetExportedObject[];
+          this.handleAutoBinFigure(msg as AutoBinFigureMessage, exported).catch(
+            err => log.error('handleAutoBinFigure failed', err)
+          );
+        }
+      } catch (e) {
+        log.error('Error processing widget message', e);
+      }
+    }) as unknown as Parameters<typeof this.widget.addEventListener>[1];
+
+    this.widget.addEventListener(this.dh.Widget.EVENT_MESSAGE, handler);
+
+    // Detect widget close (server disconnect / variable removed)
+    const closeHandler = (() => {
+      log.warn('Widget closed');
+      this.emit({ type: 'DISCONNECTED', connected: false });
+    }) as unknown as Parameters<typeof this.widget.addEventListener>[1];
+    this.widget.addEventListener(this.dh.Widget.EVENT_CLOSE, closeHandler);
+
+    return () => {
+      this.widget.removeEventListener(this.dh.Widget.EVENT_MESSAGE, handler);
+      this.widget.removeEventListener(this.dh.Widget.EVENT_CLOSE, closeHandler);
+    };
+  }
+
+  /**
+   * Unwrap Deephaven wrapper types to plain JS values.
+   * DateWrapper -> epoch millis via asDate().getTime()
+   * LongWrapper -> number via asNumber()
+   */
+  // eslint-disable-next-line class-methods-use-this
+  private unwrapValue(val: unknown): unknown {
+    if (val == null) return val;
+    if (typeof val !== 'object') return val;
+
+    const asDate = val as { asDate?: () => Date };
+    if (typeof asDate.asDate === 'function') {
+      return asDate.asDate().getTime();
+    }
+
+    const asNum = val as { asNumber?: () => number };
+    if (typeof asNum.asNumber === 'function') {
+      return asNum.asNumber();
+    }
+
+    return val;
+  }
+
+  /**
+   * Whether the chart is "ready" — i.e. every series currently in
+   * ``figureData`` has at least one row of data in :attr:`tableDataMap`.
+   *
+   * For non-partitioned charts this becomes true on the first DATA_UPDATED
+   * after model.init. For ``by``-partitioned charts it additionally
+   * requires at least one runtime partition series to have been discovered.
+   * The image-snapshotter polls this signal to know when to take a stable
+   * screenshot without resorting to hard-coded waits.
+   */
+  isReady(): boolean {
+    if (this.figureData == null) return false;
+    // A partitioned chart with no keys discovered yet should NOT be
+    // considered ready — there's nothing to render.
+    const renderableSeries = this.figureData.series.filter(
+      series => series.partition == null
+    );
+    if (renderableSeries.length === 0) return false;
+    return renderableSeries.every(series => {
+      const { tableId } = series.dataMapping;
+      const tableData = this.tableDataMap.get(tableId);
+      if (!tableData) return false;
+      const { time: timeColName } = series.dataMapping.columns;
+      const timeCol = tableData[timeColName];
+      if (timeCol != null && timeCol.length > 0) return true;
+      // No rows arrived yet. Distinguish "still waiting for first data"
+      // from "source table is intentionally empty" (e.g. a `where(...)`
+      // that filters everything out — used by the pane_preserve_empty
+      // docs example). An empty source reports size === 0 immediately
+      // after fetch, so treat that as ready instead of hanging forever.
+      const table = this.tables.get(tableId);
+      return table != null && table.size === 0;
+    });
+  }
+
+  getFigureData(): TvlFigureData | null {
+    return this.figureData;
+  }
+
+  getColumnData(tableId: number): Map<string, unknown[]> | undefined {
+    const tableData = this.tableDataMap.get(tableId);
+    if (!tableData) return undefined;
+    // Convert Record to Map for backward compat with TradingViewUtils
+    const map = new Map<string, unknown[]>();
+    Object.entries(tableData).forEach(([key, val]) => {
+      map.set(key, val);
+    });
+    return map;
+  }
+
+  getSeriesConfigs(): TvlSeriesConfig[] {
+    return this.figureData?.series ?? [];
+  }
+
+  /** Get the set of table IDs that are JS-downsampled. */
+  getDownsampledTableIds(): Set<number> {
+    return this.jsDownsampledTableIds;
+  }
+
+  /** Get a table by ID. */
+  getTable(tableId: number): DhType.Table | undefined {
+    return this.tables.get(tableId);
+  }
+
+  close(): void {
+    this.closed = true;
+
+    // Clean up subscription event listeners
+    this.subscriptionCleanupMap.forEach(cleanupSet => {
+      cleanupSet.forEach(cleanup => {
+        cleanup();
+      });
+    });
+    this.subscriptionCleanupMap.clear();
+
+    // Clean up subscriptions
+    this.tableSubscriptionMap.forEach(sub => {
+      sub.close();
+    });
+    this.tableSubscriptionMap.clear();
+
+    // Close downsampled tables
+    this.downsampledTableMap.forEach(table => {
+      try {
+        table.close();
+      } catch {
+        // ignore
+      }
+    });
+    this.downsampledTableMap.clear();
+
+    // Close original tables
+    this.originalTableMap.forEach(table => {
+      try {
+        table.close();
+      } catch {
+        // ignore
+      }
+    });
+    this.originalTableMap.clear();
+
+    // Close any remaining tables (non-downsampled)
+    this.tables.forEach((table, tableId) => {
+      // Don't double-close tables that were in original/downsampled maps
+      if (
+        !this.jsDownsampledTableIds.has(tableId)
+      ) {
+        try {
+          table.close();
+        } catch {
+          // ignore
+        }
+      }
+    });
+    this.tables.clear();
+
+    // Clean up widget listener
+    if (this.widgetListenerCleanup) {
+      this.widgetListenerCleanup();
+      this.widgetListenerCleanup = null;
+    }
+
+    // Clean up all per-template partition watchers
+    this.partitionWatchers.forEach(({ partitionedTable, cleanup }) => {
+      try {
+        cleanup();
+      } catch {
+        // ignore
+      }
+      if (partitionedTable?.close) {
+        try {
+          partitionedTable.close();
+        } catch {
+          // ignore
+        }
+      }
+    });
+    this.partitionWatchers.clear();
+
+    this.listeners.clear();
+    this.chartDataMap.clear();
+    this.tableDataMap.clear();
+    this.resetPendingForTable.clear();
+    this.freshDownsampleTables.clear();
+    this.jsDownsampledTableIds.clear();
+    this.autoBinnedTableIds.clear();
+  }
+}
+
+export default TradingViewChartModel;
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewChartPanel.tsx b/plugins/tradingview-lightweight/src/js/src/TradingViewChartPanel.tsx
new file mode 100644
index 000000000..c4a3b1b4c
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewChartPanel.tsx
@@ -0,0 +1,76 @@
+import React, { useCallback, useState } from 'react';
+import type { dh as DhType } from '@deephaven/jsapi-types';
+import { type WidgetPanelProps } from '@deephaven/plugin';
+import { WidgetPanel } from '@deephaven/dashboard-core-plugins';
+import TradingViewChart from './TradingViewChart';
+
+/**
+ * Panel wrapper for TradingViewChart.
+ *
+ * Wraps the chart in WidgetPanel to get standard DH panel features:
+ * - Session-level disconnect/reconnect detection
+ * - LoadingOverlay (spinner + error + disconnect message)
+ * - Panel lifecycle (hide/show/focus events)
+ */
+export function TradingViewChartPanel(
+  props: WidgetPanelProps<DhType.Widget>
+): JSX.Element {
+  const { fetch, metadata } = props;
+
+  const [isLoading, setIsLoading] = useState(true);
+  const [error, setError] = useState<string | null>(null);
+  const [isDisconnected, setIsDisconnected] = useState(false);
+
+  const handleLoadingChange = useCallback((loading: boolean) => {
+    setIsLoading(loading);
+  }, []);
+
+  const handleError = useCallback((err: string | null) => {
+    setError(err);
+  }, []);
+
+  const handleSessionClose = useCallback(() => {
+    setIsDisconnected(true);
+    setError('Chart disconnected');
+  }, []);
+
+  const handleSessionOpen = useCallback(() => {
+    setIsDisconnected(false);
+    setError(null);
+  }, []);
+
+  const name = metadata?.name ?? 'TradingView Chart';
+
+  // Cast to any to bridge golden-layout type version mismatches between
+  // @deephaven/plugin and @deephaven/dashboard-core-plugins.
+  // At runtime these are the same objects provided by the IDE.
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  const wp = WidgetPanel as any;
+
+  return React.createElement(
+    wp,
+    {
+      glContainer: props.glContainer,
+      glEventHub: props.glEventHub,
+      descriptor: {
+        name,
+        type: 'TvlChart',
+      },
+      className: 'dh-tvl-panel',
+      isLoading,
+      isLoaded: !isLoading,
+      isDisconnected,
+      errorMessage: error ?? '',
+      onSessionClose: handleSessionClose,
+      onSessionOpen: handleSessionOpen,
+    },
+    <TradingViewChart
+      fetch={fetch}
+      metadata={metadata}
+      onLoadingChange={handleLoadingChange}
+      onError={handleError}
+    />
+  );
+}
+
+export default TradingViewChartPanel;
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewChartRenderer.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewChartRenderer.ts
new file mode 100644
index 000000000..0d7c27cfd
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewChartRenderer.ts
@@ -0,0 +1,1205 @@
+import {
+  createChart,
+  createYieldCurveChart,
+  createOptionsChart,
+  createSeriesMarkers,
+  createTextWatermark,
+  ColorType,
+  CandlestickSeries,
+  BarSeries,
+  LineSeries,
+  AreaSeries,
+  BaselineSeries,
+  HistogramSeries,
+  TickMarkType,
+} from 'lightweight-charts';
+import type {
+  IChartApi,
+  ISeriesApi,
+  IPriceLine,
+  SeriesType,
+  DeepPartial,
+  ChartOptions,
+  YieldCurveChartOptions,
+  PriceChartOptions,
+  SeriesMarker,
+  Time,
+  SeriesPartialOptionsMap,
+  ISeriesMarkersPluginApi,
+  ITextWatermarkPluginApi,
+  TextWatermarkOptions,
+  MouseEventParams,
+} from 'lightweight-charts';
+import Log from '@deephaven/log';
+import type {
+  TvlChartType,
+  TvlSeriesConfig,
+  TvlMarkerData,
+  TvlTooltipOptions,
+} from './TradingViewTypes';
+import { resolveColor, resolveColorsDeep } from './TradingViewColors';
+import { TradingViewTooltip } from './TradingViewTooltip';
+
+const log = Log.module('TradingViewChartRenderer');
+
+/**
+ * Registry of predefined price formatters. These are referenced by name
+ * from the Python API via `localization.priceFormatterName`.
+ */
+const PRICE_FORMATTERS: Record<string, (price: number) => string> = {
+  currency_usd: (price: number) =>
+    new Intl.NumberFormat('en-US', {
+      style: 'currency',
+      currency: 'USD',
+    }).format(price),
+  currency_eur: (price: number) =>
+    new Intl.NumberFormat('de-DE', {
+      style: 'currency',
+      currency: 'EUR',
+    }).format(price),
+  currency_gbp: (price: number) =>
+    new Intl.NumberFormat('en-GB', {
+      style: 'currency',
+      currency: 'GBP',
+    }).format(price),
+  currency_jpy: (price: number) =>
+    new Intl.NumberFormat('ja-JP', {
+      style: 'currency',
+      currency: 'JPY',
+    }).format(price),
+  percent: (price: number) => `${price.toFixed(2)}%`,
+  compact: (price: number) => {
+    if (Math.abs(price) >= 1e9) return `${(price / 1e9).toFixed(1)}B`;
+    if (Math.abs(price) >= 1e6) return `${(price / 1e6).toFixed(1)}M`;
+    if (Math.abs(price) >= 1e3) return `${(price / 1e3).toFixed(1)}K`;
+    return price.toFixed(2);
+  },
+  scientific: (price: number) => price.toExponential(2),
+};
+
+/**
+ * Resolve `localization.priceFormatterName` (a string) into a real
+ * `localization.priceFormatter` function, returning the remaining
+ * chart options with the substitution applied.
+ */
+function resolveLocalization(
+  opts: Record<string, unknown>
+): Record<string, unknown> {
+  const { localization: locRaw, ...rest } = opts;
+  if (locRaw == null) return opts;
+
+  const loc = locRaw as Record<string, unknown>;
+  const { priceFormatterName, ...locRest } = loc;
+  if (
+    typeof priceFormatterName === 'string' &&
+    PRICE_FORMATTERS[priceFormatterName]
+  ) {
+    return {
+      ...rest,
+      localization: {
+        ...locRest,
+        priceFormatter: PRICE_FORMATTERS[priceFormatterName],
+      },
+    };
+  }
+  return opts;
+}
+
+/** Default watermark font size when the user only provides text. */
+const DEFAULT_WATERMARK_FONT_SIZE = 66;
+
+/** Default watermark alpha applied to the chart's textColor. */
+const DEFAULT_WATERMARK_ALPHA = 0.2;
+
+/**
+ * Shape of watermark options as serialized by the Python API.
+ * The Python side sends a flat object; we convert it to the v5
+ * `createTextWatermark` plugin format (which uses a `lines` array).
+ */
+interface WatermarkLineOptions {
+  text: string;
+  color?: string;
+  fontSize?: number;
+  fontStyle?: string;
+  lineHeight?: number;
+}
+
+interface LegacyWatermarkOptions {
+  text?: string;
+  color?: string;
+  visible?: boolean;
+  fontSize?: number;
+  fontFamily?: string;
+  fontStyle?: string;
+  lineHeight?: number;
+  horzAlign?: string;
+  vertAlign?: string;
+  lines?: WatermarkLineOptions[];
+}
+
+/**
+ * Derive a semi-transparent watermark color from the chart's text color.
+ * Handles hex (#RGB, #RRGGBB), rgb(), and rgba() formats.
+ */
+function deriveWatermarkColor(textColor: string): string {
+  if (textColor.startsWith('#')) {
+    let hex = textColor;
+    // Expand shorthand #RGB to #RRGGBB
+    if (hex.length === 4) {
+      hex = `#${hex[1]}${hex[1]}${hex[2]}${hex[2]}${hex[3]}${hex[3]}`;
+    }
+    return hexToRgba(hex, DEFAULT_WATERMARK_ALPHA);
+  }
+
+  // rgb(r, g, b) or rgba(r, g, b, a) — replace/add alpha
+  const match = textColor.match(
+    /rgba?\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*[\d.]+\s*)?\)/
+  );
+  if (match) {
+    return `rgba(${match[1]}, ${match[2]}, ${match[3]}, ${DEFAULT_WATERMARK_ALPHA})`;
+  }
+
+  // Fallback: white at low opacity (works on dark and light backgrounds)
+  return `rgba(255, 255, 255, ${DEFAULT_WATERMARK_ALPHA})`;
+}
+
+/**
+ * Format a UTC-seconds timestamp as a date/time string.
+ * @param utcSeconds UTC timestamp in seconds (as used by lightweight-charts Time)
+ * @param includeMs If true, append .SSS milliseconds
+ */
+function formatDateTime(utcSeconds: number, includeMs: boolean): string {
+  const d = new Date(utcSeconds * 1000);
+  const YYYY = d.getUTCFullYear();
+  const MM = String(d.getUTCMonth() + 1).padStart(2, '0');
+  const DD = String(d.getUTCDate()).padStart(2, '0');
+  const hh = String(d.getUTCHours()).padStart(2, '0');
+  const mm = String(d.getUTCMinutes()).padStart(2, '0');
+  const ss = String(d.getUTCSeconds()).padStart(2, '0');
+  const ms = String(d.getUTCMilliseconds()).padStart(3, '0');
+
+  const hasTime = hh !== '00' || mm !== '00' || ss !== '00' || ms !== '000';
+
+  if (!hasTime) {
+    return `${YYYY}-${MM}-${DD}`;
+  }
+  const base = `${YYYY}-${MM}-${DD} ${hh}:${mm}:${ss}`;
+  return includeMs ? `${base}.${ms}` : base;
+}
+
+/**
+ * Custom tick mark formatter that uses uniform precision per level.
+ * Year/Month ticks show date only; DayOfMonth shows date; Time ticks
+ * show HH:MM:SS consistently (no mixing HH:MM and HH:MM:SS).
+ */
+function defaultTickMarkFormatter(
+  time: unknown,
+  tickMarkType: TickMarkType
+): string | null {
+  const t = time as number;
+  const d = new Date(t * 1000);
+
+  switch (tickMarkType) {
+    case TickMarkType.Year:
+      return String(d.getUTCFullYear());
+    case TickMarkType.Month:
+      return d.toLocaleDateString('en-US', {
+        month: 'short',
+        year: 'numeric',
+        timeZone: 'UTC',
+      });
+    case TickMarkType.DayOfMonth: {
+      return d.toLocaleDateString('en-US', {
+        month: 'short',
+        day: 'numeric',
+        timeZone: 'UTC',
+      });
+    }
+    case TickMarkType.Time:
+    case TickMarkType.TimeWithSeconds:
+    default: {
+      // Always show HH:MM:SS for uniform precision
+      const hh = String(d.getUTCHours()).padStart(2, '0');
+      const mm = String(d.getUTCMinutes()).padStart(2, '0');
+      const ss = String(d.getUTCSeconds()).padStart(2, '0');
+      return `${hh}:${mm}:${ss}`;
+    }
+  }
+}
+
+/**
+ * Tick mark formatter for the yield-curve chart. LWC's createYieldCurveChart
+ * treats horizontal-axis values as months and internally maps them to seconds
+ * from the unix epoch, so the default time-axis formatter would render
+ * Tenor=240 as "1990-01-01" (i.e. 240 months after 1970). We override the
+ * formatter so the axis reads as "Xm" / "Xy" instead.
+ */
+function yieldCurveTickMarkFormatter(time: unknown): string {
+  const months = Number(time) || 0;
+  if (months >= 12 && months % 12 === 0) return `${months / 12}y`;
+  if (months >= 12) return `${(months / 12).toFixed(1)}y`;
+  return `${months}m`;
+}
+
+/**
+ * Crosshair time formatter for yield-curve charts: format the maturity
+ * value (months) as a duration instead of a date.
+ */
+function yieldCurveCrosshairFormatter(time: unknown): string {
+  return yieldCurveTickMarkFormatter(time);
+}
+
+/**
+ * Tick mark formatter for the options / custom-numeric chart. LWC's
+ * createOptionsChart maps each x-value to seconds-from-epoch, so the
+ * default time-axis formatter renders X=5 as "1970-01-01 00:00:05". We
+ * override it so the axis reads back the raw numeric value (with light
+ * formatting so 100000 renders as "100,000").
+ */
+function optionsTickMarkFormatter(time: unknown): string {
+  const n = Number(time);
+  if (!Number.isFinite(n)) return '';
+  return n.toLocaleString('en-US', { maximumFractionDigits: 6 });
+}
+
+function optionsCrosshairFormatter(time: unknown): string {
+  return optionsTickMarkFormatter(time);
+}
+
+/**
+ * Crosshair / tooltip time formatter — always shows full precision
+ * including milliseconds: "YYYY-MM-DD HH:MM:SS.mmm"
+ */
+function crosshairTimeFormatter(time: unknown): string {
+  return formatDateTime(time as number, true);
+}
+
+// Map series type string to series definition constant
+const SERIES_DEFINITIONS: Record<string, unknown> = {
+  Candlestick: CandlestickSeries,
+  Bar: BarSeries,
+  Line: LineSeries,
+  Area: AreaSeries,
+  Baseline: BaselineSeries,
+  Histogram: HistogramSeries,
+};
+
+/**
+ * Series types whose color comes from OHLC up/down theme colors
+ * rather than the colorway palette.
+ */
+const OHLC_TYPES = new Set<string>(['Candlestick', 'Bar']);
+
+/**
+ * Map of non-OHLC series type to the option key for its primary color.
+ */
+const PRIMARY_COLOR_KEY: Partial<Record<TvlSeriesConfig['type'], string>> = {
+  Line: 'color',
+  Area: 'lineColor',
+  Histogram: 'color',
+  Baseline: 'topLineColor',
+};
+
+/**
+ * Convert a hex color (#RRGGBB) to an rgba string with the given alpha.
+ */
+function hexToRgba(color: string, alpha: number): string {
+  // Handle #RGB shorthand
+  let hex = color;
+  if (hex.startsWith('#') && hex.length === 4) {
+    hex = `#${hex[1]}${hex[1]}${hex[2]}${hex[2]}${hex[3]}${hex[3]}`;
+  }
+  if (hex.startsWith('#') && hex.length >= 7) {
+    const r = parseInt(hex.slice(1, 3), 16);
+    const g = parseInt(hex.slice(3, 5), 16);
+    const b = parseInt(hex.slice(5, 7), 16);
+    return `rgba(${r}, ${g}, ${b}, ${alpha})`;
+  }
+  // Handle rgb(r, g, b) / rgba(r, g, b, a) — replace alpha
+  const match = color.match(
+    /rgba?\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*[\d.]+\s*)?\)/
+  );
+  if (match) {
+    return `rgba(${match[1]}, ${match[2]}, ${match[3]}, ${alpha})`;
+  }
+  // Unrecognized format — return as-is rather than producing NaN
+  return color;
+}
+
+/**
+ * Imperative wrapper around TradingView Lightweight Charts.
+ * Manages chart and series lifecycle, data updates, and theming.
+ */
+class TradingViewChartRenderer {
+  private chart: IChartApi;
+
+  private chartType: TvlChartType;
+
+  private seriesMap: Map<string, ISeriesApi<SeriesType>> = new Map();
+
+  /** Resolved primary color per series id, used to tint the tracking tooltip. */
+  private seriesColors: Map<string, string> = new Map();
+
+  /** Active tracking tooltip, when enabled via chartOptions.tooltip.visible. */
+  private tooltip: TradingViewTooltip | null = null;
+
+  private markersMap: Map<string, ISeriesMarkersPluginApi<Time>> = new Map();
+
+  /** Dynamic price lines that track a column's last-row value. */
+  private dynamicPriceLines: Map<
+    string,
+    Array<{ priceLine: IPriceLine; column: string }>
+  > = new Map();
+
+  private watermarkPlugin: ITextWatermarkPluginApi<Time> | null = null;
+
+  private textColor: string;
+
+  private colorway: string[] = [];
+
+  private ohlcColors: { upColor: string; downColor: string } | undefined;
+
+  private gridColor = '';
+
+  private container: HTMLElement;
+
+  /** Hidden whitespace series for proportional time spacing when downsampled. */
+  private scaffoldSeries: ISeriesApi<SeriesType> | null = null;
+
+  /** Whether scaffold is currently enabled. */
+  private scaffoldEnabled = false;
+
+  /**
+   * Watermark options captured at construction (or via the most recent
+   * setChartType call). Used to re-apply the watermark after the chart is
+   * rebuilt for a different chartType.
+   */
+  private constructorWatermark: LegacyWatermarkOptions | null = null;
+
+  /**
+   * Resolved chart options at construction time, kept so setChartType can
+   * rebuild the underlying chart with the new chartType while preserving
+   * theme/layout config.
+   */
+  private resolvedChartOpts: Record<string, unknown>;
+
+  constructor(
+    container: HTMLElement,
+    options: DeepPartial<ChartOptions> = {},
+    chartType: TvlChartType = 'standard'
+  ) {
+    this.container = container;
+    this.chartType = chartType;
+
+    // Extract watermark and resolve localization before passing to createChart.
+    // Resolve DH theme color names (e.g. "accent-300") to canvas-paintable
+    // values; lightweight-charts paints to canvas and can't resolve
+    // var(--dh-color-*) / theme tokens itself.
+    const { watermark: wmRaw, ...rawOpts } = resolveColorsDeep(
+      options as Record<string, unknown>
+    );
+    const chartOpts = resolveLocalization(rawOpts);
+
+    const resolvedTextColor =
+      ((chartOpts.layout as Record<string, unknown>)?.textColor as string) ??
+      '#D1D4DC';
+    this.textColor = resolvedTextColor;
+
+    this.gridColor =
+      ((
+        (chartOpts.grid as Record<string, unknown>)?.vertLines as Record<
+          string,
+          unknown
+        >
+      )?.color as string) ?? '';
+
+    this.resolvedChartOpts = chartOpts;
+    this.constructorWatermark = (wmRaw as LegacyWatermarkOptions) ?? null;
+    this.chart = this.buildChart(chartType);
+
+    if (wmRaw != null) {
+      this.applyWatermark(wmRaw as LegacyWatermarkOptions);
+    }
+  }
+
+  /**
+   * Build the underlying lightweight-charts instance for ``chartType`` using
+   * the already-resolved chart options. Called from the constructor and from
+   * :meth:`setChartType` when the chart needs to be torn down and rebuilt.
+   */
+  private buildChart(chartType: TvlChartType): IChartApi {
+    const chartOpts = this.resolvedChartOpts;
+    const resolvedTextColor = this.textColor;
+    const commonOpts = {
+      ...chartOpts,
+      layout: {
+        ...(chartOpts.layout as Record<string, unknown>),
+        background: (chartOpts.layout as Record<string, unknown>)
+          ?.background ?? {
+          type: ColorType.Solid,
+          color: '#1E222D',
+        },
+        textColor: resolvedTextColor,
+        attributionLogo: false,
+      },
+      timeScale: {
+        timeVisible: true,
+        // Allow extreme compression so fitContent can show all data points.
+        // The default minBarSpacing (0.5px) limits the chart to ~width*2 bars,
+        // which is too few for downsampled tables (runChartDownsample output
+        // can be much larger than the requested pixel count).
+        minBarSpacing: 0.01,
+        tickMarkFormatter:
+          chartType === 'yieldCurve'
+            ? yieldCurveTickMarkFormatter
+            : chartType === 'options'
+              ? optionsTickMarkFormatter
+              : defaultTickMarkFormatter,
+        ...(chartOpts.timeScale as Record<string, unknown>),
+      },
+      localization: {
+        timeFormatter:
+          chartType === 'yieldCurve'
+            ? yieldCurveCrosshairFormatter
+            : chartType === 'options'
+              ? optionsCrosshairFormatter
+              : crosshairTimeFormatter,
+        ...(chartOpts.localization as Record<string, unknown>),
+      },
+      autoSize: true,
+    };
+
+    switch (chartType) {
+      case 'yieldCurve': {
+        // LWC's createYieldCurveChart uses its own horzScaleBehavior that
+        // ignores timeScale.tickMarkFormatter and localization.timeFormatter.
+        // The maturity-axis formatter lives on yieldCurve.formatTime.
+        const yieldOpts: Record<string, unknown> = {
+          ...commonOpts,
+          yieldCurve: {
+            ...((commonOpts as Record<string, unknown>).yieldCurve as
+              | Record<string, unknown>
+              | undefined),
+            formatTime: yieldCurveTickMarkFormatter,
+          },
+        };
+        return createYieldCurveChart(
+          this.container,
+          yieldOpts as DeepPartial<YieldCurveChartOptions>
+        ) as unknown as IChartApi;
+      }
+      case 'options':
+        return createOptionsChart(
+          this.container,
+          commonOpts as DeepPartial<PriceChartOptions>
+        ) as unknown as IChartApi;
+      default:
+        return createChart(
+          this.container,
+          commonOpts as DeepPartial<ChartOptions>
+        );
+    }
+  }
+
+  /**
+   * Switch the chart's horzScaleBehavior at runtime. Tears down the existing
+   * chart and rebuilds it. Intended to be called once during initial connect,
+   * before any series are added (the chartType arrives in the figure message,
+   * which is parsed *after* the renderer is constructed). No-op when ``ct``
+   * matches the current chart type.
+   */
+  setChartType(ct: TvlChartType): void {
+    if (ct === this.chartType) return;
+    if (this.seriesMap.size > 0) {
+      log.warn(
+        'setChartType called after series were added; ignoring change from',
+        this.chartType,
+        'to',
+        ct
+      );
+      return;
+    }
+    if (this.watermarkPlugin) {
+      this.watermarkPlugin.detach();
+      this.watermarkPlugin = null;
+    }
+    this.chart.remove();
+    this.chartType = ct;
+    this.chart = this.buildChart(ct);
+    if (this.constructorWatermark != null) {
+      this.applyWatermark(this.constructorWatermark);
+    }
+  }
+
+  /**
+   * Create or update the text watermark plugin from legacy flat options.
+   * Fills in sensible defaults so that `watermark_text="AAPL"` alone
+   * produces a large, centered, theme-aware watermark.
+   */
+  private applyWatermark(wm: LegacyWatermarkOptions): void {
+    const hasText =
+      (wm.text != null && wm.text !== '') ||
+      (wm.lines != null && wm.lines.length > 0);
+    if (wm.visible === false || !hasText) {
+      if (this.watermarkPlugin) {
+        this.watermarkPlugin.detach();
+        this.watermarkPlugin = null;
+      }
+      return;
+    }
+
+    // Build lines array — either from explicit multi-line or legacy single-line
+    const lines =
+      wm.lines != null
+        ? wm.lines.map(line => ({
+            text: line.text,
+            color: line.color ?? deriveWatermarkColor(this.textColor),
+            fontSize: line.fontSize ?? DEFAULT_WATERMARK_FONT_SIZE,
+            fontStyle: line.fontStyle,
+            lineHeight: line.lineHeight,
+          }))
+        : [
+            {
+              text: wm.text!,
+              color: wm.color ?? deriveWatermarkColor(this.textColor),
+              fontSize: wm.fontSize ?? DEFAULT_WATERMARK_FONT_SIZE,
+              fontStyle: wm.fontStyle,
+              lineHeight: wm.lineHeight,
+            },
+          ];
+
+    const wmOptions: DeepPartial<TextWatermarkOptions> = {
+      visible: wm.visible ?? true,
+      horzAlign:
+        (wm.horzAlign as TextWatermarkOptions['horzAlign']) ?? 'center',
+      vertAlign:
+        (wm.vertAlign as TextWatermarkOptions['vertAlign']) ?? 'center',
+      lines,
+    };
+
+    if (this.watermarkPlugin) {
+      this.watermarkPlugin.applyOptions(wmOptions);
+    } else {
+      this.watermarkPlugin = createTextWatermark(
+        this.chart.panes()[0],
+        wmOptions
+      );
+    }
+  }
+
+  /**
+   * Configure series from figure data.
+   * Removes old series and creates new ones.
+   *
+   * When a colorway is provided, series that have no user-specified primary
+   * color will be assigned colors from the palette in order.  OHLC types
+   * (Candlestick / Bar) use the separate ohlcColors instead.
+   */
+  configureSeries(
+    seriesConfigs: TvlSeriesConfig[],
+    colorway: string[] = [],
+    ohlcColors?: { upColor: string; downColor: string },
+    enableScaffold = false
+  ): void {
+    // Resolve any DH theme color names in user-supplied options up front so
+    // canvas drawing calls receive concrete CSS color strings (hex/rgba).
+    seriesConfigs.forEach(cfg => {
+      if (cfg.options) resolveColorsDeep(cfg.options);
+      cfg.priceLines?.forEach(pl => {
+        if (pl.color != null) pl.color = resolveColor(pl.color);
+      });
+    });
+    // eslint-disable-next-line no-param-reassign
+    colorway = colorway.map(c => resolveColor(c) ?? c);
+    if (ohlcColors) {
+      // eslint-disable-next-line no-param-reassign
+      ohlcColors = {
+        upColor: resolveColor(ohlcColors.upColor) ?? ohlcColors.upColor,
+        downColor: resolveColor(ohlcColors.downColor) ?? ohlcColors.downColor,
+      };
+    }
+
+    // Store theme colors for marker resolution
+    this.colorway = colorway;
+    this.ohlcColors = ohlcColors;
+    this.scaffoldEnabled = enableScaffold;
+
+    // Remove existing series (including scaffold)
+    // Detach marker plugins before removing series
+    this.markersMap.forEach(plugin => {
+      try {
+        plugin.detach();
+      } catch {
+        // Plugin may already be detached if series was removed
+      }
+    });
+    this.markersMap.clear();
+    if (this.scaffoldSeries) {
+      try {
+        this.chart.removeSeries(this.scaffoldSeries);
+      } catch {
+        // ignore
+      }
+      this.scaffoldSeries = null;
+    }
+    this.seriesMap.forEach(series => {
+      this.chart.removeSeries(series);
+    });
+    this.seriesMap.clear();
+    this.seriesColors.clear();
+    this.dynamicPriceLines.clear();
+
+    // Create scaffold FIRST so it occupies base time positions
+    if (enableScaffold) {
+      this.createScaffold();
+    }
+
+    // Create new series. Skip partition templates — those are NOT
+    // rendered directly; the model's partition-watcher clones each
+    // template into one runtime series per partition key (with a
+    // synthesized id) and pushes those into figureData.series.
+    let colorIndex = 0;
+    seriesConfigs.forEach(config => {
+      if (config.partition != null) {
+        return;
+      }
+      const options: Record<string, unknown> = { ...config.options };
+
+      if (OHLC_TYPES.has(config.type)) {
+        // Apply OHLC theme defaults when not user-specified
+        if (ohlcColors) {
+          if (options.upColor == null) options.upColor = ohlcColors.upColor;
+          if (options.downColor == null) {
+            options.downColor = ohlcColors.downColor;
+          }
+          // Derive border and wick colors from up/down so the library
+          // defaults (blue-ish tint) don't bleed through.
+          const up = (options.upColor as string) ?? ohlcColors.upColor;
+          const down = (options.downColor as string) ?? ohlcColors.downColor;
+          if (options.borderUpColor == null) options.borderUpColor = up;
+          if (options.borderDownColor == null) options.borderDownColor = down;
+          if (options.wickUpColor == null) options.wickUpColor = up;
+          if (options.wickDownColor == null) options.wickDownColor = down;
+        }
+      } else if (colorway.length > 0) {
+        const colorKey =
+          PRIMARY_COLOR_KEY[config.type as keyof typeof PRIMARY_COLOR_KEY];
+        if (colorKey != null && options[colorKey] == null) {
+          const color = colorway[colorIndex % colorway.length];
+          options[colorKey] = color;
+
+          // Derive semi-transparent fill colors for area series
+          if (config.type === 'Area') {
+            if (options.topColor == null) {
+              options.topColor = hexToRgba(color, 0.4);
+            }
+            if (options.bottomColor == null) {
+              options.bottomColor = hexToRgba(color, 0);
+            }
+          }
+
+          // Derive fill colors for baseline regions
+          if (config.type === 'Baseline') {
+            // Above baseline: from colorway
+            if (options.topFillColor1 == null) {
+              options.topFillColor1 = hexToRgba(color, 0.3);
+            }
+            if (options.topFillColor2 == null) {
+              options.topFillColor2 = hexToRgba(color, 0);
+            }
+            // Below baseline: from OHLC decrease color
+            if (ohlcColors) {
+              if (options.bottomLineColor == null) {
+                options.bottomLineColor = ohlcColors.downColor;
+              }
+              if (options.bottomFillColor1 == null) {
+                options.bottomFillColor1 = hexToRgba(
+                  ohlcColors.downColor,
+                  0.05
+                );
+              }
+              if (options.bottomFillColor2 == null) {
+                options.bottomFillColor2 = hexToRgba(
+                  ohlcColors.downColor,
+                  0.28
+                );
+              }
+            }
+          }
+        }
+        colorIndex += 1;
+      }
+
+      // Theme the baseline reference line (percentage/indexed modes)
+      if (options.baseLineColor == null && this.gridColor) {
+        options.baseLineColor = this.gridColor;
+      }
+
+      const series = this.createSeries({
+        ...config,
+        options,
+      });
+      if (series) {
+        this.seriesMap.set(config.id, series);
+
+        // Record the resolved primary color for the tracking tooltip's title
+        // tint. OHLC types have no single line color, so use the up color.
+        const tooltipColorKey = OHLC_TYPES.has(config.type)
+          ? 'upColor'
+          : PRIMARY_COLOR_KEY[config.type as keyof typeof PRIMARY_COLOR_KEY];
+        const seriesColor =
+          tooltipColorKey != null
+            ? (options[tooltipColorKey] as string | undefined)
+            : undefined;
+        if (seriesColor != null && seriesColor !== '') {
+          this.seriesColors.set(config.id, seriesColor);
+        }
+
+        // Apply per-series price scale options (autoScale, scaleMargins)
+        if (config.priceScaleOptions) {
+          series.priceScale().applyOptions(config.priceScaleOptions);
+        }
+
+        // Apply price lines (static and dynamic)
+        if (config.priceLines) {
+          const dynamicEntries: Array<{
+            priceLine: IPriceLine;
+            column: string;
+          }> = [];
+
+          config.priceLines.forEach(pl => {
+            const priceLine = series.createPriceLine({
+              price: pl.price ?? 0,
+              color: pl.color ?? this.textColor,
+              lineWidth: pl.lineWidth as 1 | 2 | 3 | 4 | undefined,
+              lineStyle: pl.lineStyle,
+              axisLabelVisible: pl.axisLabelVisible,
+              title: pl.title,
+            });
+
+            if (pl.column != null && pl.column !== '') {
+              dynamicEntries.push({ priceLine, column: pl.column });
+            }
+          });
+
+          if (dynamicEntries.length > 0) {
+            this.dynamicPriceLines.set(config.id, dynamicEntries);
+          }
+        }
+      }
+    });
+  }
+
+  private createSeries(config: TvlSeriesConfig): ISeriesApi<SeriesType> | null {
+    const definition = SERIES_DEFINITIONS[config.type];
+    if (definition == null) {
+      log.warn('Unknown series type:', config.type);
+      return null;
+    }
+
+    const options = config.options as SeriesPartialOptionsMap[SeriesType];
+    return this.chart.addSeries(
+      definition as Parameters<typeof this.chart.addSeries>[0],
+      options,
+      config.paneIndex
+    );
+  }
+
+  /**
+   * Replace all data for a specific series. Use only for initial load
+   * or full reconfiguration — NOT for ticking updates.
+   */
+  setSeriesData(seriesId: string, data: unknown[]): void {
+    const series = this.seriesMap.get(seriesId);
+    if (!series) {
+      log.warn('Series not found:', seriesId);
+      return;
+    }
+    series.setData(data as Parameters<typeof series.setData>[0]);
+  }
+
+  /**
+   * Update the last bar or append a new bar to a series.
+   * This is the performant way to handle ticking/streaming data
+   * per the TradingView docs — avoids replacing the entire dataset.
+   */
+  updateSeriesPoint(seriesId: string, point: unknown): void {
+    const series = this.seriesMap.get(seriesId);
+    if (!series) {
+      log.warn('Series not found for update:', seriesId);
+      return;
+    }
+    series.update(point as Parameters<typeof series.update>[0]);
+  }
+
+  /**
+   * Set markers on a specific series.
+   */
+  /**
+   * Resolve a theme-aware default color for a marker.
+   * - Up-arrow markers (belowBar + arrowUp) → OHLC increase color
+   * - Down-arrow markers (aboveBar + arrowDown) → OHLC decrease color
+   * - All others → first colorway color, then text color as final fallback
+   */
+  private resolveMarkerColor(m: TvlMarkerData): string {
+    if (m.color != null && m.color !== '') return m.color;
+    if (this.ohlcColors != null) {
+      if (m.position === 'belowBar' && m.shape === 'arrowUp') {
+        return this.ohlcColors.upColor;
+      }
+      if (m.position === 'aboveBar' && m.shape === 'arrowDown') {
+        return this.ohlcColors.downColor;
+      }
+    }
+    if (this.colorway.length > 0) return this.colorway[0];
+    return this.textColor;
+  }
+
+  setSeriesMarkers(seriesId: string, markers: TvlMarkerData[]): void {
+    const series = this.seriesMap.get(seriesId);
+    if (!series) return;
+
+    const chartMarkers: SeriesMarker<Time>[] = markers.map(m => {
+      const raw = this.resolveMarkerColor(m);
+      return {
+        time: m.time as Time,
+        position: m.position,
+        shape: m.shape,
+        color: resolveColor(raw) ?? raw,
+        text: m.text,
+        size: m.size,
+        ...(m.price != null ? { price: m.price } : {}),
+      };
+    }) as SeriesMarker<Time>[];
+
+    // Use createSeriesMarkers API for v5
+    let markerPlugin = this.markersMap.get(seriesId);
+    if (!markerPlugin) {
+      markerPlugin = createSeriesMarkers(series, chartMarkers);
+      this.markersMap.set(seriesId, markerPlugin);
+    } else {
+      markerPlugin.setMarkers(chartMarkers);
+    }
+  }
+
+  /**
+   * Update dynamic price lines for a series by reading the last-row
+   * value of each tracked column from the current table data.
+   */
+  updateDynamicPriceLines(
+    seriesId: string,
+    columnData: Map<string, unknown[]>
+  ): void {
+    const entries = this.dynamicPriceLines.get(seriesId);
+    if (!entries) return;
+
+    entries.forEach(({ priceLine, column }) => {
+      const data = columnData.get(column);
+      if (data && data.length > 0) {
+        const lastValue = data[data.length - 1];
+        if (typeof lastValue === 'number' && !Number.isNaN(lastValue)) {
+          priceLine.applyOptions({ price: lastValue });
+        }
+      }
+    });
+  }
+
+  /**
+   * Apply new chart-level options (e.g., on theme change).
+   */
+  applyOptions(options: DeepPartial<ChartOptions>): void {
+    const { watermark: wmRaw, ...rawOpts } = resolveColorsDeep(
+      options as Record<string, unknown>
+    );
+    const chartOpts = resolveLocalization(rawOpts);
+
+    // Update cached theme colors so derived defaults use the new values
+    const newTextColor = (chartOpts.layout as Record<string, unknown>)
+      ?.textColor as string | undefined;
+    if (newTextColor != null && newTextColor !== '') {
+      this.textColor = newTextColor;
+    }
+    const newGridColor = (
+      (chartOpts.grid as Record<string, unknown>)?.vertLines as Record<
+        string,
+        unknown
+      >
+    )?.color as string | undefined;
+    if (newGridColor != null && newGridColor !== '') {
+      this.gridColor = newGridColor;
+    }
+
+    // Merge into the cached options so consumers that read resolvedChartOpts
+    // later (hasTooltip(), and setChartType's rebuild) see the figure's
+    // chartOptions — which arrive here via applyOptions, not the constructor.
+    this.resolvedChartOpts = { ...this.resolvedChartOpts, ...chartOpts };
+
+    this.chart.applyOptions(chartOpts as DeepPartial<ChartOptions>);
+    if (wmRaw != null) {
+      this.applyWatermark(wmRaw as LegacyWatermarkOptions);
+    }
+  }
+
+  /**
+   * Resize the chart to fill its container.
+   */
+  resize(width: number, height: number): void {
+    this.chart.resize(width, height);
+  }
+
+  /**
+   * Fit all data into view.
+   */
+  fitContent(): void {
+    this.chart.timeScale().fitContent();
+  }
+
+  /**
+   * Apply stretch factors to panes to control their relative sizes.
+   * Must be called after configureSeries() since panes are created
+   * implicitly by addSeries(def, opts, paneIndex).
+   */
+  applyPaneStretchFactors(factors: number[]): void {
+    const panes = this.chart.panes();
+    for (let i = 0; i < factors.length && i < panes.length; i += 1) {
+      panes[i].setStretchFactor(factors[i]);
+    }
+  }
+
+  /**
+   * Get the chart type.
+   */
+  getChartType(): TvlChartType {
+    return this.chartType;
+  }
+
+  /**
+   * Get the chart's current text color (for theme-aware defaults).
+   */
+  getTextColor(): string {
+    return this.textColor;
+  }
+
+  /**
+   * Get the underlying chart API for advanced use.
+   */
+  getChart(): IChartApi {
+    return this.chart;
+  }
+
+  /**
+   * Convert a TZ-shifted epoch-seconds time to an x coordinate (pane-relative
+   * pixels), or null if outside the visible range. Test-only: used by the
+   * Playwright inversion-oracle to compute deterministic clicks.
+   */
+  timeToCoordinate(timeSec: number): number | null {
+    return this.chart.timeScale().timeToCoordinate(timeSec as Time);
+  }
+
+  /**
+   * Convert a price on a series' scale to a y coordinate (pane-relative
+   * pixels), or null if the series is unknown. Test-only companion to
+   * {@link timeToCoordinate}.
+   */
+  priceToCoordinate(seriesId: string, price: number): number | null {
+    const series = this.seriesMap.get(seriesId);
+    if (!series) return null;
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    return series.priceToCoordinate(price as any);
+  }
+
+  /** Current series ids (insertion order). Test-only. */
+  getSeriesIds(): string[] {
+    return Array.from(this.seriesMap.keys());
+  }
+
+  /** Reset all price scales to auto-fit visible data. */
+  resetPriceScales(): void {
+    this.seriesMap.forEach(series => {
+      try {
+        series.priceScale().setAutoScale(true);
+      } catch {
+        // series may not be ready
+      }
+    });
+  }
+
+  /** Plot-area width in pixels (excludes price scale). */
+  getTimeScaleWidth(): number {
+    return this.chart.timeScale().width();
+  }
+
+  /** Subscribe to visible logical range changes (zoom/pan detection). */
+  subscribeVisibleLogicalRangeChange(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    handler: (range: any) => void
+  ): () => void {
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const ts = this.chart.timeScale() as any;
+    ts.subscribeVisibleLogicalRangeChange(handler);
+    return () => ts.unsubscribeVisibleLogicalRangeChange(handler);
+  }
+
+  /** Subscribe to chart single-click (press detection). */
+  subscribeClick(handler: (params: MouseEventParams) => void): () => void {
+    this.chart.subscribeClick(handler);
+    return () => this.chart.unsubscribeClick(handler);
+  }
+
+  /**
+   * Subscribe to chart double-click. Accepts a handler taking the LWC
+   * MouseEventParams; a plain `() => void` (used by the internal reset
+   * subscriber) is assignable and remains backward compatible.
+   */
+  subscribeDblClick(handler: (params: MouseEventParams) => void): () => void {
+    this.chart.subscribeDblClick(handler);
+    return () => this.chart.unsubscribeDblClick(handler);
+  }
+
+  /** Resolved primary color for a series id (for the tracking tooltip). */
+  getSeriesColor(id: string): string | undefined {
+    return this.seriesColors.get(id);
+  }
+
+  /** Format a crosshair time the same way this chart's time axis does. */
+  private formatCrosshairTime(time: unknown): string {
+    switch (this.chartType) {
+      case 'yieldCurve':
+        return yieldCurveCrosshairFormatter(time);
+      case 'options':
+        return optionsCrosshairFormatter(time);
+      default:
+        return crosshairTimeFormatter(time);
+    }
+  }
+
+  /** True when the figure requested a tracking tooltip. */
+  hasTooltip(): boolean {
+    const tooltip = this.resolvedChartOpts.tooltip as
+      | TvlTooltipOptions
+      | undefined;
+    return tooltip?.visible === true;
+  }
+
+  /**
+   * Create the tracking tooltip and subscribe it to crosshair moves. Returns
+   * a cleanup that unsubscribes and removes the tooltip element. No-op (returns
+   * a no-op cleanup) when the figure did not request a tooltip. Must be called
+   * after :meth:`configureSeries` so series colors are known.
+   */
+  setupTooltip(): () => void {
+    if (!this.hasTooltip()) {
+      return () => undefined;
+    }
+    const options = this.resolvedChartOpts.tooltip as TvlTooltipOptions;
+    this.tooltip = new TradingViewTooltip({
+      container: this.container,
+      getSeriesId: s => this.getSeriesIdForApi(s),
+      getSeriesColor: id => this.getSeriesColor(id),
+      formatTime: time => this.formatCrosshairTime(time),
+      options,
+    });
+    const handler = (params: MouseEventParams): void => {
+      this.tooltip?.handleCrosshairMove(params);
+    };
+    this.chart.subscribeCrosshairMove(handler);
+    return () => {
+      this.chart.unsubscribeCrosshairMove(handler);
+      this.tooltip?.destroy();
+      this.tooltip = null;
+    };
+  }
+
+  /** Reverse lookup: find our series id for a given ISeriesApi. */
+  getSeriesIdForApi(series: ISeriesApi<SeriesType>): string | undefined {
+    let found: string | undefined;
+    this.seriesMap.forEach((value, id) => {
+      if (value === series) {
+        found = id;
+      }
+    });
+    return found;
+  }
+
+  /** User-facing title for a series API, when set. */
+  getSeriesTitleForApi(series: ISeriesApi<SeriesType>): string | undefined {
+    if (this.getSeriesIdForApi(series) == null) return undefined;
+    try {
+      const opts = series.options() as { title?: string };
+      const title = opts?.title;
+      return title != null && title !== '' ? title : undefined;
+    } catch {
+      return undefined;
+    }
+  }
+
+  /** Subscribe to chart size changes (resize detection). */
+  subscribeSizeChange(handler: () => void): () => void {
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const ts = this.chart.timeScale() as any;
+    ts.subscribeSizeChange(handler);
+    return () => ts.unsubscribeSizeChange(handler);
+  }
+
+  /** Whether scaffold is currently active. */
+  isScaffoldEnabled(): boolean {
+    return this.scaffoldEnabled && this.scaffoldSeries != null;
+  }
+
+  /**
+   * Create the hidden scaffold LineSeries.
+   * Must be called before data series are created so it occupies
+   * base time positions for proportional spacing.
+   */
+  private createScaffold(): void {
+    this.scaffoldSeries = this.chart.addSeries(
+      LineSeries,
+      { visible: false, priceScaleId: '' } as SeriesPartialOptionsMap[SeriesType]
+    );
+  }
+
+  /**
+   * Set whitespace data on the scaffold series to establish proportional
+   * time spacing across the data range.
+   *
+   * @param minTime Minimum time in TZ-shifted epoch seconds
+   * @param maxTime Maximum time in TZ-shifted epoch seconds
+   * @param count Number of whitespace entries to generate
+   */
+  setScaffoldData(minTime: number, maxTime: number, count: number): void {
+    if (!this.scaffoldSeries) return;
+    if (minTime >= maxTime || count <= 0) return;
+
+    const cappedCount = Math.min(30000, count);
+    const step = (maxTime - minTime) / cappedCount;
+    const data: Array<{ time: number }> = [];
+    for (let i = 0; i <= cappedCount; i += 1) {
+      data.push({ time: minTime + step * i });
+    }
+    this.scaffoldSeries.setData(
+      data as Parameters<typeof this.scaffoldSeries.setData>[0]
+    );
+  }
+
+  /**
+   * Dispose of the chart and clean up resources.
+   */
+  dispose(): void {
+    this.seriesMap.clear();
+    this.markersMap.clear();
+    this.dynamicPriceLines.clear();
+    this.scaffoldSeries = null;
+    this.seriesColors.clear();
+    if (this.tooltip) {
+      this.tooltip.destroy();
+      this.tooltip = null;
+    }
+    if (this.watermarkPlugin) {
+      this.watermarkPlugin.detach();
+      this.watermarkPlugin = null;
+    }
+    this.chart.remove();
+  }
+}
+
+export default TradingViewChartRenderer;
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewColors.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewColors.ts
new file mode 100644
index 000000000..f0b4aff32
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewColors.ts
@@ -0,0 +1,80 @@
+import {
+  colorValueStyle,
+  resolveCssVariablesInRecord,
+} from '@deephaven/components';
+
+// Matches a key ending in "color" or "Color", optionally with a numeric
+// suffix (baseline's gradient stops are topFillColor1, topFillColor2,
+// bottomFillColor1, bottomFillColor2 — without the \d* they'd be skipped
+// and DH theme names like "positive" would reach the canvas unresolved).
+const COLOR_KEY_RE = /[Cc]olor\d*$|^color$|^colorway$/;
+
+/**
+ * Resolve a single user-supplied color string into a value that
+ * lightweight-charts can paint into a canvas.
+ *
+ * Accepts:
+ *   - DH theme color names (e.g. "seafoam-500", "accent-300", "positive")
+ *   - var(--dh-color-...) expressions
+ *   - any standard CSS color (hex, named, rgb/rgba)
+ *
+ * DH color names are first converted to `var(--dh-color-<name>)`, then all
+ * `var(...)` expressions are resolved against the document's computed style
+ * (the same mechanism plugins/ui/UITable uses for `background_color="accent-300"`).
+ * Non-DH inputs pass through unchanged so the canvas APIs paint them directly.
+ *
+ * Returns the input unchanged when there is nothing to resolve, including
+ * "transparent" and empty strings.
+ */
+export function resolveColor(value: string | undefined): string | undefined {
+  if (value == null || value === '') return value;
+  const cssVar = colorValueStyle(value) ?? value;
+  // Fast path: no CSS variable to resolve. Avoids the getComputedStyle work
+  // and a jsdom-incompatible `CSS.supports` call on every hex/rgba string.
+  if (!cssVar.includes('var(')) return cssVar;
+  const resolved = resolveCssVariablesInRecord({ v: cssVar });
+  return resolved.v;
+}
+
+/**
+ * Walk an options object and resolve every string value whose key matches a
+ * color-like name in place. Handles arrays, nested objects, and the
+ * `colorway: string[]` palette shape. Mutates the input.
+ *
+ * This lets users pass DH theme names anywhere lightweight-charts accepts a
+ * color (series colors, layout/grid/crosshair, watermark, price lines, etc.)
+ * without us having to enumerate the dozens of color keys in the LWC option
+ * tree.
+ */
+export function resolveColorsDeep<T>(obj: T): T {
+  if (obj == null || typeof obj !== 'object') return obj;
+  walk(obj as Record<string, unknown>);
+  return obj;
+}
+
+function walk(node: unknown): void {
+  if (node == null || typeof node !== 'object') return;
+
+  if (Array.isArray(node)) {
+    for (let i = 0; i < node.length; i += 1) {
+      const v = node[i];
+      if (typeof v === 'string') {
+        // Bare string arrays (e.g. a colorway palette) — assume they're colors.
+        // No-op for non-color strings since resolveColor passes them through.
+        node[i] = resolveColor(v);
+      } else {
+        walk(v);
+      }
+    }
+    return;
+  }
+
+  const record = node as Record<string, unknown>;
+  Object.entries(record).forEach(([key, val]) => {
+    if (typeof val === 'string' && COLOR_KEY_RE.test(key)) {
+      record[key] = resolveColor(val);
+    } else if (val != null && typeof val === 'object') {
+      walk(val);
+    }
+  });
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewEventPayload.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewEventPayload.ts
new file mode 100644
index 000000000..137d4c4d4
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewEventPayload.ts
@@ -0,0 +1,143 @@
+import type {
+  MouseEventParams,
+  ISeriesApi,
+  SeriesType,
+} from 'lightweight-charts';
+import { unconvertTime } from './TradingViewUtils';
+import { extractSeriesPoint } from './TradingViewSeriesFocus';
+
+/**
+ * Per-series data at the event location, mirroring the shape of the
+ * lightweight-charts data the series was given: `{ value }` for
+ * line / area / baseline / histogram, OHLC for candlestick / bar.
+ */
+export type TvlWireSeriesData =
+  | { value: number }
+  | { open: number; high: number; low: number; close: number };
+
+/**
+ * JSON-safe payload for a press / double-press chart event. This intentionally
+ * mirrors lightweight-charts' `MouseEventParams` (time, point, logical,
+ * paneIndex, seriesData, the hovered series, and the source event's modifier
+ * keys) rather than inventing a chart model of its own. Two deliberate
+ * deviations, because a DOM/native object cannot cross the wire:
+ *
+ * - the hovered `ISeriesApi` is replaced by our string series identity
+ *   (`hoveredSeries` friendly key + `hoveredSeriesId` stable id), and
+ *   `seriesData` is keyed by the friendly id;
+ * - `time` travels as `timeNs` and is rebuilt server-side as a Deephaven
+ *   timestamp matching the source column type.
+ */
+export interface TvlPressEventPayload {
+  /** Event kind. */
+  type: 'press' | 'doublePress';
+  /**
+   * Time of the data at the event location, in UTC nanoseconds. Mirrors
+   * `MouseEventParams.time`; omitted when the event is outside the data range.
+   */
+  timeNs?: number;
+  /**
+   * IANA timezone the chart is rendering in, so the server can rebuild a
+   * `ZonedDateTime` in the displayed zone. Omitted when unknown.
+   */
+  timeZone?: string;
+  /** Pixel location of the event in the chart. Omitted if outside the chart. */
+  point?: { x: number; y: number };
+  /** Logical index at the event location (`MouseEventParams.logical`). */
+  logical?: number;
+  /** Index of the pane the event occurred in. */
+  paneIndex?: number;
+  /** Friendly id of the hovered series (title / by-key, falling back to the stable id). */
+  hoveredSeries?: string;
+  /** Stable internal id (`series_<n>`) of the hovered series, for server-side lookup. */
+  hoveredSeriesId?: string;
+  /** Data of every series at the event location, keyed by friendly series id. */
+  seriesData: Record<string, TvlWireSeriesData>;
+  shiftKey: boolean;
+  ctrlKey: boolean;
+  metaKey: boolean;
+  altKey: boolean;
+}
+
+/**
+ * Build the wire payload for a press / double-press event from the LWC
+ * MouseEventParams. Pure: no side effects, JSON-safe output.
+ *
+ * @param type        'press' or 'doublePress'
+ * @param params      LWC mouse event params
+ * @param getSeriesId reverse lookup from ISeriesApi to our stable series id
+ * @param getSeriesTitle user-facing title lookup from ISeriesApi
+ * @param timeZone    IANA timezone used to undo the chart's TZ shift on time
+ */
+export function buildPressEventPayload(
+  type: 'press' | 'doublePress',
+  params: MouseEventParams,
+  getSeriesId: (s: ISeriesApi<SeriesType>) => string | undefined,
+  getSeriesTitle: (s: ISeriesApi<SeriesType>) => string | undefined,
+  timeZone: string
+): TvlPressEventPayload {
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  const source = params.sourceEvent as any;
+  const payload: TvlPressEventPayload = {
+    type,
+    seriesData: {},
+    shiftKey: source?.shiftKey ?? false,
+    ctrlKey: source?.ctrlKey ?? false,
+    metaKey: source?.metaKey ?? false,
+    altKey: source?.altKey ?? false,
+  };
+
+  // seriesData: every series' data at the event location, keyed by friendly id.
+  params.seriesData.forEach((dataItem, seriesApi) => {
+    const label = resolveSeriesLabel(seriesApi, getSeriesId, getSeriesTitle);
+    const extracted = extractSeriesPoint(dataItem);
+    if (label == null || extracted == null) return;
+    payload.seriesData[label] =
+      typeof extracted.data === 'number'
+        ? { value: extracted.data }
+        : extracted.data;
+  });
+
+  // Hovered series: LWC's own hit-test result, mapped to our string identity.
+  const hovered = params.hoveredInfo?.series;
+  if (hovered != null) {
+    const label = resolveSeriesLabel(hovered, getSeriesId, getSeriesTitle);
+    const internalId = getSeriesId(hovered);
+    if (label != null) payload.hoveredSeries = label;
+    if (internalId != null) payload.hoveredSeriesId = internalId;
+  }
+
+  if (params.point != null) {
+    payload.point = { x: params.point.x, y: params.point.y };
+  }
+  if (params.logical != null) {
+    payload.logical = params.logical as number;
+  }
+  const paneIndex = params.paneIndex ?? params.hoveredInfo?.paneIndex;
+  if (paneIndex != null) {
+    payload.paneIndex = paneIndex;
+  }
+
+  // Time: the crosshair time at the event. Chart stores TZ-shifted epoch
+  // seconds; undo the shift before sending UTC nanoseconds.
+  const { time } = params;
+  if (time != null && typeof time === 'number') {
+    const utcSec = unconvertTime(time, timeZone);
+    payload.timeNs = Math.round(utcSec * 1e9);
+    if (timeZone) {
+      payload.timeZone = timeZone;
+    }
+  }
+
+  return payload;
+}
+
+function resolveSeriesLabel(
+  series: ISeriesApi<SeriesType>,
+  getSeriesId: (s: ISeriesApi<SeriesType>) => string | undefined,
+  getSeriesTitle: (s: ISeriesApi<SeriesType>) => string | undefined
+): string | undefined {
+  const title = getSeriesTitle(series);
+  if (title != null && title !== '') return title;
+  return getSeriesId(series);
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewPlugin.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewPlugin.ts
new file mode 100644
index 000000000..25cf50b58
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewPlugin.ts
@@ -0,0 +1,17 @@
+import type { WidgetPlugin } from '@deephaven/plugin';
+import { PluginType } from '@deephaven/plugin';
+import type { dh as DhType } from '@deephaven/jsapi-types';
+import { vsGraph } from '@deephaven/icons';
+import TradingViewChart from './TradingViewChart';
+import TradingViewChartPanel from './TradingViewChartPanel';
+
+// eslint-disable-next-line import/prefer-default-export
+export const TradingViewPlugin: WidgetPlugin<DhType.Widget> = {
+  name: '@deephaven/tradingview-lightweight',
+  title: 'TradingView Chart',
+  type: PluginType.WIDGET_PLUGIN,
+  supportedTypes: 'deephaven.plot.tradingview_lightweight.TvlChart',
+  component: TradingViewChart,
+  panelComponent: TradingViewChartPanel,
+  icon: vsGraph,
+};
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewSeriesFocus.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewSeriesFocus.ts
new file mode 100644
index 000000000..8d37d0455
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewSeriesFocus.ts
@@ -0,0 +1,92 @@
+import type {
+  ISeriesApi,
+  MouseEventParams,
+  SeriesType,
+  Time,
+} from 'lightweight-charts';
+
+export interface TvlOhlcPointData {
+  open: number;
+  high: number;
+  low: number;
+  close: number;
+}
+
+export type TvlSeriesPointData = number | TvlOhlcPointData;
+
+export interface ExtractedSeriesPoint {
+  /** JSON-safe point data exposed to event handlers. */
+  data: TvlSeriesPointData;
+  /** Single comparable/display price: value for line-like data, close for OHLC. */
+  price: number;
+  /** Original LWC time for this data item, when present. */
+  time?: Time;
+}
+
+export interface FocusedSeriesPoint extends ExtractedSeriesPoint {
+  series: ISeriesApi<SeriesType>;
+}
+
+/**
+ * Pull comparable point data out of a crosshair data item. Line / Area /
+ * Baseline / Histogram carry ``value``; OHLC carries ``open/high/low/close``
+ * and uses ``close`` as the comparable price.
+ */
+export function extractSeriesPoint(
+  dataItem: unknown
+): ExtractedSeriesPoint | undefined {
+  if (dataItem == null || typeof dataItem !== 'object') return undefined;
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  const item = dataItem as any;
+  const time = item.time as Time | undefined;
+  if (typeof item.value === 'number') {
+    return { data: item.value, price: item.value, time };
+  }
+  if (
+    typeof item.open === 'number' &&
+    typeof item.high === 'number' &&
+    typeof item.low === 'number' &&
+    typeof item.close === 'number'
+  ) {
+    return {
+      data: {
+        open: item.open,
+        high: item.high,
+        low: item.low,
+        close: item.close,
+      },
+      price: item.close,
+      time,
+    };
+  }
+  return undefined;
+}
+
+/**
+ * Within the crosshair's time slice, choose the series whose rendered point is
+ * vertically nearest the cursor. Used by the x-driven tracking tooltip.
+ */
+export function resolveFocusedSeriesPoint(
+  params: MouseEventParams
+): FocusedSeriesPoint | undefined {
+  const { seriesData, point } = params;
+
+  let best: FocusedSeriesPoint | undefined;
+  let bestDist = Infinity;
+  seriesData.forEach((dataItem, series) => {
+    const extracted = extractSeriesPoint(dataItem);
+    if (extracted == null) return;
+    const y =
+      typeof series.priceToCoordinate === 'function'
+        ? series.priceToCoordinate(extracted.price)
+        : null;
+    // No coordinate (e.g. value off-scale): treat distance as 0 so a series
+    // can still resolve, which matters for single-series charts.
+    const dist = y == null || point == null ? 0 : Math.abs(y - point.y);
+    if (dist < bestDist) {
+      bestDist = dist;
+      best = { series, ...extracted };
+    }
+  });
+  return best;
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewTheme.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewTheme.ts
new file mode 100644
index 000000000..e25b0fbcd
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewTheme.ts
@@ -0,0 +1,147 @@
+import { useMemo } from 'react';
+import { useTheme } from '@deephaven/components';
+import { ColorType } from 'lightweight-charts';
+import type { DeepPartial, ChartOptions } from 'lightweight-charts';
+
+/**
+ * Resolved chart theme values from DH CSS variables.
+ */
+export interface TvlChartTheme {
+  paperBgColor: string;
+  plotBgColor: string;
+  textColor: string;
+  gridColor: string;
+  lineColor: string;
+  zeroLineColor: string;
+  crosshairLabelBgColor: string;
+  fontFamily: string;
+  ohlcIncreasing: string;
+  ohlcDecreasing: string;
+  colorway: string[];
+}
+
+/**
+ * Map of DH chart CSS variable names to TvlChartTheme keys.
+ * These are the --dh-color-chart-* variables defined by the DH theme system.
+ */
+const CSS_VAR_MAP: Record<
+  keyof Omit<TvlChartTheme, 'colorway' | 'fontFamily'>,
+  string
+> = {
+  paperBgColor: '--dh-color-chart-bg',
+  plotBgColor: '--dh-color-chart-plot-bg',
+  textColor: '--dh-color-chart-title',
+  gridColor: '--dh-color-chart-grid',
+  lineColor: '--dh-color-chart-axis-line',
+  zeroLineColor: '--dh-color-chart-axis-line-zero',
+  crosshairLabelBgColor: '--dh-color-gray-600',
+  ohlcIncreasing: '--dh-color-chart-ohlc-increase',
+  ohlcDecreasing: '--dh-color-chart-ohlc-decrease',
+};
+
+const COLORWAY_VAR = '--dh-color-chart-colorway';
+
+/**
+ * Resolve all chart CSS variables from the computed styles.
+ */
+function resolveChartTheme(): TvlChartTheme {
+  const style = getComputedStyle(document.documentElement);
+
+  const get = (varName: string): string =>
+    style.getPropertyValue(varName).trim();
+
+  const theme: Record<string, string> = {};
+  Object.entries(CSS_VAR_MAP).forEach(([key, cssVar]) => {
+    theme[key] = get(cssVar);
+  });
+
+  const fontFamily = get('--font-family-sans-serif');
+
+  const colorwayRaw = get(COLORWAY_VAR);
+  const colorway = colorwayRaw
+    ? colorwayRaw.split(/[\s,]+/).filter(Boolean)
+    : [];
+
+  return {
+    ...(theme as Omit<TvlChartTheme, 'colorway' | 'fontFamily'>),
+    fontFamily,
+    colorway,
+  };
+}
+
+/**
+ * Hook that resolves DH chart CSS variables and re-resolves when the
+ * theme changes. Uses the DH ThemeContext (via `useTheme`) to detect
+ * theme switches reliably — the context updates whenever the active
+ * theme changes, which triggers a re-resolve of CSS variables.
+ */
+export function useDHChartTheme(): TvlChartTheme {
+  const { activeThemes } = useTheme();
+
+  return useMemo(() => resolveChartTheme(), [activeThemes]);
+}
+
+/**
+ * Convert a TvlChartTheme to lightweight-charts ChartOptions.
+ */
+export function chartThemeToOptions(
+  theme: TvlChartTheme
+): DeepPartial<ChartOptions> {
+  return {
+    layout: {
+      background: {
+        type: ColorType.Solid,
+        color: theme.paperBgColor || theme.plotBgColor,
+      },
+      textColor: theme.textColor,
+      fontFamily: theme.fontFamily || undefined,
+      panes: {
+        separatorColor: theme.gridColor,
+        separatorHoverColor: theme.lineColor,
+      },
+    },
+    grid: {
+      vertLines: { color: theme.gridColor },
+      horzLines: { color: theme.gridColor },
+    },
+    rightPriceScale: {
+      borderColor: theme.lineColor,
+    },
+    leftPriceScale: {
+      borderColor: theme.lineColor,
+    },
+    timeScale: {
+      borderColor: theme.lineColor,
+    },
+    crosshair: {
+      vertLine: {
+        color: theme.gridColor,
+        labelBackgroundColor: theme.crosshairLabelBgColor,
+      },
+      horzLine: {
+        color: theme.gridColor,
+        labelBackgroundColor: theme.crosshairLabelBgColor,
+      },
+    },
+  };
+}
+
+/**
+ * Get the OHLC colors from the chart theme.
+ */
+export function getOhlcColors(theme: TvlChartTheme): {
+  upColor: string;
+  downColor: string;
+} {
+  return {
+    upColor: theme.ohlcIncreasing,
+    downColor: theme.ohlcDecreasing,
+  };
+}
+
+/**
+ * Get the colorway palette from the chart theme.
+ */
+export function getColorway(theme: TvlChartTheme): string[] {
+  return theme.colorway;
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewTooltip.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewTooltip.ts
new file mode 100644
index 000000000..d0a336288
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewTooltip.ts
@@ -0,0 +1,204 @@
+import type {
+  ISeriesApi,
+  MouseEventParams,
+  SeriesType,
+  Time,
+} from 'lightweight-charts';
+import type { TvlTooltipOptions } from './TradingViewTypes';
+import {
+  resolveFocusedSeriesPoint,
+  type FocusedSeriesPoint,
+} from './TradingViewSeriesFocus';
+
+/** Gap in pixels between the cursor and the tooltip box (from the LWC tutorial). */
+const TOOLTIP_MARGIN = 15;
+
+/**
+ * Dependencies injected into the tooltip so the module stays pure and
+ * testable — it never reaches into the renderer's internals directly.
+ */
+export interface TradingViewTooltipDeps {
+  /** Chart container the tooltip is positioned within and appended to. */
+  container: HTMLElement;
+  /** Reverse lookup from an ISeriesApi to our stable series id. */
+  getSeriesId: (series: ISeriesApi<SeriesType>) => string | undefined;
+  /** Resolved primary color for a series id (used to tint the title line). */
+  getSeriesColor: (id: string) => string | undefined;
+  /** Format a crosshair time the same way the chart's time axis does. */
+  formatTime: (time: Time) => string;
+  /** Tooltip options as emitted by the Python API. */
+  options: TvlTooltipOptions;
+}
+
+/**
+ * Tracking tooltip: a cursor-following overlay that displays a single focused
+ * series. In a multi-series chart the focused series is whichever line's value
+ * is vertically nearest the cursor within the hovered time slice, so moving the
+ * cursor up and down switches between overlaid series. Colors come from the
+ * active Deephaven theme (via CSS), with the title tinted by the series color.
+ */
+export class TradingViewTooltip {
+  private deps: TradingViewTooltipDeps;
+
+  private el: HTMLDivElement;
+
+  private titleEl: HTMLDivElement;
+
+  private valueEl: HTMLDivElement;
+
+  private dateEl: HTMLDivElement;
+
+  constructor(deps: TradingViewTooltipDeps) {
+    this.deps = deps;
+
+    const doc = deps.container.ownerDocument;
+    this.el = doc.createElement('div');
+    this.el.className = 'tvl-tooltip';
+    this.el.style.display = 'none';
+
+    this.titleEl = doc.createElement('div');
+    this.titleEl.className = 'tvl-tooltip-title';
+    this.valueEl = doc.createElement('div');
+    this.valueEl.className = 'tvl-tooltip-value';
+    this.dateEl = doc.createElement('div');
+    this.dateEl.className = 'tvl-tooltip-date';
+
+    // Default-on: a line is shown unless the option explicitly disables it.
+    const { showTitle, showValue, showDate } = deps.options;
+    if (showTitle === false) this.titleEl.style.display = 'none';
+    if (showValue === false) this.valueEl.style.display = 'none';
+    if (showDate === false) this.dateEl.style.display = 'none';
+
+    this.el.appendChild(this.titleEl);
+    this.el.appendChild(this.valueEl);
+    this.el.appendChild(this.dateEl);
+    deps.container.appendChild(this.el);
+  }
+
+  /**
+   * Crosshair-move handler. Hides the tooltip when the cursor leaves the
+   * chart or there is nothing to show; otherwise renders the focused series
+   * and positions the box near the cursor, clamped to the container.
+   */
+  handleCrosshairMove(params: MouseEventParams): void {
+    const { container } = this.deps;
+    const { point } = params;
+    if (
+      point == null ||
+      params.time == null ||
+      point.x < 0 ||
+      point.x > container.clientWidth ||
+      point.y < 0 ||
+      point.y > container.clientHeight
+    ) {
+      this.hide();
+      return;
+    }
+
+    const focused = resolveFocusedSeriesPoint(params);
+    if (focused == null) {
+      this.hide();
+      return;
+    }
+
+    this.render(focused, params.time);
+    this.position(point.x, point.y);
+  }
+
+  /** Remove the tooltip element from the DOM. */
+  destroy(): void {
+    this.el.remove();
+  }
+
+  private hide(): void {
+    this.el.style.display = 'none';
+  }
+
+  private render(focused: FocusedSeriesPoint, time: Time): void {
+    const { getSeriesId, getSeriesColor, formatTime, options } = this.deps;
+    const { series, price } = focused;
+    const id = getSeriesId(series);
+
+    if (options.showTitle !== false) {
+      // ISeriesApi.options().title is set from the Python `title=`; fall back
+      // to the series id when untitled so the line is never empty.
+      const opts = series.options() as { title?: string };
+      const seriesTitle = opts?.title;
+      let title = '';
+      if (seriesTitle != null && seriesTitle !== '') {
+        title = seriesTitle;
+      } else if (id != null) {
+        title = id;
+      }
+      this.titleEl.textContent = title;
+      const color = id != null ? getSeriesColor(id) : undefined;
+      // Empty string clears any prior inline color → falls back to CSS theme.
+      this.titleEl.style.color = color ?? '';
+    }
+
+    if (options.showValue !== false) {
+      this.valueEl.textContent = this.formatValue(series, price);
+    }
+
+    if (options.showDate !== false) {
+      this.dateEl.textContent = formatTime(time);
+    }
+
+    this.el.style.display = 'block';
+    // Test seam: expose the rendered text so Playwright can assert content
+    // without screenshotting the canvas (matches data-tvl-last-event).
+    this.el.setAttribute(
+      'data-tvl-tooltip',
+      [
+        this.titleEl.textContent,
+        this.valueEl.textContent,
+        this.dateEl.textContent,
+      ]
+        .filter(t => t != null && t !== '')
+        .join(' | ')
+    );
+  }
+
+  /**
+   * Format the value line: an explicit ``valuePrecision`` wins; otherwise use
+   * the series' own price formatter so the tooltip matches the price axis.
+   */
+  private formatValue(series: ISeriesApi<SeriesType>, value: number): string {
+    const { valuePrecision } = this.deps.options;
+    if (valuePrecision != null) {
+      return value.toFixed(valuePrecision);
+    }
+    try {
+      return series.priceFormatter().format(value);
+    } catch {
+      return String(value);
+    }
+  }
+
+  /**
+   * Place the box near the cursor with a margin, flipping to the other side
+   * of the cursor when it would overflow the container (LWC tutorial logic).
+   */
+  private position(x: number, y: number): void {
+    const { container } = this.deps;
+    const width = this.el.offsetWidth;
+    const height = this.el.offsetHeight;
+
+    let left = x + TOOLTIP_MARGIN;
+    if (left > container.clientWidth - width) {
+      left = x - TOOLTIP_MARGIN - width;
+    }
+    if (left < 0) left = 0;
+
+    let top = y + TOOLTIP_MARGIN;
+    if (top > container.clientHeight - height) {
+      top = y - height - TOOLTIP_MARGIN;
+    }
+    if (top < 0) top = 0;
+
+    this.el.style.left = `${left}px`;
+    this.el.style.top = `${top}px`;
+  }
+}
+
+export default TradingViewTooltip;
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewTypes.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewTypes.ts
new file mode 100644
index 000000000..77deba657
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewTypes.ts
@@ -0,0 +1,200 @@
+import type { dh as DhType } from '@deephaven/jsapi-types';
+
+// Message types from Python
+export interface NewFigureMessage {
+  type: 'NEW_FIGURE';
+  figure: TvlFigureData;
+  revision: number;
+  new_references: number[];
+  removed_references: number[];
+}
+
+export type TvlChartType = 'standard' | 'yieldCurve' | 'options';
+
+/**
+ * Per-series partition template. Each series with `by=` on the Python
+ * side gets one of these. The JS partition-watcher uses the series'
+ * own `dataMapping.columns`, `options`, `type`, `paneIndex`, and
+ * `priceScaleOptions` as the template — only `byColumn` and `refIndex`
+ * are unique to the partition block.
+ */
+export interface TvlSeriesPartition {
+  /** Column name used for partitioning. */
+  byColumn: string;
+  /** Index into the exported references for this series' PartitionedTable.
+   *  Patched in by the Python listener at serialize time. */
+  refIndex?: number;
+}
+
+/** Per-table metadata for JS-side downsampling via runChartDownsample. */
+export interface TvlDownsampleMeta {
+  tableSize: number;
+  timeCol: string;
+  valueCols: string[];
+  seriesTypes: string[];
+}
+
+/** Per-source-table metadata for server-side auto-bin aggregation. */
+export interface TvlAutoBinMeta {
+  /** Time column name on the source table. */
+  timeCol: string;
+  /** Current aggregation bin width in nanoseconds. */
+  binWidthNs: number;
+  /** [minNs, maxNs] full extent of the raw source table. */
+  fullRangeNs: [number, number];
+  /** Target bin count used to compute the initial bin width. */
+  targetBins: number;
+  /** Per-series aggregation spec. Keyed by series id. */
+  series: Record<
+    string,
+    {
+      type: 'Histogram' | 'Candlestick' | 'Bar';
+      agg: 'sum' | 'count' | 'avg' | 'last' | 'ohlc';
+      valueCols: string[];
+    }
+  >;
+}
+
+/** Server response to AUTOBIN_ZOOM / AUTOBIN_RESET. */
+export interface AutoBinFigureMessage {
+  type: 'AUTOBIN_FIGURE';
+  revision: number;
+  /** Source-table ref the zoom request was for. */
+  tableRef: number;
+  /** New bin width in nanoseconds for that table. */
+  binWidthNs: number;
+  /** Updated full autoBinMeta map. */
+  autoBinMeta: Record<string, TvlAutoBinMeta>;
+  /** New reference list (parallels NEW_FIGURE). Empty when noop is true. */
+  new_references: number[];
+  /** True when the server determined no re-aggregation was needed. */
+  noop?: boolean;
+}
+
+export interface TvlFigureData {
+  chartType?: TvlChartType;
+  chartOptions: Record<string, unknown>;
+  series: TvlSeriesConfig[];
+  paneStretchFactors?: number[];
+  deephaven: {
+    mappings: TvlDataMapping[];
+  };
+  /** Present when tables are eligible for JS-side downsampling. Keyed by table ref ID. */
+  downsampleMeta?: Record<string, TvlDownsampleMeta>;
+  /** Present when source tables are server-side auto-binned. Keyed by source-table ref ID. */
+  autoBinMeta?: Record<string, TvlAutoBinMeta>;
+  /** Handler ids wired on the Python side (subset of ["press","doublePress"]). */
+  enabledHandlers?: string[];
+}
+
+/**
+ * Tracking-tooltip options, emitted by the Python API as
+ * ``chartOptions.tooltip``. The tooltip is a cursor-following overlay that
+ * shows a single focused series' title, value, and time. Colors are derived
+ * entirely from the active Deephaven theme (plus the focused series' own
+ * color for the title), so there are no color fields here.
+ */
+export interface TvlTooltipOptions {
+  /** Master switch. The block is only emitted when this is true. */
+  visible?: boolean;
+  /** Show the series title line (tinted with the series color). Default true. */
+  showTitle?: boolean;
+  /** Show the value line. Default true. */
+  showValue?: boolean;
+  /** Show the date/time line. Default true. */
+  showDate?: boolean;
+  /** Override decimal places for the value; unset = use the series price format. */
+  valuePrecision?: number;
+}
+
+export interface TvlSeriesConfig {
+  id: string;
+  type: 'Candlestick' | 'Bar' | 'Line' | 'Area' | 'Baseline' | 'Histogram';
+  options: Record<string, unknown>;
+  dataMapping: {
+    tableId: number;
+    columns: Record<string, string>; // e.g. { time: "Timestamp", open: "Open", ... }
+  };
+  markers?: TvlMarkerData[];
+  markerSpec?: TvlMarkerSpec;
+  priceLines?: TvlPriceLineData[];
+  priceScaleOptions?: Record<string, unknown>;
+  paneIndex?: number;
+  /** Set when the series is a partition template (Python-side `by=`).
+   *  The JS partition-watcher creates one runtime series per partition
+   *  key using this series' options/dataMapping/type/paneIndex as the
+   *  template. The series itself is NOT rendered directly. */
+  partition?: TvlSeriesPartition;
+}
+
+export interface TvlDataMapping {
+  table: number;
+  dataColumns: Record<string, string[]>; // column name -> series field paths
+}
+
+export interface TvlMarkerData {
+  time: string | number;
+  position:
+    | 'aboveBar'
+    | 'belowBar'
+    | 'inBar'
+    | 'atPriceTop'
+    | 'atPriceBottom'
+    | 'atPriceMiddle';
+  shape: 'circle' | 'square' | 'arrowUp' | 'arrowDown';
+  color?: string;
+  text: string;
+  size?: number;
+  /** Required when position is atPriceTop / atPriceBottom / atPriceMiddle. */
+  price?: number;
+}
+
+export interface TvlMarkerSpec {
+  tableId: number;
+  /** Column names for per-row marker properties. `time` is always present. */
+  columns: Record<string, string>;
+  /** Fixed defaults for properties not sourced from columns. */
+  defaults: {
+    position?: 'aboveBar' | 'belowBar' | 'inBar';
+    shape?: 'circle' | 'square' | 'arrowUp' | 'arrowDown';
+    color?: string;
+    text?: string;
+    size?: number;
+  };
+}
+
+export interface TvlPriceLineData {
+  /** Static price value. Mutually exclusive with `column`. */
+  price?: number;
+  /** Column name whose last-row value drives the price line dynamically. */
+  column?: string;
+  color?: string;
+  lineWidth?: number;
+  lineStyle?: number;
+  axisLabelVisible?: boolean;
+  title?: string;
+}
+
+// Model events
+export type ModelEvent =
+  | { type: 'FIGURE_UPDATED'; figure: TvlFigureData; tables: DhType.Table[] }
+  | {
+      type: 'DATA_UPDATED';
+      tableId: number;
+      isInitialLoad: boolean;
+      /** Number of rows added */
+      addedCount: number;
+      /** Number of rows removed */
+      removedCount: number;
+      /** Number of rows modified */
+      modifiedCount: number;
+      /** True when this update follows a RESET (double-click). */
+      isResetView?: boolean;
+      /** True when this is the first data from a fresh downsample (not a tick). */
+      isDownsampleSwap?: boolean;
+    }
+  | { type: 'ERROR'; message: string }
+  | { type: 'DOWNSAMPLE_PENDING'; pending: boolean }
+  | { type: 'DISCONNECTED'; connected: boolean };
+
+export type ModelEventListener = (event: ModelEvent) => void;
diff --git a/plugins/tradingview-lightweight/src/js/src/TradingViewUtils.ts b/plugins/tradingview-lightweight/src/js/src/TradingViewUtils.ts
new file mode 100644
index 000000000..803b75e87
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/TradingViewUtils.ts
@@ -0,0 +1,410 @@
+import type {
+  TvlChartType,
+  TvlMarkerData,
+  TvlMarkerSpec,
+  TvlSeriesConfig,
+} from './TradingViewTypes';
+import { resolveColor } from './TradingViewColors';
+
+/**
+ * Cache of resolved theme-color strings keyed by their raw input.
+ * `color_column` rows typically repeat a small handful of distinct values
+ * (e.g. "positive"/"negative") across thousands of rows; caching avoids
+ * calling `getComputedStyle` once per row.
+ */
+const rowColorCache = new Map<string, string | undefined>();
+function resolveRowColor(value: unknown): unknown {
+  if (typeof value !== 'string' || value === '') return value;
+  let cached = rowColorCache.get(value);
+  if (cached === undefined && !rowColorCache.has(value)) {
+    cached = resolveColor(value);
+    rowColorCache.set(value, cached);
+  }
+  return cached ?? value;
+}
+
+/**
+ * Cache of Intl.DateTimeFormat instances keyed by timezone string.
+ * Avoids re-constructing the formatter on every convertTime call.
+ * The options are always identical; only the timezone varies.
+ */
+const formatterCache = new Map<string, Intl.DateTimeFormat>();
+
+/**
+ * Convert Deephaven table column data into lightweight-charts data points.
+ *
+ * For OHLC series: [{time, open, high, low, close}, ...]
+ * For value series: [{time, value}, ...]
+ *
+ * Time column values are expected to be pre-converted by the model's
+ * timeTranslator (TZ-adjusted epoch seconds for standard charts, raw
+ * numbers for yieldCurve/options). No convertTime call is needed here.
+ *
+ * @param startIndex Optional index to start processing from. Used for
+ *   append-only ticking updates to avoid re-processing old rows.
+ */
+export function transformTableData(
+  seriesConfig: TvlSeriesConfig,
+  columnData: Map<string, unknown[]>,
+  chartType?: TvlChartType,
+  startIndex = 0
+): unknown[] {
+  const { columns } = seriesConfig.dataMapping;
+  const timeColumn = columnData.get(columns.time);
+  if (!timeColumn) return [];
+
+  const isNumericScale = chartType === 'yieldCurve' || chartType === 'options';
+  const { length } = timeColumn;
+  const result: unknown[] = [];
+  const effectiveStart = Math.max(0, startIndex);
+
+  for (let i = effectiveStart; i < length; i += 1) {
+    // Time values are already converted by the model's translator:
+    // - Standard charts: TZ-adjusted epoch seconds (number)
+    // - Numeric scales: raw x-axis values (number)
+    const rawTime = timeColumn[i];
+
+    // Skip non-finite times (null/undefined/string/NaN/Infinity). A point
+    // with NaN time was previously kept and confused lightweight-charts;
+    // a point with an unparseable time was previously kept at i=0 with
+    // time=0, which made the chart draw a line from epoch (1970) to the
+    // first real point — visible as a near-vertical "spike" entering the
+    // chart from the left edge when zoomed to recent data.
+    if (typeof rawTime !== 'number' || !Number.isFinite(rawTime)) {
+      // eslint-disable-next-line no-continue
+      continue;
+    }
+    const timeVal = Math.floor(rawTime);
+
+    // For standard (time-based) charts, time=0 is essentially always a
+    // sentinel for missing data — Instant columns don't represent epoch.
+    // Skip at every index (including i=0) to avoid the same left-edge
+    // spike as above. Numeric scales (yieldCurve, options) treat 0 as a
+    // valid x-axis value and don't apply this filter.
+    if (!isNumericScale && timeVal === 0) {
+      // eslint-disable-next-line no-continue
+      continue;
+    }
+    const point: Record<string, unknown> = {
+      time: timeVal,
+    };
+
+    // Map each non-time column
+    Object.entries(columns).forEach(([field, colName]) => {
+      if (field === 'time') return;
+      const data = columnData.get(colName);
+      if (data != null) {
+        const raw =
+          typeof data[i] === 'object' && data[i] !== null
+            ? Number(data[i])
+            : data[i];
+        // `color` rows can carry DH theme names ("positive") or
+        // `var(--dh-color-...)` expressions — resolve them to canvas-paintable
+        // CSS so lightweight-charts paints theme colors per-row, not the
+        // literal token. Cached so the hot path stays cheap.
+        point[field] = field === 'color' ? resolveRowColor(raw) : raw;
+      }
+    });
+
+    result.push(point);
+  }
+
+  return result;
+}
+
+/**
+ * Convert a time value to lightweight-charts UTCTimestamp (integer seconds).
+ *
+ * Lightweight-charts has no timezone support — it renders timestamps as-is.
+ * To make the axis labels match the user's Deephaven timezone setting, we
+ * shift the UTC timestamp by the timezone offset. This is the standard
+ * approach recommended by the TradingView community.
+ *
+ * @param value The time value (millis, nanos, Date, or string)
+ * @param timeZone The IANA timezone string from user settings (e.g. "America/New_York").
+ *   Falls back to the browser's local timezone if not provided.
+ */
+export function convertTime(value: unknown, timeZone?: string): number {
+  let utcSeconds: number;
+  if (typeof value === 'number') {
+    if (value > 1e15) {
+      utcSeconds = Math.floor(value / 1e9);
+    } else if (value > 1e12) {
+      utcSeconds = Math.floor(value / 1e3);
+    } else {
+      utcSeconds = Math.floor(value);
+    }
+  } else if (value instanceof Date) {
+    utcSeconds = Math.floor(value.getTime() / 1000);
+  } else if (typeof value === 'string') {
+    const ms = new Date(value).getTime();
+    if (Number.isNaN(ms)) return 0;
+    utcSeconds = Math.floor(ms / 1000);
+  } else {
+    return 0;
+  }
+
+  // Shift by the user's timezone offset so axis labels display in their
+  // configured timezone. Uses Intl API to resolve the offset for the
+  // specific instant (handles DST correctly).
+  const offsetSeconds = getTimezoneOffsetSeconds(utcSeconds * 1000, timeZone);
+  return utcSeconds + offsetSeconds;
+}
+
+/**
+ * Reverse the TZ shift applied by convertTime. Given a TZ-shifted epoch
+ * seconds value (as stored in the chart's data and returned by
+ * getVisibleRange), return the real UTC epoch seconds.
+ *
+ * convertTime does: realUTC + offset → tzShifted
+ * unconvertTime does: tzShifted - offset → realUTC
+ *
+ * Uses the shifted value as an approximation for the offset lookup, which
+ * is correct except at DST boundaries (where the error is ≤1 hour).
+ */
+export function unconvertTime(
+  tzShiftedSeconds: number,
+  timeZone?: string
+): number {
+  if (
+    timeZone == null ||
+    timeZone === '' ||
+    timeZone === 'UTC' ||
+    timeZone === 'Etc/UTC'
+  ) {
+    return tzShiftedSeconds;
+  }
+  // Use the shifted value as an approximation to compute the offset
+  const offsetSeconds = getTimezoneOffsetSeconds(
+    tzShiftedSeconds * 1000,
+    timeZone
+  );
+  return tzShiftedSeconds - offsetSeconds;
+}
+
+/**
+ * Get the timezone offset in seconds for a given instant and timezone.
+ * Positive = east of UTC (e.g. +9 for Tokyo), negative = west (e.g. -5 for NY).
+ */
+function getTimezoneOffsetSeconds(epochMs: number, timeZone?: string): number {
+  if (timeZone == null || timeZone === '') {
+    // Fall back to browser local timezone
+    return -(new Date(epochMs).getTimezoneOffset() * 60);
+  }
+  // Use Intl.DateTimeFormat to compute the offset for the given timezone.
+  // The formatter is cached per timezone — only formatToParts varies per instant.
+  const utcDate = new Date(epochMs);
+  let formatter = formatterCache.get(timeZone);
+  if (formatter == null) {
+    formatter = new Intl.DateTimeFormat('en-US', {
+      timeZone,
+      year: 'numeric',
+      month: '2-digit',
+      day: '2-digit',
+      hour: '2-digit',
+      minute: '2-digit',
+      second: '2-digit',
+      hour12: false,
+    });
+    formatterCache.set(timeZone, formatter);
+  }
+  const parts = formatter.formatToParts(utcDate);
+  const get = (type: string) =>
+    Number(parts.find(p => p.type === type)?.value ?? 0);
+  const localDate = new Date(
+    Date.UTC(
+      get('year'),
+      get('month') - 1,
+      get('day'),
+      get('hour'),
+      get('minute'),
+      get('second')
+    )
+  );
+  return Math.round((localDate.getTime() - utcDate.getTime()) / 1000);
+}
+
+/**
+ * Deduplicate data points by time, keeping the last value for each time.
+ * Lightweight-charts requires strictly ascending unique time values for setData().
+ * For sub-second ticking data where multiple rows share the same second,
+ * we keep only the most recent value per second.
+ */
+export function deduplicateByTime(
+  data: Record<string, unknown>[]
+): Record<string, unknown>[] {
+  if (data.length === 0) return data;
+
+  const seen = new Map<unknown, number>();
+  for (let i = 0; i < data.length; i += 1) {
+    seen.set(data[i].time, i);
+  }
+
+  // If no duplicates, return as-is
+  if (seen.size === data.length) return data;
+
+  // Build deduplicated array keeping last occurrence of each time
+  const result: Record<string, unknown>[] = [];
+  const usedIndices = new Set(seen.values());
+  for (let i = 0; i < data.length; i += 1) {
+    if (usedIndices.has(i)) {
+      result.push(data[i]);
+    }
+  }
+  return result;
+}
+
+/**
+ * Get the column names needed for a series subscription.
+ */
+export function getRequiredColumns(seriesConfig: TvlSeriesConfig): string[] {
+  return Object.values(seriesConfig.dataMapping.columns);
+}
+
+/**
+ * Get all unique column names across all series for a given table.
+ */
+export function getAllColumnsForTable(
+  series: TvlSeriesConfig[],
+  tableId: number
+): string[] {
+  const columns = new Set<string>();
+  series.forEach(s => {
+    // Series data columns
+    if (s.dataMapping.tableId === tableId) {
+      Object.values(s.dataMapping.columns).forEach(colName => {
+        columns.add(colName);
+      });
+      // Include columns referenced by dynamic price lines
+      s.priceLines?.forEach(pl => {
+        if (pl.column) {
+          columns.add(pl.column);
+        }
+      });
+    }
+    // Marker spec columns (may reference a different table)
+    if (s.markerSpec?.tableId === tableId) {
+      Object.values(s.markerSpec.columns).forEach(colName => {
+        columns.add(colName);
+      });
+    }
+  });
+  return Array.from(columns);
+}
+
+/**
+ * Mapping from Python-friendly position names to camelCase.
+ */
+const POSITION_MAP: Record<string, TvlMarkerData['position']> = {
+  above_bar: 'aboveBar',
+  below_bar: 'belowBar',
+  in_bar: 'inBar',
+  at_price_top: 'atPriceTop',
+  at_price_bottom: 'atPriceBottom',
+  at_price_middle: 'atPriceMiddle',
+  aboveBar: 'aboveBar',
+  belowBar: 'belowBar',
+  inBar: 'inBar',
+  atPriceTop: 'atPriceTop',
+  atPriceBottom: 'atPriceBottom',
+  atPriceMiddle: 'atPriceMiddle',
+};
+
+/**
+ * Mapping from Python-friendly shape names to camelCase.
+ */
+const SHAPE_MAP: Record<string, TvlMarkerData['shape']> = {
+  circle: 'circle',
+  square: 'square',
+  arrow_up: 'arrowUp',
+  arrow_down: 'arrowDown',
+  arrowUp: 'arrowUp',
+  arrowDown: 'arrowDown',
+};
+
+/**
+ * Resolve a marker property from a column value or a default.
+ */
+function resolveMarkerField(
+  spec: TvlMarkerSpec,
+  field: string,
+  columnData: Map<string, unknown[]>,
+  rowIndex: number
+): unknown {
+  const colName = spec.columns[field];
+  if (colName) {
+    const data = columnData.get(colName);
+    const val = data?.[rowIndex];
+    return val ?? (spec.defaults as Record<string, unknown>)[field];
+  }
+  return (spec.defaults as Record<string, unknown>)[field];
+}
+
+/**
+ * Build TvlMarkerData[] from a marker table's column data.
+ * Each row in the marker table produces one marker.
+ *
+ * Time column values are expected to be pre-converted by the model's
+ * timeTranslator (same as transformTableData).
+ */
+export function buildMarkersFromTableData(
+  markerSpec: TvlMarkerSpec,
+  columnData: Map<string, unknown[]>,
+  chartType?: TvlChartType,
+  defaultColor?: string
+): TvlMarkerData[] {
+  const timeColName = markerSpec.columns.time;
+  const timeCol = columnData.get(timeColName);
+  if (!timeCol) return [];
+
+  const isNumericScale = chartType === 'yieldCurve' || chartType === 'options';
+  const markers: TvlMarkerData[] = [];
+
+  for (let i = 0; i < timeCol.length; i += 1) {
+    // Time values are already converted by the model's translator
+    const timeVal =
+      typeof timeCol[i] === 'number' ? Math.floor(timeCol[i] as number) : 0;
+
+    // Skip invalid times
+    if (!isNumericScale && timeVal === 0 && i > 0) {
+      // eslint-disable-next-line no-continue
+      continue;
+    }
+
+    const rawPosition = resolveMarkerField(
+      markerSpec,
+      'position',
+      columnData,
+      i
+    ) as string;
+    const rawShape = resolveMarkerField(
+      markerSpec,
+      'shape',
+      columnData,
+      i
+    ) as string;
+    const color = (resolveMarkerField(markerSpec, 'color', columnData, i) ??
+      defaultColor) as string | undefined;
+    const text = (resolveMarkerField(markerSpec, 'text', columnData, i) ??
+      '') as string;
+    const size = resolveMarkerField(markerSpec, 'size', columnData, i) as
+      | number
+      | undefined;
+
+    const position = POSITION_MAP[rawPosition] ?? 'aboveBar';
+    const shape = SHAPE_MAP[rawShape] ?? 'circle';
+
+    markers.push({
+      time: timeVal,
+      position,
+      shape,
+      ...(color != null ? { color } : {}),
+      text,
+      ...(size != null ? { size: Number(size) } : {}),
+    });
+  }
+
+  // lightweight-charts requires markers sorted by time ascending
+  markers.sort((a, b) => (a.time as number) - (b.time as number));
+  return markers;
+}
diff --git a/plugins/tradingview-lightweight/src/js/src/__mocks__/lightweight-charts.js b/plugins/tradingview-lightweight/src/js/src/__mocks__/lightweight-charts.js
new file mode 100644
index 000000000..2efddc4fb
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__mocks__/lightweight-charts.js
@@ -0,0 +1,98 @@
+// Manual mock for lightweight-charts module
+const mockPriceScale = {
+  applyOptions: jest.fn(),
+};
+
+const mockPriceLine = {
+  applyOptions: jest.fn(),
+  options: jest.fn(() => ({ price: 0 })),
+};
+
+const mockSeriesInstance = {
+  setData: jest.fn(),
+  createPriceLine: jest.fn(() => mockPriceLine),
+  priceScale: jest.fn(() => mockPriceScale),
+  options: jest.fn(() => ({})),
+  priceFormatter: jest.fn(() => ({ format: v => String(v) })),
+  priceToCoordinate: jest.fn(() => null),
+};
+
+const mockMarkersPlugin = {
+  setMarkers: jest.fn(),
+  markers: jest.fn(() => []),
+};
+
+const mockWatermarkPlugin = {
+  applyOptions: jest.fn(),
+  detach: jest.fn(),
+};
+
+const mockPane = {
+  setStretchFactor: jest.fn(),
+  getStretchFactor: jest.fn(() => 1),
+};
+
+const mockPane2 = {
+  setStretchFactor: jest.fn(),
+  getStretchFactor: jest.fn(() => 1),
+};
+
+const mockTimeScale = {
+  fitContent: jest.fn(),
+};
+
+const mockChart = {
+  addSeries: jest.fn(() => mockSeriesInstance),
+  removeSeries: jest.fn(),
+  applyOptions: jest.fn(),
+  resize: jest.fn(),
+  remove: jest.fn(),
+  timeScale: jest.fn(() => mockTimeScale),
+  panes: jest.fn(() => [mockPane, mockPane2]),
+  subscribeClick: jest.fn(),
+  unsubscribeClick: jest.fn(),
+  subscribeDblClick: jest.fn(),
+  unsubscribeDblClick: jest.fn(),
+  subscribeCrosshairMove: jest.fn(),
+  unsubscribeCrosshairMove: jest.fn(),
+};
+
+const createChart = jest.fn(() => mockChart);
+const createYieldCurveChart = jest.fn(() => mockChart);
+const createOptionsChart = jest.fn(() => mockChart);
+const createSeriesMarkers = jest.fn(() => mockMarkersPlugin);
+const createTextWatermark = jest.fn(() => mockWatermarkPlugin);
+
+const ColorType = { Solid: 'solid' };
+
+// Series definition constants
+const CandlestickSeries = 'CandlestickSeries';
+const BarSeries = 'BarSeries';
+const LineSeries = 'LineSeries';
+const AreaSeries = 'AreaSeries';
+const BaselineSeries = 'BaselineSeries';
+const HistogramSeries = 'HistogramSeries';
+
+module.exports = {
+  createChart,
+  createYieldCurveChart,
+  createOptionsChart,
+  createSeriesMarkers,
+  createTextWatermark,
+  ColorType,
+  CandlestickSeries,
+  BarSeries,
+  LineSeries,
+  AreaSeries,
+  BaselineSeries,
+  HistogramSeries,
+  __mockChart: mockChart,
+  __mockSeriesInstance: mockSeriesInstance,
+  __mockPriceLine: mockPriceLine,
+  __mockPriceScale: mockPriceScale,
+  __mockMarkersPlugin: mockMarkersPlugin,
+  __mockWatermarkPlugin: mockWatermarkPlugin,
+  __mockPane: mockPane,
+  __mockPane2: mockPane2,
+  __mockTimeScale: mockTimeScale,
+};
diff --git a/plugins/tradingview-lightweight/src/js/src/__mocks__/styleMock.js b/plugins/tradingview-lightweight/src/js/src/__mocks__/styleMock.js
new file mode 100644
index 000000000..38b08af1d
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__mocks__/styleMock.js
@@ -0,0 +1 @@
+module.exports = "";
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChart.interaction.test.tsx b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChart.interaction.test.tsx
new file mode 100644
index 000000000..109bd03d0
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChart.interaction.test.tsx
@@ -0,0 +1,338 @@
+import React from 'react';
+import { act, render } from '@testing-library/react';
+import TradingViewChart from '../TradingViewChart';
+
+const mockFigure = {
+  chartType: 'standard',
+  chartOptions: {},
+  series: [
+    {
+      id: 's0',
+      type: 'Area',
+      options: {},
+      dataMapping: {
+        tableId: 0,
+        columns: { time: 'Timestamp', value: 'Value' },
+      },
+    },
+  ],
+  deephaven: { mappings: [] },
+  downsampleMeta: {
+    0: {
+      tableSize: 10_000,
+      timeCol: 'Timestamp',
+      valueCols: ['Value'],
+      seriesTypes: ['Area'],
+    },
+  },
+};
+
+const mockColumnData = new Map<string, unknown[]>([
+  ['Timestamp', [0, 50, 100, 101]],
+  ['Value', [10, 11, 12, 13]],
+]);
+
+let mockVisibleRange = { from: 0, to: 100 };
+const mockVisibleRangeHandlers: Array<() => void> = [];
+const mockSizeHandlers: Array<() => void> = [];
+const mockModelInstances: unknown[] = [];
+const mockRendererInstances: unknown[] = [];
+const mockDh = {};
+const mockChartTheme = {
+  paperBgColor: '#111',
+  plotBgColor: '#111',
+  textColor: '#eee',
+  gridColor: '#333',
+  lineColor: '#555',
+  zeroLineColor: '#777',
+  crosshairLabelBgColor: '#444',
+  fontFamily: 'sans-serif',
+  ohlcIncreasing: '#0a0',
+  ohlcDecreasing: '#a00',
+  colorway: ['#48a', '#f81'],
+};
+
+const mockTimeScale = {
+  getVisibleRange: jest.fn(() => mockVisibleRange),
+  setVisibleRange: jest.fn(range => {
+    mockVisibleRange = range;
+  }),
+  width: jest.fn(() => 1000),
+};
+
+const mockChart = {
+  timeScale: jest.fn(() => mockTimeScale),
+  applyOptions: jest.fn(),
+};
+
+jest.mock('react-redux', () => ({
+  useSelector: jest.fn(() => 'UTC'),
+}));
+
+jest.mock('@deephaven/redux', () => ({
+  getTimeZone: jest.fn(),
+}));
+
+jest.mock('@deephaven/jsapi-bootstrap', () => ({
+  useApi: jest.fn(() => mockDh),
+}));
+
+jest.mock('../TradingViewTheme', () => ({
+  useDHChartTheme: jest.fn(() => mockChartTheme),
+  chartThemeToOptions: jest.fn(() => ({})),
+  getColorway: jest.fn(() => ['#48a']),
+  getOhlcColors: jest.fn(() => ({
+    upColor: '#0a0',
+    downColor: '#a00',
+    borderUpColor: '#0a0',
+    borderDownColor: '#a00',
+    wickUpColor: '#0a0',
+    wickDownColor: '#a00',
+  })),
+}));
+
+jest.mock('../TradingViewChartRenderer', () => {
+  class MockRenderer {
+    setChartType = jest.fn();
+
+    applyOptions = jest.fn();
+
+    configureSeries = jest.fn();
+
+    applyPaneStretchFactors = jest.fn();
+
+    getChartType = jest.fn(() => 'standard');
+
+    getChart = jest.fn(() => mockChart);
+
+    setSeriesData = jest.fn();
+
+    updateSeriesPoint = jest.fn();
+
+    setSeriesMarkers = jest.fn();
+
+    updateDynamicPriceLines = jest.fn();
+
+    isScaffoldEnabled = jest.fn(() => false);
+
+    setScaffoldData = jest.fn();
+
+    fitContent = jest.fn();
+
+    getTimeScaleWidth = jest.fn(() => mockTimeScale.width());
+
+    resetPriceScales = jest.fn();
+
+    subscribeVisibleLogicalRangeChange = jest.fn(handler => {
+      mockVisibleRangeHandlers.push(handler);
+      return () => undefined;
+    });
+
+    subscribeSizeChange = jest.fn(handler => {
+      mockSizeHandlers.push(handler);
+      return () => undefined;
+    });
+
+    subscribeClick = jest.fn(() => () => undefined);
+
+    subscribeDblClick = jest.fn(() => () => undefined);
+
+    hasTooltip = jest.fn(() => false);
+
+    setupTooltip = jest.fn(() => () => undefined);
+
+    resize = jest.fn();
+
+    dispose = jest.fn();
+
+    getTextColor = jest.fn(() => '#eee');
+
+    timeToCoordinate = jest.fn(() => null);
+
+    priceToCoordinate = jest.fn(() => null);
+
+    getSeriesIds = jest.fn(() => ['s0']);
+
+    constructor() {
+      mockRendererInstances.push(this);
+    }
+  }
+
+  return {
+    __esModule: true,
+    default: MockRenderer,
+  };
+});
+
+jest.mock('../TradingViewChartModel', () => ({
+  __esModule: true,
+  default: jest.fn().mockImplementation(() => {
+    const listeners: Array<(event: unknown) => void> = [];
+    const model = {
+      subscribe: jest.fn(listener => {
+        listeners.push(listener);
+        return () => undefined;
+      }),
+      emit: (event: unknown) => {
+        listeners.forEach(listener => listener(event));
+      },
+      init: jest.fn(async () => undefined),
+      close: jest.fn(),
+      setTimeZone: jest.fn(),
+      setChartType: jest.fn(),
+      setDebugFn: jest.fn(),
+      getFigureData: jest.fn(() => mockFigure),
+      getColumnData: jest.fn(() => mockColumnData),
+      isResampling: jest.fn(() => true),
+      isDownsampled: jest.fn(() => true),
+      isAutoBinned: jest.fn(() => false),
+      getDownsampledTableIds: jest.fn(() => new Set([0])),
+      getAutoBinMeta: jest.fn(() => ({})),
+      getAutoBinBodyRange: jest.fn(() => null),
+      getTable: jest.fn(() => ({ size: 1000 })),
+      isReady: jest.fn(() => true),
+      getTimeZone: jest.fn(() => 'UTC'),
+      getEnabledHandlers: jest.fn(() => []),
+      performResample: jest.fn(),
+      performAutoBin: jest.fn(),
+    };
+    mockModelInstances.push(model);
+    return model;
+  }),
+}));
+
+const MockResizeObserver = jest.fn().mockImplementation(() => ({
+  observe: jest.fn(),
+  unobserve: jest.fn(),
+  disconnect: jest.fn(),
+}));
+
+(global as unknown as { ResizeObserver: unknown }).ResizeObserver =
+  MockResizeObserver;
+
+function makeWidget() {
+  return {
+    addEventListener: jest.fn(() => () => undefined),
+    removeEventListener: jest.fn(),
+    exportedObjects: [],
+    getDataAsString: jest.fn(() =>
+      JSON.stringify({
+        type: 'NEW_FIGURE',
+        figure: mockFigure,
+        revision: 1,
+        new_references: [0],
+        removed_references: [],
+      })
+    ),
+  };
+}
+
+async function renderChart() {
+  const widget = makeWidget();
+  const result = render(
+    <TradingViewChart fetch={() => Promise.resolve(widget)} metadata={{}} />
+  );
+
+  await act(async () => {
+    await Promise.resolve();
+    await Promise.resolve();
+  });
+
+  expect(mockRendererInstances).toHaveLength(1);
+  expect(mockModelInstances).toHaveLength(1);
+  return result;
+}
+
+function emitDataUpdate(event: Record<string, unknown>): void {
+  const model = mockModelInstances[0] as { emit: (e: unknown) => void };
+  act(() => {
+    model.emit({
+      type: 'DATA_UPDATED',
+      tableId: 0,
+      isInitialLoad: false,
+      addedCount: 0,
+      removedCount: 0,
+      modifiedCount: 0,
+      isDownsampleSwap: false,
+      ...event,
+    });
+  });
+}
+
+function dispatchPointerDown(element: Element): void {
+  act(() => {
+    element.dispatchEvent(new Event('pointerdown', { bubbles: true }));
+  });
+}
+
+describe('TradingViewChart drag viewport handling', () => {
+  beforeEach(() => {
+    jest.useFakeTimers();
+    jest.clearAllMocks();
+    mockVisibleRange = { from: 0, to: 100 };
+    mockVisibleRangeHandlers.length = 0;
+    mockSizeHandlers.length = 0;
+    mockModelInstances.length = 0;
+    mockRendererInstances.length = 0;
+  });
+
+  afterEach(() => {
+    act(() => {
+      jest.runOnlyPendingTimers();
+    });
+    jest.useRealTimers();
+  });
+
+  it('does not fit content when a tick arrives during an active drag', async () => {
+    const { container } = await renderChart();
+    const renderer = mockRendererInstances[0] as { fitContent: jest.Mock };
+    const chartContainer = container.querySelector('.dh-tvl-chart');
+    expect(chartContainer).not.toBeNull();
+
+    renderer.fitContent.mockClear();
+    mockTimeScale.setVisibleRange.mockClear();
+    dispatchPointerDown(chartContainer as Element);
+    emitDataUpdate({ addedCount: 1 });
+
+    expect(renderer.fitContent).not.toHaveBeenCalled();
+    expect(mockTimeScale.setVisibleRange).not.toHaveBeenCalled();
+  });
+
+  it('restores the live drag range when a downsample swap arrives mid-drag', async () => {
+    const { container } = await renderChart();
+    const model = mockModelInstances[0] as {
+      performResample: jest.Mock;
+    };
+    const chartContainer = container.querySelector('.dh-tvl-chart');
+    expect(chartContainer).not.toBeNull();
+
+    act(() => {
+      jest.advanceTimersByTime(1000);
+    });
+
+    mockVisibleRange = { from: 10, to: 60 };
+    act(() => {
+      mockVisibleRangeHandlers.forEach(handler => handler());
+      jest.advanceTimersByTime(200);
+    });
+    expect(model.performResample).toHaveBeenCalledWith([0, 70], 1000);
+
+    dispatchPointerDown(chartContainer as Element);
+    mockVisibleRange = { from: 20, to: 70 };
+    act(() => {
+      mockVisibleRangeHandlers.forEach(handler => handler());
+    });
+
+    mockTimeScale.setVisibleRange.mockClear();
+    emitDataUpdate({ isDownsampleSwap: true });
+
+    expect(mockTimeScale.setVisibleRange).toHaveBeenCalledWith({
+      from: 20,
+      to: 70,
+    });
+    expect(mockTimeScale.setVisibleRange).not.toHaveBeenCalledWith({
+      from: 10,
+      to: 60,
+    });
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChart.realredux.test.tsx b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChart.realredux.test.tsx
new file mode 100644
index 000000000..ade00c7a4
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChart.realredux.test.tsx
@@ -0,0 +1,142 @@
+/**
+ * FAITHFUL integration test of the timezone wiring using the REAL
+ * @deephaven/redux store, the REAL updateSettings action (what the Settings
+ * dropdown dispatches), and the REAL getTimeZone selector — nothing about the
+ * redux layer is mocked. This reproduces the exact path the user exercises
+ * when changing the timezone in the Settings sidebar, without a DH server.
+ */
+import fs from 'fs';
+import path from 'path';
+import React from 'react';
+import { render, act, waitFor } from '@testing-library/react';
+import { Provider } from 'react-redux';
+import { store, updateSettings } from '@deephaven/redux';
+import TradingViewChart from '../TradingViewChart';
+import TradingViewChartModel from '../TradingViewChartModel';
+
+// Regression guard: the DH client's plugin require shim does NOT provide
+// `@deephaven/redux`, so it must be BUNDLED, not externalized. Externalizing
+// it makes the plugin fail to load entirely ("Could not require
+// '@deephaven/redux'"). Importing it is fine (plotly-express does the same) as
+// long as it is absent from vite.config externals. This test fails if it is
+// ever added back to externals. (react-redux/redux ARE client-provided, so
+// they stay externalized.)
+it('does not externalize @deephaven/redux (must be bundled)', () => {
+  const vite = fs.readFileSync(
+    path.join(__dirname, '..', '..', 'vite.config.ts'),
+    'utf8'
+  );
+  const externalBlock = vite.slice(
+    vite.indexOf('external:'),
+    vite.indexOf(']', vite.indexOf('external:'))
+  );
+  expect(externalBlock).not.toContain('@deephaven/redux');
+});
+
+jest.mock('@deephaven/jsapi-bootstrap', () => {
+  const dh = {
+    Widget: { EVENT_MESSAGE: 'message', EVENT_CLOSE: 'close' },
+    Table: { EVENT_UPDATED: 'updated', EVENT_DISCONNECT: 'd', EVENT_RECONNECT: 'r' },
+    DateWrapper: { ofJsDate: (d: Date) => ({ asDate: () => d }) },
+    plot: {
+      ChartData: function ChartData() {
+        return { update: () => undefined, getColumn: () => [] };
+      },
+      Downsample: { runChartDownsample: () => undefined },
+    },
+  };
+  return { useApi: () => dh };
+});
+
+jest.mock('../TradingViewTheme', () => {
+  const actual = jest.requireActual('../TradingViewTheme');
+  return {
+    ...actual,
+    useDHChartTheme: () => ({
+      paperBgColor: '#111', plotBgColor: '#111', textColor: '#eee',
+      gridColor: '#333', lineColor: '#555', zeroLineColor: '#777',
+      crosshairLabelBgColor: '#444', fontFamily: 'sans-serif',
+      ohlcIncreasing: '#0a0', ohlcDecreasing: '#a00', colorway: ['#48a', '#f81'],
+    }),
+  };
+});
+
+class MockResizeObserver {
+  observe = jest.fn();
+
+  unobserve = jest.fn();
+
+  disconnect = jest.fn();
+}
+(global as unknown as { ResizeObserver: unknown }).ResizeObserver = MockResizeObserver;
+
+class MockTable {
+  size = 10;
+
+  columns = [
+    { name: 'Timestamp', type: 'io.deephaven.time.DateTime' },
+    { name: 'Value', type: 'double' },
+  ];
+
+  addEventListener = jest.fn(() => () => undefined);
+
+  removeEventListener = jest.fn();
+
+  subscribe = jest.fn(() => ({
+    addEventListener: jest.fn(() => () => undefined),
+    close: jest.fn(),
+  }));
+
+  close = jest.fn();
+}
+
+function makeWidget() {
+  const table = new MockTable();
+  return {
+    addEventListener: jest.fn(() => () => undefined),
+    removeEventListener: jest.fn(),
+    exportedObjects: [{ fetch: jest.fn().mockResolvedValue(table) }],
+    getDataAsString: jest.fn(() =>
+      JSON.stringify({
+        type: 'NEW_FIGURE',
+        figure: {
+          chartType: 'standard',
+          chartOptions: {},
+          series: [{ id: 's0', type: 'Line', options: {}, dataMapping: { tableId: 0, columns: { time: 'Timestamp', value: 'Value' } } }],
+          deephaven: { mappings: [] },
+        },
+        revision: 1,
+        new_references: [0],
+        removed_references: [],
+      })
+    ),
+  };
+}
+
+it('changing the real redux timezone setting pushes it into the model', async () => {
+  const setTimeZoneSpy = jest.spyOn(TradingViewChartModel.prototype, 'setTimeZone');
+  const widget = makeWidget();
+  const props = {
+    fetch: () => Promise.resolve(widget),
+    metadata: {},
+  } as unknown as React.ComponentProps<typeof TradingViewChart>;
+
+  await act(async () => {
+    render(
+      <Provider store={store}>
+        <TradingViewChart {...props} />
+      </Provider>
+    );
+  });
+
+  // The Settings dropdown dispatches exactly this.
+  await act(async () => {
+    store.dispatch(updateSettings({ timeZone: 'Asia/Tokyo' }) as never);
+  });
+
+  await waitFor(() =>
+    expect(setTimeZoneSpy).toHaveBeenCalledWith('Asia/Tokyo')
+  );
+
+  setTimeZoneSpy.mockRestore();
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChartModel.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChartModel.test.ts
new file mode 100644
index 000000000..ec19ef8fc
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChartModel.test.ts
@@ -0,0 +1,634 @@
+/**
+ * Unit tests for TradingViewChartModel server-side auto-bin path:
+ *  - performAutoBin sends AUTOBIN_ZOOM / AUTOBIN_RESET via widget.sendMessage
+ *  - handleAutoBinFigure swaps the subscribed table, drains queued requests
+ *  - performResample dispatches across both paths
+ */
+import TradingViewChartModel from '../TradingViewChartModel';
+import type { TvlFigureData, TvlSeriesConfig } from '../TradingViewTypes';
+
+type Listener = (event: { detail: unknown }) => void;
+
+class MockTable {
+  size: number;
+
+  columns: { name: string; type: string }[] = [
+    { name: 'Timestamp', type: 'io.deephaven.time.DateTime' },
+    { name: 'Value', type: 'double' },
+  ];
+
+  isRefreshing = false;
+
+  listenerMap: Map<string, Set<Listener>> = new Map();
+
+  closed = false;
+
+  addEventListener = jest.fn((event: string, l: Listener) => {
+    if (!this.listenerMap.has(event)) this.listenerMap.set(event, new Set());
+    this.listenerMap.get(event)!.add(l);
+    return () => this.listenerMap.get(event)?.delete(l);
+  });
+
+  removeEventListener = jest.fn();
+
+  subscribe = jest.fn(() => ({
+    addEventListener: jest.fn(() => () => {
+      /* noop */
+    }),
+    close: jest.fn(),
+  }));
+
+  setViewport = jest.fn(() => ({
+    addEventListener: jest.fn(() => () => {
+      /* noop */
+    }),
+    setViewport: jest.fn(),
+    close: jest.fn(),
+  }));
+
+  close = jest.fn(() => {
+    this.closed = true;
+  });
+
+  constructor(size = 100) {
+    this.size = size;
+  }
+}
+
+function makeMockPartitionedTable(tables: Map<unknown, MockTable>) {
+  const listenerMap: Map<string, Set<Listener>> = new Map();
+  return {
+    listenerMap,
+    addEventListener: jest.fn((event: string, l: Listener) => {
+      if (!listenerMap.has(event)) listenerMap.set(event, new Set());
+      listenerMap.get(event)!.add(l);
+      return () => listenerMap.get(event)?.delete(l);
+    }),
+    getKeys: jest.fn(() => new Set(tables.keys())),
+    getTable: jest.fn((key: unknown) =>
+      Promise.resolve(tables.get(key) ?? null)
+    ),
+    close: jest.fn(),
+  };
+}
+
+function makeFigure(autoBin: boolean): TvlFigureData {
+  return {
+    chartOptions: {},
+    series: [
+      {
+        id: 'series_0',
+        type: 'Histogram',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'Timestamp', value: 'Value' },
+        },
+      },
+    ],
+    deephaven: { mappings: [] },
+    autoBinMeta: autoBin
+      ? {
+          '0': {
+            timeCol: 'Timestamp',
+            binWidthNs: 1_000_000_000,
+            fullRangeNs: [0, 86_400_000_000_000],
+            targetBins: 5000,
+            series: {
+              series_0: { type: 'Histogram', agg: 'sum', valueCols: ['Value'] },
+            },
+          },
+        }
+      : undefined,
+  };
+}
+
+function makeMockDh() {
+  const tableSubscribers: Set<Listener> = new Set();
+  return {
+    Widget: { EVENT_MESSAGE: 'message', EVENT_CLOSE: 'close' },
+    Table: {
+      EVENT_UPDATED: 'updated',
+      EVENT_DISCONNECT: 'disconnect',
+      EVENT_RECONNECT: 'reconnect',
+    },
+    DateWrapper: {
+      ofJsDate: (d: Date) => ({ asDate: () => d }),
+    },
+    plot: {
+      ChartData: jest.fn().mockImplementation(() => ({
+        update: jest.fn(),
+        getColumn: jest.fn(() => []),
+      })),
+      Downsample: { runChartDownsample: jest.fn() },
+    },
+    _tableSubscribers: tableSubscribers,
+  } as unknown as typeof import('@deephaven/jsapi-types').dh;
+}
+
+function makeMockWidget() {
+  const listeners = new Map<string, Set<Listener>>();
+  return {
+    sendMessage: jest.fn(),
+    addEventListener: jest.fn((event: string, l: Listener) => {
+      if (!listeners.has(event)) listeners.set(event, new Set());
+      listeners.get(event)!.add(l);
+    }),
+    removeEventListener: jest.fn((event: string, l: Listener) => {
+      listeners.get(event)?.delete(l);
+    }),
+    exportedObjects: [],
+    getDataAsString: jest.fn(),
+    /** Fire a synthetic widget event. */
+    fire(event: string, detail: unknown) {
+      const ls = listeners.get(event);
+      if (ls) ls.forEach(l => l({ detail }));
+    },
+  };
+}
+
+function makePartitionFigure(): TvlFigureData {
+  return {
+    chartOptions: {},
+    series: [
+      {
+        id: 'series_0',
+        type: 'Area',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'Timestamp', value: 'Value' },
+        },
+        partition: { byColumn: 'Sym', refIndex: 1 },
+      },
+    ],
+    deephaven: { mappings: [] },
+    downsampleMeta: {
+      '0': {
+        tableSize: 10_000_000,
+        timeCol: 'Timestamp',
+        valueCols: ['Value'],
+        seriesTypes: ['Area'],
+      },
+    },
+  };
+}
+
+function runDownsampleMock(
+  dh: ReturnType<typeof makeMockDh>
+): jest.MockedFunction<
+  (
+    table: unknown,
+    timeCol: string,
+    valueCols: string[],
+    targetWidth: number,
+    range?: unknown
+  ) => Promise<MockTable>
+> {
+  return (
+    dh as unknown as {
+      plot: {
+        Downsample: {
+          runChartDownsample: jest.MockedFunction<
+            (
+              table: unknown,
+              timeCol: string,
+              valueCols: string[],
+              targetWidth: number,
+              range?: unknown
+            ) => Promise<MockTable>
+          >;
+        };
+      };
+    }
+  ).plot.Downsample.runChartDownsample;
+}
+
+async function initModelWithAutoBin(autoBin: boolean): Promise<{
+  model: TradingViewChartModel;
+  widget: ReturnType<typeof makeMockWidget>;
+  table: MockTable;
+}> {
+  const dh = makeMockDh();
+  const widget = makeMockWidget();
+  const model = new TradingViewChartModel(dh, widget as never);
+
+  const figure = makeFigure(autoBin);
+  const dataString = JSON.stringify({
+    type: 'NEW_FIGURE',
+    figure,
+    revision: 1,
+    new_references: [0],
+    removed_references: [],
+  });
+
+  const table = new MockTable();
+  const exported = [{ fetch: jest.fn().mockResolvedValue(table) } as never];
+
+  model.setTimeZone('UTC');
+  await model.init(exported, dataString);
+
+  return { model, widget, table };
+}
+
+describe('TradingViewChartModel auto-bin', () => {
+  describe('autoBinMeta detection', () => {
+    it('marks the model as auto-binned when figure.autoBinMeta is present', async () => {
+      const { model } = await initModelWithAutoBin(true);
+      expect(model.isAutoBinned()).toBe(true);
+      expect(model.isResampling()).toBe(true);
+      expect(Object.keys(model.getAutoBinMeta())).toEqual(['0']);
+    });
+
+    it('is not auto-binned when figure has no autoBinMeta', async () => {
+      const { model } = await initModelWithAutoBin(false);
+      expect(model.isAutoBinned()).toBe(false);
+      expect(model.isResampling()).toBe(false);
+    });
+  });
+
+  describe('performAutoBin', () => {
+    it('sends AUTOBIN_RESET when range is null', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      model.performAutoBin(null);
+      expect(widget.sendMessage).toHaveBeenCalledTimes(1);
+      const [payload] = widget.sendMessage.mock.calls[0];
+      const msg = JSON.parse(payload as string);
+      expect(msg).toEqual({ type: 'AUTOBIN_RESET', tableRef: 0 });
+    });
+
+    it('sends AUTOBIN_ZOOM with from/to nanoseconds when range is provided', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      // 2024-01-01T00:00:00Z to 2024-01-01T01:00:00Z in TZ-shifted seconds
+      // (timeZone='UTC' so unconvertTime is identity).
+      const fromSec = 1704067200;
+      const toSec = 1704067200 + 3600;
+      model.performAutoBin([fromSec, toSec]);
+      expect(widget.sendMessage).toHaveBeenCalledTimes(1);
+      const msg = JSON.parse(widget.sendMessage.mock.calls[0][0] as string);
+      expect(msg).toMatchObject({
+        type: 'AUTOBIN_ZOOM',
+        tableRef: 0,
+        fromNs: fromSec * 1e9,
+        toNs: toSec * 1e9,
+      });
+    });
+
+    it('queues a second request while the first is in flight', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      model.performAutoBin([0, 100]);
+      expect(widget.sendMessage).toHaveBeenCalledTimes(1);
+      // Second call hits the pending guard
+      model.performAutoBin([200, 300]);
+      expect(widget.sendMessage).toHaveBeenCalledTimes(1);
+    });
+
+    it('emits DOWNSAMPLE_PENDING when in flight', async () => {
+      const { model } = await initModelWithAutoBin(true);
+      const events: { pending: boolean }[] = [];
+      model.subscribe(e => {
+        if (e.type === 'DOWNSAMPLE_PENDING') {
+          events.push({ pending: e.pending });
+        }
+      });
+      model.performAutoBin([0, 100]);
+      expect(events).toEqual([{ pending: true }]);
+    });
+
+    it('increments resampleSeq on each issued request', async () => {
+      const { model } = await initModelWithAutoBin(true);
+      const before = model.resampleSeq;
+      model.performAutoBin([0, 100]);
+      expect(model.resampleSeq).toBe(before + 1);
+    });
+
+    it('does nothing when not auto-binned', async () => {
+      const { model, widget } = await initModelWithAutoBin(false);
+      model.performAutoBin([0, 100]);
+      expect(widget.sendMessage).not.toHaveBeenCalled();
+    });
+  });
+
+  describe('handleAutoBinFigure', () => {
+    it('clears pendingAutoBin on a noop ack', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      const events: { pending: boolean }[] = [];
+      model.subscribe(e => {
+        if (e.type === 'DOWNSAMPLE_PENDING') {
+          events.push({ pending: e.pending });
+        }
+      });
+      model.performAutoBin([0, 100]);
+      // Simulate the server's noop AUTOBIN_FIGURE ack
+      const detail = {
+        getDataAsString: () =>
+          JSON.stringify({
+            type: 'AUTOBIN_FIGURE',
+            revision: 2,
+            tableRef: 0,
+            binWidthNs: 1_000_000_000,
+            autoBinMeta: model.getAutoBinMeta(),
+            new_references: [],
+            noop: true,
+          }),
+        exportedObjects: [],
+      };
+      widget.fire('message', detail);
+      // setPendingAutoBin(false) runs synchronously inside the noop branch
+      expect(events.map(e => e.pending)).toEqual([true, false]);
+    });
+
+    it('marks the swap as a reset when AUTOBIN_RESET was the trigger', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      // First send a reset
+      model.performAutoBin(null);
+
+      const newTable = new MockTable();
+      newTable.size = 12;
+
+      const detail = {
+        getDataAsString: () =>
+          JSON.stringify({
+            type: 'AUTOBIN_FIGURE',
+            revision: 2,
+            tableRef: 0,
+            binWidthNs: 86_400_000_000_000,
+            autoBinMeta: {
+              '0': {
+                timeCol: 'Timestamp',
+                binWidthNs: 86_400_000_000_000,
+                fullRangeNs: [0, 86_400_000_000_000],
+                targetBins: 5000,
+                series: {
+                  series_0: {
+                    type: 'Histogram',
+                    agg: 'sum',
+                    valueCols: ['Value'],
+                  },
+                },
+              },
+            },
+            new_references: [0],
+          }),
+        exportedObjects: [{ fetch: jest.fn().mockResolvedValue(newTable) }],
+      };
+
+      const dataEvents: { isResetView?: boolean }[] = [];
+      model.subscribe(e => {
+        if (e.type === 'DATA_UPDATED') dataEvents.push({ isResetView: e.isResetView });
+      });
+
+      widget.fire('message', detail);
+      await new Promise<void>(resolve => {
+        setTimeout(resolve, 0);
+      });
+
+      // The new table's first DATA_UPDATED would normally come from a real
+      // subscription tick. Here MockTable doesn't fire one, so we just verify
+      // the resetPendingForTable bookkeeping by inspecting model state via
+      // its public swap behavior — the table was replaced.
+      expect(model.getTable(0)).toBe(newTable);
+    });
+
+    it('swaps the aggregated table when a non-noop response arrives', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      model.performAutoBin([0, 100]);
+
+      const newTable = new MockTable();
+      newTable.size = 42;
+
+      const detail = {
+        getDataAsString: () =>
+          JSON.stringify({
+            type: 'AUTOBIN_FIGURE',
+            revision: 2,
+            tableRef: 0,
+            binWidthNs: 500_000_000,
+            autoBinMeta: {
+              '0': {
+                timeCol: 'Timestamp',
+                binWidthNs: 500_000_000,
+                fullRangeNs: [0, 86_400_000_000_000],
+                targetBins: 5000,
+                series: {
+                  series_0: {
+                    type: 'Histogram',
+                    agg: 'sum',
+                    valueCols: ['Value'],
+                  },
+                },
+              },
+            },
+            new_references: [0],
+          }),
+        exportedObjects: [{ fetch: jest.fn().mockResolvedValue(newTable) }],
+      };
+      widget.fire('message', detail);
+
+      // Allow the awaited fetch + subscribe to run
+      await new Promise<void>(resolve => {
+        setTimeout(resolve, 0);
+      });
+
+      expect(model.getTable(0)).toBe(newTable);
+      expect(model.getAutoBinMeta()['0'].binWidthNs).toBe(500_000_000);
+    });
+  });
+
+  describe('performResample router', () => {
+    it('routes auto-binned figures through the auto-bin path', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      model.performResample([0, 100], 1024);
+      expect(widget.sendMessage).toHaveBeenCalledTimes(1);
+      const msg = JSON.parse(widget.sendMessage.mock.calls[0][0] as string);
+      expect(msg.type).toBe('AUTOBIN_ZOOM');
+    });
+
+    it('initial auto-bin subscription uses subscribe (not setViewport)', async () => {
+      const { table } = await initModelWithAutoBin(true);
+      // Server-side scoping: agg table is small enough for full subscribe.
+      // The viewport API is no longer used on autobin tables.
+      expect(table.setViewport).not.toHaveBeenCalled();
+      expect(table.subscribe).toHaveBeenCalledTimes(1);
+    });
+
+    it('AUTOBIN_ZOOM payload includes atLiveEdge=true at the source right edge', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      // fullRangeNs[1] = 86_400_000_000_000 → 86400s in TZ-shifted seconds
+      const fromSec = 86400 - 60;
+      const toSec = 86400;
+      model.performAutoBin([fromSec, toSec]);
+      const msg = JSON.parse(widget.sendMessage.mock.calls[0][0] as string);
+      expect(msg.type).toBe('AUTOBIN_ZOOM');
+      expect(msg.atLiveEdge).toBe(true);
+    });
+
+    it('AUTOBIN_ZOOM payload includes atLiveEdge=false inside the source extent', async () => {
+      const { model, widget } = await initModelWithAutoBin(true);
+      const fromSec = 100;
+      const toSec = 200;
+      model.performAutoBin([fromSec, toSec]);
+      const msg = JSON.parse(widget.sendMessage.mock.calls[0][0] as string);
+      expect(msg.type).toBe('AUTOBIN_ZOOM');
+      expect(msg.atLiveEdge).toBe(false);
+    });
+
+    it('does nothing when neither downsample nor auto-bin is active', async () => {
+      const { model, widget } = await initModelWithAutoBin(false);
+      model.performResample([0, 100], 1024);
+      expect(widget.sendMessage).not.toHaveBeenCalled();
+    });
+  });
+});
+
+describe('TradingViewChartModel partition downsampling', () => {
+  it('downsamples large partition constituents without fetching the raw source table', async () => {
+    const dh = makeMockDh();
+    const widget = makeMockWidget();
+    const model = new TradingViewChartModel(dh, widget as never);
+
+    const sourceTable = new MockTable(10_000_000);
+    const partitionSourceTable = new MockTable(5_000);
+    const downsampledTable = new MockTable(250);
+    const partitionedTable = makeMockPartitionedTable(
+      new Map([['aaa', partitionSourceTable]])
+    );
+
+    const runDownsample = runDownsampleMock(dh);
+    runDownsample.mockResolvedValue(downsampledTable);
+
+    const sourceExport = {
+      fetch: jest.fn().mockResolvedValue(sourceTable),
+    };
+    const partitionExport = {
+      fetch: jest.fn().mockResolvedValue(partitionedTable),
+    };
+
+    await model.init(
+      [sourceExport, partitionExport] as never,
+      JSON.stringify({
+        type: 'NEW_FIGURE',
+        figure: makePartitionFigure(),
+        revision: 1,
+        new_references: [0, 1],
+        removed_references: [],
+      })
+    );
+
+    expect(sourceExport.fetch).not.toHaveBeenCalled();
+    expect(partitionExport.fetch).toHaveBeenCalledTimes(1);
+    expect(partitionedTable.getTable).toHaveBeenCalledWith('aaa');
+    expect(runDownsample).toHaveBeenCalledWith(
+      partitionSourceTable,
+      'Timestamp',
+      ['Value'],
+      1000,
+      undefined
+    );
+    expect(partitionSourceTable.subscribe).not.toHaveBeenCalled();
+    expect(downsampledTable.subscribe).toHaveBeenCalledTimes(1);
+    expect(model.getDownsampledTableIds().has(2)).toBe(true);
+    expect(model.getDownsampleMeta()['2']).toMatchObject({
+      tableSize: 5_000,
+      timeCol: 'Timestamp',
+      valueCols: ['Value'],
+    });
+  });
+
+  it('subscribes small partition constituents directly', async () => {
+    const dh = makeMockDh();
+    const widget = makeMockWidget();
+    const model = new TradingViewChartModel(dh, widget as never);
+
+    const sourceTable = new MockTable(10_000_000);
+    const partitionSourceTable = new MockTable(10);
+    const partitionedTable = makeMockPartitionedTable(
+      new Map([['aaa', partitionSourceTable]])
+    );
+    const runDownsample = runDownsampleMock(dh);
+
+    await model.init(
+      [
+        { fetch: jest.fn().mockResolvedValue(sourceTable) },
+        { fetch: jest.fn().mockResolvedValue(partitionedTable) },
+      ] as never,
+      JSON.stringify({
+        type: 'NEW_FIGURE',
+        figure: makePartitionFigure(),
+        revision: 1,
+        new_references: [0, 1],
+        removed_references: [],
+      })
+    );
+
+    expect(runDownsample).not.toHaveBeenCalled();
+    expect(partitionSourceTable.subscribe).toHaveBeenCalledTimes(1);
+    expect(model.getDownsampledTableIds().has(2)).toBe(false);
+  });
+
+  it('isReady ignores partition templates once runtime series has data', () => {
+    const dh = makeMockDh();
+    const widget = makeMockWidget();
+    const model = new TradingViewChartModel(dh, widget as never);
+    const template = makePartitionFigure().series[0];
+    const runtimeSeries: TvlSeriesConfig = {
+      id: 'series_0_aaa',
+      type: 'Area',
+      options: { title: 'aaa' },
+      dataMapping: {
+        tableId: 2,
+        columns: { time: 'Timestamp', value: 'Value' },
+      },
+    };
+    const state = model as unknown as {
+      figureData: TvlFigureData;
+      tableDataMap: Map<number, Record<string, unknown[]>>;
+      tables: Map<number, MockTable>;
+    };
+    state.figureData = {
+      ...makePartitionFigure(),
+      series: [template, runtimeSeries],
+    };
+    state.tableDataMap.set(2, { Timestamp: [1], Value: [2] });
+    state.tables.set(2, new MockTable(1));
+
+    expect(model.isReady()).toBe(true);
+  });
+});
+
+describe('TradingViewChartModel timezone changes', () => {
+  it('re-subscribes active tables when the timezone changes after init', async () => {
+    const { model, table } = await initModelWithAutoBin(false);
+    // init subscribed exactly once
+    expect(table.subscribe).toHaveBeenCalledTimes(1);
+    const firstSub = table.subscribe.mock.results[0].value;
+
+    model.setTimeZone('America/New_York');
+
+    // Old subscription torn down, a fresh one created so time columns
+    // re-convert through timeTranslator in the new timezone.
+    expect(firstSub.close).toHaveBeenCalledTimes(1);
+    expect(table.subscribe).toHaveBeenCalledTimes(2);
+    expect(model.getTimeZone()).toBe('America/New_York');
+  });
+
+  it('does not re-subscribe when the timezone is unchanged', async () => {
+    const { model, table } = await initModelWithAutoBin(false);
+    expect(table.subscribe).toHaveBeenCalledTimes(1);
+
+    // initModelWithAutoBin sets the zone to 'UTC' before init
+    model.setTimeZone('UTC');
+
+    expect(table.subscribe).toHaveBeenCalledTimes(1);
+  });
+
+  it('stores the timezone before init without subscribing', () => {
+    const dh = makeMockDh();
+    const widget = makeMockWidget();
+    const model = new TradingViewChartModel(dh, widget as never);
+
+    model.setTimeZone('Europe/London');
+
+    expect(model.getTimeZone()).toBe('Europe/London');
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChartRenderer.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChartRenderer.test.ts
new file mode 100644
index 000000000..fbee9f0bb
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewChartRenderer.test.ts
@@ -0,0 +1,1488 @@
+import type { TvlSeriesConfig } from '../TradingViewTypes';
+import TradingViewChartRenderer from '../TradingViewChartRenderer';
+
+// The manual mock at src/__mocks__/lightweight-charts.js is loaded via moduleNameMapper.
+// We import the mock internals to set up assertions.
+// eslint-disable-next-line @typescript-eslint/no-var-requires
+const lwc = require('lightweight-charts');
+
+const {
+  createChart,
+  createYieldCurveChart,
+  createOptionsChart,
+  createSeriesMarkers,
+  createTextWatermark,
+} = lwc;
+// eslint-disable-next-line no-underscore-dangle
+const mockChart = lwc.__mockChart;
+// eslint-disable-next-line no-underscore-dangle
+const mockSeriesInstance = lwc.__mockSeriesInstance;
+// eslint-disable-next-line no-underscore-dangle
+const mockMarkersPlugin = lwc.__mockMarkersPlugin;
+// eslint-disable-next-line no-underscore-dangle
+const mockWatermarkPlugin = lwc.__mockWatermarkPlugin;
+// eslint-disable-next-line no-underscore-dangle
+const mockPane = lwc.__mockPane;
+// eslint-disable-next-line no-underscore-dangle
+const mockTimeScale = lwc.__mockTimeScale;
+// eslint-disable-next-line no-underscore-dangle
+const mockPriceLine = lwc.__mockPriceLine;
+// eslint-disable-next-line no-underscore-dangle
+const mockPriceScale = lwc.__mockPriceScale;
+// eslint-disable-next-line no-underscore-dangle
+const mockPane2 = lwc.__mockPane2;
+
+beforeEach(() => {
+  jest.clearAllMocks();
+});
+
+function createRenderer(): TradingViewChartRenderer {
+  const container = document.createElement('div');
+  return new TradingViewChartRenderer(container);
+}
+
+describe('TradingViewChartRenderer', () => {
+  describe('constructor', () => {
+    it('should call createChart with the container and default options', () => {
+      const container = document.createElement('div');
+      const renderer = new TradingViewChartRenderer(container);
+
+      expect(createChart).toHaveBeenCalledTimes(1);
+      expect(createChart).toHaveBeenCalledWith(
+        container,
+        expect.objectContaining({
+          autoSize: true,
+        })
+      );
+      expect(renderer).toBeDefined();
+    });
+
+    it('should apply custom options to createChart', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        layout: {
+          background: { type: 'solid' as never, color: '#FF0000' },
+        },
+      });
+
+      expect(createChart).toHaveBeenCalledWith(
+        container,
+        expect.objectContaining({
+          layout: expect.objectContaining({
+            background: { type: 'solid', color: '#FF0000' },
+          }),
+          autoSize: true,
+        })
+      );
+    });
+  });
+
+  describe('configureSeries', () => {
+    it('should create a Candlestick series via addSeries', () => {
+      const renderer = createRenderer();
+      const configs: TvlSeriesConfig[] = [
+        {
+          id: 'candle-1',
+          type: 'Candlestick',
+          options: { upColor: '#00FF00' },
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ];
+
+      renderer.configureSeries(configs);
+
+      expect(mockChart.addSeries).toHaveBeenCalledTimes(1);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.CandlestickSeries,
+        { upColor: '#00FF00' },
+        undefined
+      );
+    });
+
+    it('should create a Bar series via addSeries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'bar-1',
+          type: 'Bar',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.BarSeries,
+        {},
+        undefined
+      );
+    });
+
+    it('should create a Line series via addSeries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: { color: '#0000FF' },
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.LineSeries,
+        { color: '#0000FF' },
+        undefined
+      );
+    });
+
+    it('should create an Area series via addSeries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'area-1',
+          type: 'Area',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.AreaSeries,
+        {},
+        undefined
+      );
+    });
+
+    it('should create a Baseline series via addSeries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'baseline-1',
+          type: 'Baseline',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.BaselineSeries,
+        {},
+        undefined
+      );
+    });
+
+    it('should create a Histogram series via addSeries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'hist-1',
+          type: 'Histogram',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.HistogramSeries,
+        {},
+        undefined
+      );
+    });
+
+    it('should handle unknown series type gracefully', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'unknown-1',
+          type: 'Unknown' as TvlSeriesConfig['type'],
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      // addSeries should NOT be called for unknown types
+      expect(mockChart.addSeries).not.toHaveBeenCalled();
+    });
+
+    it('should remove existing series before creating new ones', () => {
+      const renderer = createRenderer();
+
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledTimes(1);
+
+      // Second configuration should remove old series first
+      renderer.configureSeries([
+        {
+          id: 'candle-1',
+          type: 'Candlestick',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.removeSeries).toHaveBeenCalledTimes(1);
+      expect(mockChart.removeSeries).toHaveBeenCalledWith(mockSeriesInstance);
+      expect(mockChart.addSeries).toHaveBeenCalledTimes(2);
+    });
+
+    it('should create multiple series at once', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'candle-1',
+          type: 'Candlestick',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledTimes(2);
+    });
+
+    it('should apply price lines when configured', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+          priceLines: [
+            {
+              price: 100,
+              color: '#FF0000',
+              lineWidth: 2,
+              lineStyle: 0,
+              axisLabelVisible: true,
+              title: 'Support',
+            },
+          ],
+        },
+      ]);
+      expect(mockSeriesInstance.createPriceLine).toHaveBeenCalledTimes(1);
+      expect(mockSeriesInstance.createPriceLine).toHaveBeenCalledWith({
+        price: 100,
+        color: '#FF0000',
+        lineWidth: 2,
+        lineStyle: 0,
+        axisLabelVisible: true,
+        title: 'Support',
+      });
+    });
+  });
+
+  describe('colorway defaults', () => {
+    const colorway = ['#4878d0', '#6acc64', '#d5bb67'];
+    const ohlcColors = { upColor: '#26a69a', downColor: '#ef5350' };
+
+    it('should assign colorway colors to Line series without explicit color', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'line-1',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+          {
+            id: 'line-2',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledTimes(2);
+      expect(mockChart.addSeries).toHaveBeenNthCalledWith(
+        1,
+        lwc.LineSeries,
+        expect.objectContaining({ color: '#4878d0' }),
+        undefined
+      );
+      expect(mockChart.addSeries).toHaveBeenNthCalledWith(
+        2,
+        lwc.LineSeries,
+        expect.objectContaining({ color: '#6acc64' }),
+        undefined
+      );
+    });
+
+    it('should not override user-specified colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'line-1',
+            type: 'Line',
+            options: { color: '#FF0000' },
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.LineSeries,
+        expect.objectContaining({ color: '#FF0000' }),
+        undefined
+      );
+    });
+
+    it('should wrap around when more series than colorway entries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'line-1',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+          {
+            id: 'line-2',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+          {
+            id: 'line-3',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+          {
+            id: 'line-4',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      // 4th series wraps to colorway[0]
+      expect(mockChart.addSeries).toHaveBeenNthCalledWith(
+        4,
+        lwc.LineSeries,
+        expect.objectContaining({ color: '#4878d0' }),
+        undefined
+      );
+    });
+
+    it('should assign colorway color and derive fills for Area series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'area-1',
+            type: 'Area',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.AreaSeries,
+        expect.objectContaining({
+          lineColor: '#4878d0',
+          topColor: 'rgba(72, 120, 208, 0.4)',
+          bottomColor: 'rgba(72, 120, 208, 0)',
+        }),
+        undefined
+      );
+    });
+
+    it('should not override user-specified Area fill colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'area-1',
+            type: 'Area',
+            options: { topColor: '#FF0000' },
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      // lineColor from colorway, but topColor kept as user-specified
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.AreaSeries,
+        expect.objectContaining({
+          lineColor: '#4878d0',
+          topColor: '#FF0000',
+          bottomColor: 'rgba(72, 120, 208, 0)',
+        }),
+        undefined
+      );
+    });
+
+    it('should assign colorway color and derive fills for Baseline series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'baseline-1',
+            type: 'Baseline',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.BaselineSeries,
+        expect.objectContaining({
+          topLineColor: '#4878d0',
+          topFillColor1: 'rgba(72, 120, 208, 0.3)',
+          topFillColor2: 'rgba(72, 120, 208, 0)',
+        }),
+        undefined
+      );
+    });
+
+    it('should assign colorway color to Histogram series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'hist-1',
+            type: 'Histogram',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.HistogramSeries,
+        expect.objectContaining({ color: '#4878d0' }),
+        undefined
+      );
+    });
+
+    it('should apply OHLC theme colors to Candlestick without user colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'candle-1',
+            type: 'Candlestick',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway,
+        ohlcColors
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.CandlestickSeries,
+        expect.objectContaining({
+          upColor: '#26a69a',
+          downColor: '#ef5350',
+        }),
+        undefined
+      );
+    });
+
+    it('should derive border and wick colors from OHLC theme colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'candle-1',
+            type: 'Candlestick',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway,
+        ohlcColors
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.CandlestickSeries,
+        expect.objectContaining({
+          borderUpColor: '#26a69a',
+          borderDownColor: '#ef5350',
+          wickUpColor: '#26a69a',
+          wickDownColor: '#ef5350',
+        }),
+        undefined
+      );
+    });
+
+    it('should not override user-specified border/wick colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'candle-1',
+            type: 'Candlestick',
+            options: { borderUpColor: '#AAAAAA', wickDownColor: '#BBBBBB' },
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway,
+        ohlcColors
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.CandlestickSeries,
+        expect.objectContaining({
+          borderUpColor: '#AAAAAA',
+          borderDownColor: '#ef5350',
+          wickUpColor: '#26a69a',
+          wickDownColor: '#BBBBBB',
+        }),
+        undefined
+      );
+    });
+
+    it('should not override user-specified OHLC colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'candle-1',
+            type: 'Candlestick',
+            options: { upColor: '#00FF00' },
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway,
+        ohlcColors
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.CandlestickSeries,
+        expect.objectContaining({
+          upColor: '#00FF00',
+          downColor: '#ef5350',
+        }),
+        undefined
+      );
+    });
+
+    it('should apply OHLC theme colors to Bar without user colors', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'bar-1',
+            type: 'Bar',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway,
+        ohlcColors
+      );
+
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.BarSeries,
+        expect.objectContaining({
+          upColor: '#26a69a',
+          downColor: '#ef5350',
+        }),
+        undefined
+      );
+    });
+
+    it('should not consume colorway index for OHLC types', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries(
+        [
+          {
+            id: 'candle-1',
+            type: 'Candlestick',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+          {
+            id: 'line-1',
+            type: 'Line',
+            options: {},
+            dataMapping: { tableId: 0, columns: { time: 'T' } },
+          },
+        ],
+        colorway,
+        ohlcColors
+      );
+
+      // Line series should get colorway[0], not colorway[1]
+      expect(mockChart.addSeries).toHaveBeenNthCalledWith(
+        2,
+        lwc.LineSeries,
+        expect.objectContaining({ color: '#4878d0' }),
+        undefined
+      );
+    });
+  });
+
+  describe('setSeriesData', () => {
+    it('should call setData on the correct series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+
+      const data = [
+        { time: 1704067200, value: 100 },
+        { time: 1704153600, value: 105 },
+      ];
+
+      renderer.setSeriesData('line-1', data);
+      expect(mockSeriesInstance.setData).toHaveBeenCalledTimes(1);
+      expect(mockSeriesInstance.setData).toHaveBeenCalledWith(data);
+    });
+
+    it('should not throw when series id is not found', () => {
+      const renderer = createRenderer();
+      expect(() => renderer.setSeriesData('nonexistent', [])).not.toThrow();
+      expect(mockSeriesInstance.setData).not.toHaveBeenCalled();
+    });
+  });
+
+  describe('setSeriesMarkers', () => {
+    it('should call createSeriesMarkers for the series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+
+      const markers = [
+        {
+          time: 1704067200,
+          position: 'aboveBar' as const,
+          shape: 'arrowDown' as const,
+          color: '#FF0000',
+          text: 'Sell',
+        },
+      ];
+
+      renderer.setSeriesMarkers('line-1', markers);
+      expect(createSeriesMarkers).toHaveBeenCalledTimes(1);
+      expect(createSeriesMarkers).toHaveBeenCalledWith(
+        mockSeriesInstance,
+        expect.arrayContaining([
+          expect.objectContaining({
+            time: 1704067200,
+            position: 'aboveBar',
+            shape: 'arrowDown',
+            color: '#FF0000',
+            text: 'Sell',
+          }),
+        ])
+      );
+    });
+
+    it('should use setMarkers on subsequent calls for same series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+
+      const markers1 = [
+        {
+          time: 1704067200,
+          position: 'aboveBar' as const,
+          shape: 'circle' as const,
+          color: '#FF0000',
+          text: 'A',
+        },
+      ];
+      const markers2 = [
+        {
+          time: 1704153600,
+          position: 'belowBar' as const,
+          shape: 'square' as const,
+          color: '#00FF00',
+          text: 'B',
+        },
+      ];
+
+      renderer.setSeriesMarkers('line-1', markers1);
+      renderer.setSeriesMarkers('line-1', markers2);
+
+      // createSeriesMarkers should only be called once
+      expect(createSeriesMarkers).toHaveBeenCalledTimes(1);
+      // setMarkers should be called on the plugin for subsequent calls
+      expect(mockMarkersPlugin.setMarkers).toHaveBeenCalledTimes(1);
+    });
+
+    it('should not throw when series id is not found', () => {
+      const renderer = createRenderer();
+      expect(() => renderer.setSeriesMarkers('nonexistent', [])).not.toThrow();
+      expect(createSeriesMarkers).not.toHaveBeenCalled();
+    });
+  });
+
+  describe('applyOptions', () => {
+    it('should call chart.applyOptions', () => {
+      const renderer = createRenderer();
+      const newOptions = {
+        layout: { textColor: '#AABBCC' },
+      };
+
+      renderer.applyOptions(newOptions);
+      expect(mockChart.applyOptions).toHaveBeenCalledTimes(1);
+      expect(mockChart.applyOptions).toHaveBeenCalledWith(newOptions);
+    });
+  });
+
+  describe('resize', () => {
+    it('should call chart.resize with width and height', () => {
+      const renderer = createRenderer();
+      renderer.resize(800, 600);
+
+      expect(mockChart.resize).toHaveBeenCalledTimes(1);
+      expect(mockChart.resize).toHaveBeenCalledWith(800, 600);
+    });
+  });
+
+  describe('fitContent', () => {
+    it('should call chart.timeScale().fitContent()', () => {
+      const renderer = createRenderer();
+      renderer.fitContent();
+
+      expect(mockChart.timeScale).toHaveBeenCalledTimes(1);
+      expect(mockTimeScale.fitContent).toHaveBeenCalledTimes(1);
+    });
+  });
+
+  describe('getChart', () => {
+    it('should return the underlying chart API', () => {
+      const renderer = createRenderer();
+      const chart = renderer.getChart();
+      expect(chart).toBe(mockChart);
+    });
+  });
+
+  describe('dispose', () => {
+    it('should call chart.remove()', () => {
+      const renderer = createRenderer();
+      renderer.dispose();
+
+      expect(mockChart.remove).toHaveBeenCalledTimes(1);
+    });
+
+    it('should clear the series map so subsequent data calls are no-ops', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+
+      mockSeriesInstance.setData.mockClear();
+
+      renderer.dispose();
+
+      // After dispose, setting data should be a no-op
+      renderer.setSeriesData('line-1', []);
+      expect(mockSeriesInstance.setData).not.toHaveBeenCalled();
+    });
+
+    it('should detach watermark on dispose', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      const renderer = new TradingViewChartRenderer(container, {
+        watermark: {
+          text: 'AAPL',
+          color: 'rgba(0,0,0,0.2)',
+        },
+      } as never);
+
+      renderer.dispose();
+      expect(mockWatermarkPlugin.detach).toHaveBeenCalledTimes(1);
+    });
+  });
+
+  describe('watermark', () => {
+    it('should create a text watermark plugin when watermark options are provided', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        watermark: {
+          text: 'AAPL',
+          color: 'rgba(0,0,0,0.2)',
+          fontSize: 64,
+          horzAlign: 'left',
+          vertAlign: 'top',
+        },
+      } as never);
+
+      expect(createTextWatermark).toHaveBeenCalledTimes(1);
+      expect(createTextWatermark).toHaveBeenCalledWith(
+        mockPane,
+        expect.objectContaining({
+          visible: true,
+          horzAlign: 'left',
+          vertAlign: 'top',
+          lines: [
+            expect.objectContaining({
+              text: 'AAPL',
+              color: 'rgba(0,0,0,0.2)',
+              fontSize: 64,
+            }),
+          ],
+        })
+      );
+    });
+
+    it('should use theme-derived defaults when only text is provided', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        layout: { textColor: '#D1D4DC' },
+        watermark: { text: 'AAPL' },
+      } as never);
+
+      expect(createTextWatermark).toHaveBeenCalledTimes(1);
+      expect(createTextWatermark).toHaveBeenCalledWith(
+        mockPane,
+        expect.objectContaining({
+          horzAlign: 'center',
+          vertAlign: 'center',
+          lines: [
+            expect.objectContaining({
+              text: 'AAPL',
+              color: 'rgba(209, 212, 220, 0.2)',
+              fontSize: 66,
+            }),
+          ],
+        })
+      );
+    });
+
+    it('should not create watermark when no watermark options are provided', () => {
+      createRenderer();
+      expect(createTextWatermark).not.toHaveBeenCalled();
+    });
+
+    it('should not create watermark when visible is false', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        watermark: {
+          text: 'AAPL',
+          visible: false,
+        },
+      } as never);
+
+      expect(createTextWatermark).not.toHaveBeenCalled();
+    });
+
+    it('should not create watermark when text is empty', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        watermark: {
+          color: 'rgba(0,0,0,0.2)',
+        },
+      } as never);
+
+      expect(createTextWatermark).not.toHaveBeenCalled();
+    });
+
+    it('should not pass watermark option to createChart', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        watermark: {
+          text: 'AAPL',
+        },
+      } as never);
+
+      const createChartOptions = createChart.mock.calls[0][1];
+      expect(createChartOptions).not.toHaveProperty('watermark');
+    });
+
+    it('should update watermark via applyOptions', () => {
+      const container = document.createElement('div');
+      const renderer = new TradingViewChartRenderer(container, {
+        watermark: {
+          text: 'AAPL',
+        },
+      } as never);
+
+      renderer.applyOptions({
+        watermark: {
+          text: 'GOOG',
+          color: '#FF0000',
+        },
+      } as never);
+
+      expect(mockWatermarkPlugin.applyOptions).toHaveBeenCalledTimes(1);
+      expect(mockWatermarkPlugin.applyOptions).toHaveBeenCalledWith(
+        expect.objectContaining({
+          lines: [
+            expect.objectContaining({
+              text: 'GOOG',
+              color: '#FF0000',
+            }),
+          ],
+        })
+      );
+    });
+
+    it('should not pass watermark to chart.applyOptions', () => {
+      const renderer = createRenderer();
+      renderer.applyOptions({
+        watermark: { text: 'AAPL' },
+        layout: { textColor: '#FFF' },
+      } as never);
+
+      expect(mockChart.applyOptions).toHaveBeenCalledWith(
+        expect.not.objectContaining({ watermark: expect.anything() })
+      );
+      expect(mockChart.applyOptions).toHaveBeenCalledWith(
+        expect.objectContaining({ layout: { textColor: '#FFF' } })
+      );
+    });
+
+    it('should update textColor for watermark derivation on applyOptions', () => {
+      const container = document.createElement('div');
+      // Start with dark text color
+      const renderer = new TradingViewChartRenderer(container, {
+        layout: { textColor: '#000000' },
+        watermark: { text: 'AAPL' },
+      } as never);
+
+      // First watermark uses initial textColor-derived color
+      const firstCall = (createTextWatermark as jest.Mock).mock.calls[0][1];
+      const firstColor = firstCall.lines[0].color;
+      expect(firstColor).toContain('0, 0, 0'); // derived from #000000
+
+      jest.clearAllMocks();
+
+      // Apply new theme with light text color + watermark update
+      renderer.applyOptions({
+        layout: { textColor: '#FFFFFF' },
+        watermark: { text: 'AAPL' },
+      } as never);
+
+      // Watermark should now derive from the NEW text color
+      const updateCall = (mockWatermarkPlugin.applyOptions as jest.Mock).mock
+        .calls[0][0];
+      const updatedColor = updateCall.lines[0].color;
+      expect(updatedColor).toContain('255, 255, 255'); // derived from #FFFFFF
+    });
+  });
+
+  describe('priceScaleOptions', () => {
+    it('should apply priceScaleOptions after creating series', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+          priceScaleOptions: {
+            autoScale: false,
+            scaleMargins: { top: 0.1, bottom: 0.2 },
+          },
+        },
+      ]);
+
+      expect(mockSeriesInstance.priceScale).toHaveBeenCalled();
+      expect(mockPriceScale.applyOptions).toHaveBeenCalledWith({
+        autoScale: false,
+        scaleMargins: { top: 0.1, bottom: 0.2 },
+      });
+    });
+
+    it('should not call priceScale when no priceScaleOptions', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+
+      expect(mockPriceScale.applyOptions).not.toHaveBeenCalled();
+    });
+  });
+
+  describe('localization price formatter', () => {
+    it('should resolve priceFormatterName to a function in constructor', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        localization: { priceFormatterName: 'currency_usd' },
+      } as never);
+
+      const createChartOptions = createChart.mock.calls[0][1];
+      expect(createChartOptions.localization).toBeDefined();
+      expect(typeof createChartOptions.localization.priceFormatter).toBe(
+        'function'
+      );
+      expect(
+        createChartOptions.localization.priceFormatterName
+      ).toBeUndefined();
+    });
+
+    it('should resolve priceFormatterName via applyOptions', () => {
+      const renderer = createRenderer();
+      renderer.applyOptions({
+        localization: { priceFormatterName: 'percent' },
+      } as never);
+
+      const appliedOptions = mockChart.applyOptions.mock.calls[0][0];
+      expect(typeof appliedOptions.localization.priceFormatter).toBe(
+        'function'
+      );
+      // Verify the percent formatter works correctly
+      const fmt = appliedOptions.localization.priceFormatter;
+      expect(fmt(42.5)).toBe('42.50%');
+    });
+
+    it('should pass through unknown formatter names as-is', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        localization: { priceFormatterName: 'nonexistent' },
+      } as never);
+
+      const createChartOptions = createChart.mock.calls[0][1];
+      // Should be left as-is (not resolved)
+      expect(createChartOptions.localization.priceFormatterName).toBe(
+        'nonexistent'
+      );
+    });
+
+    it('should include default timeFormatter in localization', () => {
+      createRenderer();
+      const createChartOptions = createChart.mock.calls[0][1];
+      expect(createChartOptions.localization).toBeDefined();
+      expect(createChartOptions.localization.timeFormatter).toBeInstanceOf(
+        Function
+      );
+    });
+
+    it('should format compact values correctly', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        localization: { priceFormatterName: 'compact' },
+      } as never);
+
+      const createChartOptions = createChart.mock.calls[0][1];
+      const fmt = createChartOptions.localization.priceFormatter;
+      expect(fmt(1500)).toBe('1.5K');
+      expect(fmt(2500000)).toBe('2.5M');
+      expect(fmt(3200000000)).toBe('3.2B');
+      expect(fmt(42.5)).toBe('42.50');
+    });
+
+    it('should format scientific values correctly', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {
+        localization: { priceFormatterName: 'scientific' },
+      } as never);
+
+      const createChartOptions = createChart.mock.calls[0][1];
+      const fmt = createChartOptions.localization.priceFormatter;
+      expect(fmt(12345)).toBe('1.23e+4');
+    });
+  });
+
+  describe('pane support', () => {
+    it('should pass paneIndex as third arg to addSeries', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+          paneIndex: 1,
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(lwc.LineSeries, {}, 1);
+    });
+
+    it('should pass undefined paneIndex when not specified', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+        },
+      ]);
+      expect(mockChart.addSeries).toHaveBeenCalledWith(
+        lwc.LineSeries,
+        {},
+        undefined
+      );
+    });
+
+    it('should apply stretch factors to panes', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'candle-1',
+          type: 'Candlestick',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+          paneIndex: 0,
+        },
+        {
+          id: 'hist-1',
+          type: 'Histogram',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T' } },
+          paneIndex: 1,
+        },
+      ]);
+
+      renderer.applyPaneStretchFactors([3, 1]);
+
+      expect(mockChart.panes).toHaveBeenCalled();
+      expect(mockPane.setStretchFactor).toHaveBeenCalledWith(3);
+      expect(mockPane2.setStretchFactor).toHaveBeenCalledWith(1);
+    });
+
+    it('should not throw when stretch factors exceed pane count', () => {
+      const renderer = createRenderer();
+      expect(() => renderer.applyPaneStretchFactors([3, 1, 2])).not.toThrow();
+    });
+  });
+
+  describe('dynamic price lines', () => {
+    it('should create a dynamic price line with initial price 0 for column-based lines', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+          priceLines: [
+            {
+              column: 'AvgPrice',
+              color: 'blue',
+              title: 'Average',
+            },
+          ],
+        },
+      ]);
+      expect(mockSeriesInstance.createPriceLine).toHaveBeenCalledTimes(1);
+      expect(mockSeriesInstance.createPriceLine).toHaveBeenCalledWith({
+        price: 0,
+        color: 'blue',
+        lineWidth: undefined,
+        lineStyle: undefined,
+        axisLabelVisible: undefined,
+        title: 'Average',
+      });
+    });
+
+    it('should update dynamic price line with last-row column value', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+          priceLines: [
+            {
+              column: 'AvgPrice',
+              color: 'blue',
+              title: 'Average',
+            },
+          ],
+        },
+      ]);
+
+      const columnData = new Map<string, unknown[]>();
+      columnData.set('AvgPrice', [100, 110, 120]);
+
+      renderer.updateDynamicPriceLines('line-1', columnData);
+      expect(mockPriceLine.applyOptions).toHaveBeenCalledWith({ price: 120 });
+    });
+
+    it('should not update static price lines on data change', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+          priceLines: [
+            {
+              price: 100,
+              color: 'gray',
+              title: 'Static',
+            },
+          ],
+        },
+      ]);
+
+      const columnData = new Map<string, unknown[]>();
+      columnData.set('SomeCol', [200, 300]);
+
+      renderer.updateDynamicPriceLines('line-1', columnData);
+      // No dynamic price lines registered, so applyOptions should not be called
+      // (the createPriceLine mock is called once for the static line, but
+      // applyOptions on the price line should not be called)
+      expect(mockPriceLine.applyOptions).not.toHaveBeenCalled();
+    });
+
+    it('should handle mixed static and dynamic price lines', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+          priceLines: [
+            { price: 50, color: 'gray', title: 'Static' },
+            { column: 'MaxPrice', color: 'green', title: 'High' },
+          ],
+        },
+      ]);
+
+      expect(mockSeriesInstance.createPriceLine).toHaveBeenCalledTimes(2);
+
+      const columnData = new Map<string, unknown[]>();
+      columnData.set('MaxPrice', [150, 160, 170]);
+
+      renderer.updateDynamicPriceLines('line-1', columnData);
+      expect(mockPriceLine.applyOptions).toHaveBeenCalledWith({ price: 170 });
+    });
+
+    it('should not throw when updating non-existent series', () => {
+      const renderer = createRenderer();
+      const columnData = new Map<string, unknown[]>();
+      columnData.set('AvgPrice', [100]);
+
+      expect(() =>
+        renderer.updateDynamicPriceLines('nonexistent', columnData)
+      ).not.toThrow();
+    });
+
+    it('should skip NaN values when updating dynamic price lines', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+          priceLines: [{ column: 'AvgPrice', color: 'blue', title: 'Avg' }],
+        },
+      ]);
+
+      const columnData = new Map<string, unknown[]>();
+      columnData.set('AvgPrice', [NaN]);
+
+      renderer.updateDynamicPriceLines('line-1', columnData);
+      expect(mockPriceLine.applyOptions).not.toHaveBeenCalled();
+    });
+
+    it('should clear dynamic price lines on reconfigure', () => {
+      const renderer = createRenderer();
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+          priceLines: [{ column: 'AvgPrice', color: 'blue', title: 'Avg' }],
+        },
+      ]);
+
+      // Reconfigure without dynamic price lines
+      renderer.configureSeries([
+        {
+          id: 'line-1',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+        },
+      ]);
+
+      const columnData = new Map<string, unknown[]>();
+      columnData.set('AvgPrice', [100]);
+
+      renderer.updateDynamicPriceLines('line-1', columnData);
+      // After reconfigure, no dynamic price lines should be registered
+      expect(mockPriceLine.applyOptions).not.toHaveBeenCalled();
+    });
+  });
+
+  describe('chart type selection', () => {
+    it('should call createChart for standard chart type', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {}, 'standard');
+      expect(createChart).toHaveBeenCalledTimes(1);
+      expect(createYieldCurveChart).not.toHaveBeenCalled();
+      expect(createOptionsChart).not.toHaveBeenCalled();
+    });
+
+    it('should call createYieldCurveChart for yieldCurve chart type', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {}, 'yieldCurve');
+      expect(createYieldCurveChart).toHaveBeenCalledTimes(1);
+      expect(createChart).not.toHaveBeenCalled();
+      expect(createOptionsChart).not.toHaveBeenCalled();
+    });
+
+    it('should call createOptionsChart for options chart type', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container, {}, 'options');
+      expect(createOptionsChart).toHaveBeenCalledTimes(1);
+      expect(createChart).not.toHaveBeenCalled();
+      expect(createYieldCurveChart).not.toHaveBeenCalled();
+    });
+
+    it('should default to createChart when no chart type specified', () => {
+      const container = document.createElement('div');
+      // eslint-disable-next-line no-new
+      new TradingViewChartRenderer(container);
+      expect(createChart).toHaveBeenCalledTimes(1);
+    });
+
+    it('should expose chart type via getChartType()', () => {
+      const container = document.createElement('div');
+      const standard = new TradingViewChartRenderer(container, {}, 'standard');
+      expect(standard.getChartType()).toBe('standard');
+
+      const yc = new TradingViewChartRenderer(container, {}, 'yieldCurve');
+      expect(yc.getChartType()).toBe('yieldCurve');
+
+      const opts = new TradingViewChartRenderer(container, {}, 'options');
+      expect(opts.getChartType()).toBe('options');
+    });
+  });
+
+  describe('event subscriptions', () => {
+    it('getSeriesIdForApi reverse-looks-up the series id', () => {
+      const renderer = createRenderer();
+      const configs: TvlSeriesConfig[] = [
+        {
+          id: 'line-x',
+          type: 'Line',
+          options: {},
+          dataMapping: { tableId: 0, columns: { time: 'T', value: 'V' } },
+        },
+      ];
+      renderer.configureSeries(configs);
+
+      // mockSeriesInstance is what addSeries returns and what gets stored.
+      expect(renderer.getSeriesIdForApi(mockSeriesInstance)).toBe('line-x');
+    });
+
+    it('getSeriesIdForApi returns undefined for an unknown series', () => {
+      const renderer = createRenderer();
+      const other = { setData: jest.fn() };
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      expect(renderer.getSeriesIdForApi(other as any)).toBeUndefined();
+    });
+
+    it('subscribeClick registers a handler and returns a working unsubscribe', () => {
+      const renderer = createRenderer();
+      const handler = jest.fn();
+      const unsub = renderer.subscribeClick(handler);
+
+      expect(mockChart.subscribeClick).toHaveBeenCalledWith(handler);
+      unsub();
+      expect(mockChart.unsubscribeClick).toHaveBeenCalledWith(handler);
+    });
+
+    it('subscribeDblClick registers a handler and returns a working unsubscribe', () => {
+      const renderer = createRenderer();
+      const handler = jest.fn();
+      const unsub = renderer.subscribeDblClick(handler);
+
+      expect(mockChart.subscribeDblClick).toHaveBeenCalledWith(handler);
+      unsub();
+      expect(mockChart.unsubscribeDblClick).toHaveBeenCalledWith(handler);
+    });
+  });
+
+  describe('tracking tooltip', () => {
+    // Regression: the figure's chartOptions (incl. `tooltip`) reach the
+    // renderer via applyOptions, NOT the constructor. hasTooltip() must read
+    // those merged options, else setupTooltip() is a no-op and the tooltip
+    // element is never created (caught originally only by the e2e suite).
+    it('hasTooltip reflects tooltip options applied via applyOptions', () => {
+      const renderer = createRenderer();
+      expect(renderer.hasTooltip()).toBe(false);
+      renderer.applyOptions({
+        tooltip: { visible: true },
+      } as never);
+      expect(renderer.hasTooltip()).toBe(true);
+    });
+
+    it('setupTooltip creates the tooltip element and subscribes to crosshair moves', () => {
+      const container = document.createElement('div');
+      const renderer = new TradingViewChartRenderer(container);
+      renderer.applyOptions({ tooltip: { visible: true } } as never);
+
+      const cleanup = renderer.setupTooltip();
+      expect(container.querySelector('.tvl-tooltip')).not.toBeNull();
+      expect(mockChart.subscribeCrosshairMove).toHaveBeenCalledTimes(1);
+
+      cleanup();
+      expect(container.querySelector('.tvl-tooltip')).toBeNull();
+      expect(mockChart.unsubscribeCrosshairMove).toHaveBeenCalledTimes(1);
+    });
+
+    it('setupTooltip is a no-op when no tooltip is configured', () => {
+      const container = document.createElement('div');
+      const renderer = new TradingViewChartRenderer(container);
+      renderer.setupTooltip();
+      expect(container.querySelector('.tvl-tooltip')).toBeNull();
+      expect(mockChart.subscribeCrosshairMove).not.toHaveBeenCalled();
+    });
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewColors.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewColors.test.ts
new file mode 100644
index 000000000..6ce162951
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewColors.test.ts
@@ -0,0 +1,65 @@
+import { resolveColor, resolveColorsDeep } from '../TradingViewColors';
+
+describe('resolveColor', () => {
+  it('passes through hex colors unchanged', () => {
+    expect(resolveColor('#1f8a70')).toBe('#1f8a70');
+  });
+
+  it('passes through rgb/rgba unchanged', () => {
+    expect(resolveColor('rgba(255, 0, 0, 0.5)')).toBe('rgba(255, 0, 0, 0.5)');
+  });
+
+  it('passes through "transparent" unchanged', () => {
+    expect(resolveColor('transparent')).toBe('transparent');
+  });
+
+  it('passes through named CSS colors unchanged', () => {
+    expect(resolveColor('crimson')).toBe('crimson');
+  });
+
+  it('transforms a DH theme color name out of its bare form', () => {
+    // jsdom has no real theme stylesheet, so we only assert the bare name was
+    // recognized as a DH token (the function tried to resolve it). Full
+    // resolution to a hex/rgba value happens against the real DOM at runtime.
+    expect(resolveColor('seafoam-500')).not.toBe('seafoam-500');
+  });
+
+  it('returns undefined / empty strings unchanged', () => {
+    expect(resolveColor(undefined)).toBeUndefined();
+    expect(resolveColor('')).toBe('');
+  });
+});
+
+describe('resolveColorsDeep', () => {
+  it('resolves a single nested color key', () => {
+    const opts = { layout: { textColor: '#abc' } };
+    resolveColorsDeep(opts);
+    expect(opts.layout.textColor).toBe('#abc');
+  });
+
+  it('walks nested objects and arrays', () => {
+    const opts = {
+      layout: { textColor: 'seafoam-500' },
+      lines: [{ color: '#fff' }, { color: 'accent-300' }],
+    };
+    resolveColorsDeep(opts);
+    expect(opts.layout.textColor).not.toBe('seafoam-500');
+    expect(opts.lines[0].color).toBe('#fff');
+    expect(opts.lines[1].color).not.toBe('accent-300');
+  });
+
+  it('treats every entry in a string[] as a color (e.g. colorway)', () => {
+    const palette: string[] = ['#1f77b4', 'seafoam-500', 'transparent'];
+    resolveColorsDeep(palette);
+    expect(palette[0]).toBe('#1f77b4');
+    expect(palette[1]).not.toBe('seafoam-500');
+    expect(palette[2]).toBe('transparent');
+  });
+
+  it('leaves non-color keys alone', () => {
+    const opts = { title: 'seafoam-500', count: 5 } as Record<string, unknown>;
+    resolveColorsDeep(opts);
+    expect(opts.title).toBe('seafoam-500');
+    expect(opts.count).toBe(5);
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewEventPayload.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewEventPayload.test.ts
new file mode 100644
index 000000000..7cbf41d59
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewEventPayload.test.ts
@@ -0,0 +1,283 @@
+import type {
+  MouseEventParams,
+  ISeriesApi,
+  SeriesType,
+} from 'lightweight-charts';
+import { buildPressEventPayload } from '../TradingViewEventPayload';
+
+// Lightweight fake ISeriesApi objects. The payload builder only uses them as
+// identity keys for the id/title resolvers.
+type FakeSeries = {
+  title?: string;
+};
+
+function asSeries(s: FakeSeries): ISeriesApi<SeriesType> {
+  return s as unknown as ISeriesApi<SeriesType>;
+}
+
+/** Build a getSeriesId resolver backed by a Map you control. */
+function makeResolver(
+  entries: Array<[FakeSeries, string]>
+): (s: ISeriesApi<SeriesType>) => string | undefined {
+  const map = new Map<FakeSeries, string>(entries);
+  return (s: ISeriesApi<SeriesType>) =>
+    map.get(s as unknown as FakeSeries) ?? undefined;
+}
+
+function makeTitleResolver(): (
+  s: ISeriesApi<SeriesType>
+) => string | undefined {
+  return (s: ISeriesApi<SeriesType>) =>
+    (s as unknown as FakeSeries).title ?? undefined;
+}
+
+function buildPayload(
+  type: 'press' | 'doublePress',
+  params: MouseEventParams,
+  getSeriesId: (s: ISeriesApi<SeriesType>) => string | undefined,
+  timeZone = 'UTC'
+) {
+  return buildPressEventPayload(
+    type,
+    params,
+    getSeriesId,
+    makeTitleResolver(),
+    timeZone
+  );
+}
+
+/** An empty resolver (resolves nothing). */
+function resolver0(): (s: ISeriesApi<SeriesType>) => string | undefined {
+  return () => undefined;
+}
+
+describe('buildPressEventPayload', () => {
+  describe('seriesData', () => {
+    it('maps line value to { value } and OHLC to an object, skips unknown', () => {
+      const seriesLine: FakeSeries = {};
+      const seriesOhlc: FakeSeries = {};
+      const seriesUnknown: FakeSeries = {};
+      const resolver = makeResolver([
+        [seriesLine, 'line-1'],
+        [seriesOhlc, 'ohlc-1'],
+        // seriesUnknown intentionally not registered
+      ]);
+      const seriesData = new Map<ISeriesApi<SeriesType>, unknown>([
+        [asSeries(seriesLine), { value: 42.5 }],
+        [asSeries(seriesOhlc), { open: 1, high: 4, low: 0.5, close: 3 }],
+        [asSeries(seriesUnknown), { value: 99 }],
+      ]);
+      const params = { seriesData } as unknown as MouseEventParams;
+
+      const payload = buildPayload('press', params, resolver);
+      expect(payload.seriesData).toEqual({
+        'line-1': { value: 42.5 },
+        'ohlc-1': { open: 1, high: 4, low: 0.5, close: 3 },
+      });
+    });
+
+    it('keys seriesData by the series title when present', () => {
+      const series: FakeSeries = { title: 'AAA' };
+      const resolver = makeResolver([[series, 'series_0_AAA']]);
+      const seriesData = new Map<ISeriesApi<SeriesType>, unknown>([
+        [asSeries(series), { value: 7 }],
+      ]);
+      const params = { seriesData } as unknown as MouseEventParams;
+
+      const payload = buildPayload('press', params, resolver);
+      expect(payload.seriesData).toEqual({ AAA: { value: 7 } });
+    });
+
+    it('skips whitespace items with neither value nor OHLC', () => {
+      const series: FakeSeries = {};
+      const resolver = makeResolver([[series, 'a']]);
+      const seriesData = new Map<ISeriesApi<SeriesType>, unknown>([
+        [asSeries(series), { time: 123 }],
+      ]);
+      const params = { seriesData } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver);
+      expect(payload.seriesData).toEqual({});
+    });
+  });
+
+  describe('hovered series', () => {
+    it('emits friendly id and stable id from hoveredInfo.series', () => {
+      const series: FakeSeries = { title: 'AAA' };
+      const resolver = makeResolver([[series, 'series_0_AAA']]);
+      const params = {
+        seriesData: new Map(),
+        hoveredInfo: { series: asSeries(series) },
+      } as unknown as MouseEventParams;
+
+      const payload = buildPayload('press', params, resolver);
+      expect(payload.hoveredSeries).toBe('AAA');
+      expect(payload.hoveredSeriesId).toBe('series_0_AAA');
+    });
+
+    it('falls back to the stable id as the friendly key when no title', () => {
+      const series: FakeSeries = {};
+      const resolver = makeResolver([[series, 'series_0']]);
+      const params = {
+        seriesData: new Map(),
+        hoveredInfo: { series: asSeries(series) },
+      } as unknown as MouseEventParams;
+
+      const payload = buildPayload('press', params, resolver);
+      expect(payload.hoveredSeries).toBe('series_0');
+      expect(payload.hoveredSeriesId).toBe('series_0');
+    });
+
+    it('omits hovered fields when no series is hovered', () => {
+      const params = {
+        seriesData: new Map(),
+      } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect('hoveredSeries' in payload).toBe(false);
+      expect('hoveredSeriesId' in payload).toBe(false);
+    });
+  });
+
+  describe('point / logical / paneIndex', () => {
+    it('passes through point coordinates', () => {
+      const params = {
+        seriesData: new Map(),
+        point: { x: 100, y: 50 },
+      } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect(payload.point).toEqual({ x: 100, y: 50 });
+    });
+
+    it('omits point when outside the chart', () => {
+      const params = { seriesData: new Map() } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect('point' in payload).toBe(false);
+    });
+
+    it('passes through logical index', () => {
+      const params = {
+        seriesData: new Map(),
+        logical: 1234,
+      } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect(payload.logical).toBe(1234);
+    });
+
+    it('uses params.paneIndex, then hoveredInfo.paneIndex', () => {
+      const a = {
+        seriesData: new Map(),
+        paneIndex: 2,
+      } as unknown as MouseEventParams;
+      expect(buildPayload('press', a, resolver0()).paneIndex).toBe(2);
+
+      const b = {
+        seriesData: new Map(),
+        hoveredInfo: { paneIndex: 1 },
+      } as unknown as MouseEventParams;
+      expect(buildPayload('press', b, resolver0()).paneIndex).toBe(1);
+    });
+  });
+
+  describe('time conversion', () => {
+    it('converts the crosshair time (UTC seconds) to nanoseconds', () => {
+      const params = {
+        seriesData: new Map(),
+        time: 1700000000,
+      } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect(payload.timeNs).toBe(1700000000 * 1e9);
+    });
+
+    it('reverses TZ shift for a non-UTC zone', () => {
+      const params = {
+        seriesData: new Map(),
+        time: 1700000000,
+      } as unknown as MouseEventParams;
+      const ny = buildPayload('press', params, resolver0(), 'America/New_York');
+      const utc = buildPayload('press', params, resolver0(), 'UTC');
+      const expectedDiffSec = 5 * 3600; // NY is UTC-5 in winter
+      expect((utc.timeNs as number) - (ny.timeNs as number)).toBe(
+        -expectedDiffSec * 1e9
+      );
+    });
+
+    it('omits timeNs when time is undefined (outside data range)', () => {
+      const params = { seriesData: new Map() } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect('timeNs' in payload).toBe(false);
+    });
+
+    it('carries the display timeZone alongside timeNs', () => {
+      const params = {
+        seriesData: new Map(),
+        time: 1700000000,
+      } as unknown as MouseEventParams;
+      const payload = buildPayload(
+        'press',
+        params,
+        resolver0(),
+        'America/New_York'
+      );
+      expect(payload.timeZone).toBe('America/New_York');
+    });
+
+    it('omits timeZone when none is supplied (empty string)', () => {
+      const params = {
+        seriesData: new Map(),
+        time: 1700000000,
+      } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0(), '');
+      expect('timeZone' in payload).toBe(false);
+    });
+  });
+
+  describe('modifier keys', () => {
+    it('extracts modifiers from sourceEvent', () => {
+      const params = {
+        seriesData: new Map(),
+        sourceEvent: {
+          shiftKey: true,
+          ctrlKey: false,
+          metaKey: true,
+          altKey: false,
+        },
+      } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect(payload.shiftKey).toBe(true);
+      expect(payload.ctrlKey).toBe(false);
+      expect(payload.metaKey).toBe(true);
+      expect(payload.altKey).toBe(false);
+    });
+
+    it('defaults all modifiers to false when sourceEvent missing', () => {
+      const params = { seriesData: new Map() } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect(payload.shiftKey).toBe(false);
+      expect(payload.ctrlKey).toBe(false);
+      expect(payload.metaKey).toBe(false);
+      expect(payload.altKey).toBe(false);
+    });
+  });
+
+  describe('empty-area press', () => {
+    it('produces a minimal shape with type, empty seriesData + modifiers', () => {
+      const params = { seriesData: new Map() } as unknown as MouseEventParams;
+      const payload = buildPayload('press', params, resolver0());
+      expect(payload).toEqual({
+        type: 'press',
+        seriesData: {},
+        shiftKey: false,
+        ctrlKey: false,
+        metaKey: false,
+        altKey: false,
+      });
+    });
+  });
+
+  describe('type passthrough', () => {
+    it('carries doublePress through', () => {
+      const params = { seriesData: new Map() } as unknown as MouseEventParams;
+      const payload = buildPayload('doublePress', params, resolver0());
+      expect(payload.type).toBe('doublePress');
+    });
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewTheme.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewTheme.test.ts
new file mode 100644
index 000000000..ab1f862af
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewTheme.test.ts
@@ -0,0 +1,75 @@
+import {
+  chartThemeToOptions,
+  getOhlcColors,
+  getColorway,
+} from '../TradingViewTheme';
+import type { TvlChartTheme } from '../TradingViewTheme';
+
+const mockTheme: TvlChartTheme = {
+  paperBgColor: '#1a171a',
+  plotBgColor: '#2d2a2e',
+  textColor: '#f0f0ee',
+  gridColor: '#3d3a3e',
+  lineColor: '#5b5a5c',
+  zeroLineColor: '#7b797e',
+  fontFamily: '"Fira Sans", sans-serif',
+  ohlcIncreasing: '#26a69a',
+  ohlcDecreasing: '#ef5350',
+  colorway: ['#4878d0', '#6acc64', '#d5bb67'],
+};
+
+describe('chartThemeToOptions', () => {
+  it('should map paperBgColor to layout background', () => {
+    const options = chartThemeToOptions(mockTheme);
+    expect(options.layout?.background).toEqual({
+      type: expect.anything(),
+      color: '#1a171a',
+    });
+  });
+
+  it('should map textColor to layout textColor', () => {
+    const options = chartThemeToOptions(mockTheme);
+    expect((options.layout as Record<string, unknown>)?.textColor).toBe(
+      '#f0f0ee'
+    );
+  });
+
+  it('should map fontFamily to layout fontFamily', () => {
+    const options = chartThemeToOptions(mockTheme);
+    expect((options.layout as Record<string, unknown>)?.fontFamily).toBe(
+      '"Fira Sans", sans-serif'
+    );
+  });
+
+  it('should map gridColor to grid lines', () => {
+    const options = chartThemeToOptions(mockTheme);
+    expect(options.grid?.vertLines).toEqual({ color: '#3d3a3e' });
+    expect(options.grid?.horzLines).toEqual({ color: '#3d3a3e' });
+  });
+
+  it('should map lineColor to scale borders', () => {
+    const options = chartThemeToOptions(mockTheme);
+    expect(options.rightPriceScale).toEqual({ borderColor: '#5b5a5c' });
+    expect(options.timeScale).toEqual({ borderColor: '#5b5a5c' });
+  });
+
+  it('should map gridColor to crosshair', () => {
+    const options = chartThemeToOptions(mockTheme);
+    expect(options.crosshair?.vertLine).toEqual({ color: '#3d3a3e' });
+    expect(options.crosshair?.horzLine).toEqual({ color: '#3d3a3e' });
+  });
+});
+
+describe('getOhlcColors', () => {
+  it('should return ohlc increasing and decreasing colors', () => {
+    const colors = getOhlcColors(mockTheme);
+    expect(colors.upColor).toBe('#26a69a');
+    expect(colors.downColor).toBe('#ef5350');
+  });
+});
+
+describe('getColorway', () => {
+  it('should return the colorway array', () => {
+    expect(getColorway(mockTheme)).toEqual(['#4878d0', '#6acc64', '#d5bb67']);
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewTooltip.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewTooltip.test.ts
new file mode 100644
index 000000000..a4b936602
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewTooltip.test.ts
@@ -0,0 +1,280 @@
+import { TradingViewTooltip } from '../TradingViewTooltip';
+import type { TradingViewTooltipDeps } from '../TradingViewTooltip';
+
+/**
+ * Minimal stand-in for an ISeriesApi. Only the members the tooltip touches
+ * are implemented; cast to any at the call boundary.
+ */
+function makeSeries(opts: {
+  title?: string;
+  formatted?: string;
+  coordinate?: number | null;
+}) {
+  return {
+    options: () => ({ title: opts.title }),
+    priceFormatter: () => ({
+      format: (v: number) => opts.formatted ?? String(v),
+    }),
+    priceToCoordinate: () => opts.coordinate ?? null,
+  };
+}
+
+/** A container whose client size and the tooltip's offset size are stubbed. */
+function makeContainer(clientWidth = 800, clientHeight = 600): HTMLElement {
+  const container = document.createElement('div');
+  Object.defineProperty(container, 'clientWidth', { value: clientWidth });
+  Object.defineProperty(container, 'clientHeight', { value: clientHeight });
+  document.body.appendChild(container);
+  return container;
+}
+
+/** Build crosshair params with a seriesData Map keyed by the series stubs. */
+function makeParams(
+  entries: Array<[unknown, unknown]>,
+  overrides: Record<string, unknown> = {}
+): any {
+  return {
+    time: 1700000000,
+    point: { x: 100, y: 100 },
+    seriesData: new Map(entries),
+    ...overrides,
+  };
+}
+
+function deps(
+  container: HTMLElement,
+  series: Array<{ api: unknown; id: string; color?: string }>,
+  options: TradingViewTooltipDeps['options'] = { visible: true }
+): TradingViewTooltipDeps {
+  const byApi = new Map(series.map(s => [s.api, s]));
+  return {
+    container,
+    getSeriesId: s => byApi.get(s)?.id,
+    getSeriesColor: id => series.find(s => s.id === id)?.color,
+    formatTime: t => `T:${t}`,
+    options,
+  };
+}
+
+function tooltipEl(container: HTMLElement): HTMLElement {
+  return container.querySelector('.tvl-tooltip') as HTMLElement;
+}
+
+describe('TradingViewTooltip', () => {
+  afterEach(() => {
+    document.body.innerHTML = '';
+  });
+
+  it('creates a hidden tooltip element in the container', () => {
+    const container = makeContainer();
+    // eslint-disable-next-line no-new
+    new TradingViewTooltip(deps(container, []));
+    const el = tooltipEl(container);
+    expect(el).not.toBeNull();
+    expect(el.style.display).toBe('none');
+    expect(el.querySelector('.tvl-tooltip-title')).not.toBeNull();
+    expect(el.querySelector('.tvl-tooltip-value')).not.toBeNull();
+    expect(el.querySelector('.tvl-tooltip-date')).not.toBeNull();
+  });
+
+  it.each([
+    ['no point', { point: undefined }],
+    ['no time', { time: undefined }],
+    ['x out of bounds', { point: { x: 5000, y: 100 } }],
+    ['y out of bounds', { point: { x: 100, y: 5000 } }],
+  ])('hides when %s', (_label, override) => {
+    const container = makeContainer();
+    const api = makeSeries({ title: 'A', formatted: '1.00' });
+    const tt = new TradingViewTooltip(deps(container, [{ api, id: 'a' }]));
+    tt.handleCrosshairMove(makeParams([[api, { value: 1 }]], override));
+    expect(tooltipEl(container).style.display).toBe('none');
+  });
+
+  it('renders the hovered series title, value, and date', () => {
+    const container = makeContainer();
+    const api = makeSeries({ title: 'Acme', formatted: '42.50' });
+    const tt = new TradingViewTooltip(
+      deps(container, [{ api, id: 'a', color: '#ff0000' }])
+    );
+    tt.handleCrosshairMove(
+      makeParams([[api, { value: 42.5 }]], {
+        hoveredInfo: { sourceKind: 'series', series: api },
+      })
+    );
+    const el = tooltipEl(container);
+    expect(el.style.display).toBe('block');
+    expect(el.querySelector('.tvl-tooltip-title')?.textContent).toBe('Acme');
+    expect(el.querySelector('.tvl-tooltip-value')?.textContent).toBe('42.50');
+    expect(el.querySelector('.tvl-tooltip-date')?.textContent).toBe(
+      'T:1700000000'
+    );
+    // Title tinted with the series color.
+    expect(
+      (el.querySelector('.tvl-tooltip-title') as HTMLElement).style.color
+    ).toBe('rgb(255, 0, 0)');
+    // Test seam for Playwright.
+    expect(el.getAttribute('data-tvl-tooltip')).toBe(
+      'Acme | 42.50 | T:1700000000'
+    );
+  });
+
+  it('falls back to series id when the series is untitled', () => {
+    const container = makeContainer();
+    const api = makeSeries({ formatted: '1' });
+    const tt = new TradingViewTooltip(
+      deps(container, [{ api, id: 'series_0' }])
+    );
+    tt.handleCrosshairMove(
+      makeParams([[api, { value: 1 }]], {
+        hoveredInfo: { sourceKind: 'series', series: api },
+      })
+    );
+    expect(
+      tooltipEl(container).querySelector('.tvl-tooltip-title')?.textContent
+    ).toBe('series_0');
+  });
+
+  it('uses the close value for OHLC series', () => {
+    const container = makeContainer();
+    const api = makeSeries({ title: 'C', formatted: '99' });
+    const tt = new TradingViewTooltip(deps(container, [{ api, id: 'c' }]));
+    tt.handleCrosshairMove(
+      makeParams([[api, { open: 90, high: 100, low: 80, close: 99 }]], {
+        hoveredInfo: { sourceKind: 'series', series: api },
+      })
+    );
+    expect(
+      tooltipEl(container).querySelector('.tvl-tooltip-value')?.textContent
+    ).toBe('99');
+  });
+
+  it('picks the nearest series by price when nothing is hovered', () => {
+    const container = makeContainer();
+    // near's value maps to y=105 (5px from cursor y=100); far maps to y=400.
+    const near = makeSeries({ title: 'near', coordinate: 105, formatted: 'N' });
+    const far = makeSeries({ title: 'far', coordinate: 400, formatted: 'F' });
+    const tt = new TradingViewTooltip(
+      deps(container, [
+        { api: near, id: 'near' },
+        { api: far, id: 'far' },
+      ])
+    );
+    tt.handleCrosshairMove(
+      makeParams([
+        [far, { value: 10 }],
+        [near, { value: 20 }],
+      ])
+    );
+    expect(
+      tooltipEl(container).querySelector('.tvl-tooltip-title')?.textContent
+    ).toBe('near');
+  });
+
+  it('picks the vertically nearest series even when another is hovered', () => {
+    const container = makeContainer();
+    // cursor y=100. hovered maps to y=400 (far); near maps to y=105 (close).
+    const hovered = makeSeries({
+      title: 'hovered',
+      coordinate: 400,
+      formatted: 'H',
+    });
+    const near = makeSeries({ title: 'near', coordinate: 105, formatted: 'N' });
+    const tt = new TradingViewTooltip(
+      deps(container, [
+        { api: hovered, id: 'hovered' },
+        { api: near, id: 'near' },
+      ])
+    );
+    tt.handleCrosshairMove(
+      makeParams(
+        [
+          [hovered, { value: 10 }],
+          [near, { value: 20 }],
+        ],
+        // LWC reports `hovered` as the hovered series, but `near` sits closer
+        // to the cursor's y — the tooltip must track `near`.
+        { hoveredInfo: { sourceKind: 'series', series: hovered } }
+      )
+    );
+    expect(
+      tooltipEl(container).querySelector('.tvl-tooltip-title')?.textContent
+    ).toBe('near');
+  });
+
+  it('honors valuePrecision over the series formatter', () => {
+    const container = makeContainer();
+    const api = makeSeries({ title: 'P', formatted: 'IGNORED' });
+    const tt = new TradingViewTooltip(
+      deps(container, [{ api, id: 'p' }], { visible: true, valuePrecision: 3 })
+    );
+    tt.handleCrosshairMove(
+      makeParams([[api, { value: 1.23456 }]], {
+        hoveredInfo: { sourceKind: 'series', series: api },
+      })
+    );
+    expect(
+      tooltipEl(container).querySelector('.tvl-tooltip-value')?.textContent
+    ).toBe('1.235');
+  });
+
+  it('hides lines disabled via options', () => {
+    const container = makeContainer();
+    const api = makeSeries({ title: 'X', formatted: '1' });
+    const tt = new TradingViewTooltip(
+      deps(container, [{ api, id: 'x' }], {
+        visible: true,
+        showDate: false,
+        showValue: false,
+      })
+    );
+    tt.handleCrosshairMove(
+      makeParams([[api, { value: 1 }]], {
+        hoveredInfo: { sourceKind: 'series', series: api },
+      })
+    );
+    const el = tooltipEl(container);
+    expect(
+      (el.querySelector('.tvl-tooltip-date') as HTMLElement).style.display
+    ).toBe('none');
+    expect(
+      (el.querySelector('.tvl-tooltip-value') as HTMLElement).style.display
+    ).toBe('none');
+    expect(
+      (el.querySelector('.tvl-tooltip-title') as HTMLElement).style.display
+    ).not.toBe('none');
+  });
+
+  it('positions near the cursor, flipping when it would overflow', () => {
+    const container = makeContainer(200, 200);
+    const api = makeSeries({ title: 'X', formatted: '1' });
+    const tt = new TradingViewTooltip(deps(container, [{ api, id: 'x' }]));
+    const el = tooltipEl(container);
+    Object.defineProperty(el, 'offsetWidth', {
+      value: 100,
+      configurable: true,
+    });
+    Object.defineProperty(el, 'offsetHeight', {
+      value: 80,
+      configurable: true,
+    });
+    // Cursor near the right/bottom edge → tooltip flips to the other side.
+    tt.handleCrosshairMove(
+      makeParams([[api, { value: 1 }]], {
+        point: { x: 180, y: 180 },
+        hoveredInfo: { sourceKind: 'series', series: api },
+      })
+    );
+    // left = 180 + 15 = 195 > (200 - 100) → flip to 180 - 15 - 100 = 65
+    expect(el.style.left).toBe('65px');
+    // top = 180 + 15 = 195 > (200 - 80) → flip to 180 - 80 - 15 = 85
+    expect(el.style.top).toBe('85px');
+  });
+
+  it('removes the element on destroy', () => {
+    const container = makeContainer();
+    const tt = new TradingViewTooltip(deps(container, []));
+    expect(tooltipEl(container)).not.toBeNull();
+    tt.destroy();
+    expect(tooltipEl(container)).toBeNull();
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewUtils.test.ts b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewUtils.test.ts
new file mode 100644
index 000000000..51b62dfc2
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/__tests__/TradingViewUtils.test.ts
@@ -0,0 +1,760 @@
+import type { TvlMarkerSpec, TvlSeriesConfig } from '../TradingViewTypes';
+import {
+  convertTime,
+  transformTableData,
+  getRequiredColumns,
+  getAllColumnsForTable,
+  buildMarkersFromTableData,
+} from '../TradingViewUtils';
+
+describe('convertTime', () => {
+  const utcSeconds = 1704067200; // 2024-01-01T00:00:00Z
+
+  it('should apply explicit timezone offset for America/New_York', () => {
+    // 2024-01-01 is EST (UTC-5), so offset = -5 * 3600 = -18000
+    const result = convertTime(utcSeconds, 'America/New_York');
+    expect(result).toBe(utcSeconds - 5 * 3600);
+  });
+
+  it('should apply explicit timezone offset for Asia/Tokyo', () => {
+    // Tokyo is UTC+9, so offset = +9 * 3600
+    const result = convertTime(utcSeconds, 'Asia/Tokyo');
+    expect(result).toBe(utcSeconds + 9 * 3600);
+  });
+
+  it('should fall back to browser local timezone when no timezone provided', () => {
+    const offsetSeconds = -(
+      new Date(utcSeconds * 1000).getTimezoneOffset() * 60
+    );
+    const expected = utcSeconds + offsetSeconds;
+    expect(convertTime(utcSeconds)).toBe(expected);
+  });
+
+  it('should convert milliseconds to offset-adjusted seconds', () => {
+    const result = convertTime(utcSeconds * 1000, 'UTC');
+    expect(result).toBe(utcSeconds); // UTC offset is 0
+  });
+
+  it('should convert nanoseconds to offset-adjusted seconds', () => {
+    const result = convertTime(utcSeconds * 1e9, 'UTC');
+    expect(result).toBe(utcSeconds);
+  });
+
+  it('should handle a Date object', () => {
+    const date = new Date('2024-01-01T00:00:00Z');
+    const result = convertTime(date, 'UTC');
+    expect(result).toBe(utcSeconds);
+  });
+
+  it('should handle a string timestamp', () => {
+    const result = convertTime('2024-01-01T00:00:00Z', 'UTC');
+    expect(result).toBe(utcSeconds);
+  });
+
+  it('should return 0 for null/undefined', () => {
+    expect(convertTime(null)).toBe(0);
+    expect(convertTime(undefined)).toBe(0);
+  });
+
+  it('should return 0 for unsupported types like boolean', () => {
+    expect(convertTime(true)).toBe(0);
+  });
+
+  it('should produce consistent results for same instant in different formats', () => {
+    const tz = 'America/Chicago'; // UTC-6 in winter
+    const fromSeconds = convertTime(utcSeconds, tz);
+    const fromMillis = convertTime(utcSeconds * 1000, tz);
+    const fromNanos = convertTime(utcSeconds * 1e9, tz);
+    const fromDate = convertTime(new Date('2024-01-01T00:00:00Z'), tz);
+    expect(fromSeconds).toBe(fromMillis);
+    expect(fromMillis).toBe(fromNanos);
+    expect(fromNanos).toBe(fromDate);
+  });
+
+  it('should use cached formatter for same timezone (performance)', () => {
+    // Call twice with same timezone — second call should be fast (cached)
+    const r1 = convertTime(utcSeconds, 'Europe/London');
+    const r2 = convertTime(utcSeconds + 86400, 'Europe/London');
+    // Both should produce valid results (not testing speed, just correctness)
+    expect(typeof r1).toBe('number');
+    expect(typeof r2).toBe('number');
+    expect(r1).not.toBe(r2); // Different input → different output
+  });
+});
+
+describe('transformTableData', () => {
+  // In production, time column values are pre-converted by the model's
+  // timeTranslator (TZ-adjusted epoch seconds). Tests use raw epoch
+  // seconds directly, matching what the model would produce for UTC.
+
+  describe('OHLC series (Candlestick)', () => {
+    const ohlcConfig: TvlSeriesConfig = {
+      id: 'candle-1',
+      type: 'Candlestick',
+      options: {},
+      dataMapping: {
+        tableId: 0,
+        columns: {
+          time: 'Timestamp',
+          open: 'Open',
+          high: 'High',
+          low: 'Low',
+          close: 'Close',
+        },
+      },
+    };
+
+    it('should produce OHLC data points', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1704067200, 1704153600]],
+        ['Open', [100, 105]],
+        ['High', [110, 115]],
+        ['Low', [95, 100]],
+        ['Close', [105, 110]],
+      ]);
+
+      const result = transformTableData(ohlcConfig, columnData);
+      expect(result).toEqual([
+        {
+          time: 1704067200,
+          open: 100,
+          high: 110,
+          low: 95,
+          close: 105,
+        },
+        {
+          time: 1704153600,
+          open: 105,
+          high: 115,
+          low: 100,
+          close: 110,
+        },
+      ]);
+    });
+
+    it('should return empty array when time column is missing', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Open', [100]],
+        ['High', [110]],
+      ]);
+
+      const result = transformTableData(ohlcConfig, columnData);
+      expect(result).toEqual([]);
+    });
+
+    it('should handle object values by converting them to numbers', () => {
+      // Simulate Deephaven BigDecimal-like objects with valueOf
+      const bigVal = { valueOf: () => 123.45 };
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1704067200]],
+        ['Open', [bigVal]],
+        ['High', [bigVal]],
+        ['Low', [bigVal]],
+        ['Close', [bigVal]],
+      ]);
+
+      const result = transformTableData(ohlcConfig, columnData);
+      expect(result).toHaveLength(1);
+      // Object values should be converted via Number()
+      expect((result[0] as Record<string, unknown>).open).toBe(Number(bigVal));
+    });
+
+    it('should handle empty column data', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', []],
+        ['Open', []],
+        ['High', []],
+        ['Low', []],
+        ['Close', []],
+      ]);
+
+      const result = transformTableData(ohlcConfig, columnData);
+      expect(result).toEqual([]);
+    });
+  });
+
+  describe('value-based series (Line, Area)', () => {
+    const lineConfig: TvlSeriesConfig = {
+      id: 'line-1',
+      type: 'Line',
+      options: {},
+      dataMapping: {
+        tableId: 0,
+        columns: {
+          time: 'Timestamp',
+          value: 'Price',
+        },
+      },
+    };
+
+    it('should produce value data points', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1704067200, 1704153600]],
+        ['Price', [100.5, 101.3]],
+      ]);
+
+      const result = transformTableData(lineConfig, columnData);
+      expect(result).toEqual([
+        { time: 1704067200, value: 100.5 },
+        { time: 1704153600, value: 101.3 },
+      ]);
+    });
+
+    it('should skip missing non-time columns gracefully', () => {
+      // Only time column present, value column missing from map
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1704067200]],
+      ]);
+
+      const result = transformTableData(lineConfig, columnData);
+      expect(result).toEqual([{ time: 1704067200 }]);
+    });
+  });
+
+  describe('startIndex parameter', () => {
+    const config: TvlSeriesConfig = {
+      id: 'line-si',
+      type: 'Line',
+      options: {},
+      dataMapping: {
+        tableId: 0,
+        columns: { time: 'Timestamp', value: 'Val' },
+      },
+    };
+
+    it('should only process rows from startIndex onward', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1000, 2000, 3000, 4000]],
+        ['Val', [10, 20, 30, 40]],
+      ]);
+
+      const result = transformTableData(config, columnData, undefined, 2);
+      expect(result).toEqual([
+        { time: 3000, value: 30 },
+        { time: 4000, value: 40 },
+      ]);
+    });
+
+    it('should return all rows when startIndex is 0', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1000, 2000]],
+        ['Val', [10, 20]],
+      ]);
+
+      const all = transformTableData(config, columnData);
+      const withZero = transformTableData(config, columnData, undefined, 0);
+      expect(all).toEqual(withZero);
+    });
+
+    it('should return empty array when startIndex exceeds length', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1000, 2000]],
+        ['Val', [10, 20]],
+      ]);
+
+      const result = transformTableData(config, columnData, undefined, 100);
+      expect(result).toEqual([]);
+    });
+
+    it('should clamp negative startIndex to 0', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1000, 2000]],
+        ['Val', [10, 20]],
+      ]);
+
+      const result = transformTableData(config, columnData, undefined, -5);
+      expect(result).toHaveLength(2);
+    });
+  });
+
+  describe('pre-converted time values', () => {
+    const config: TvlSeriesConfig = {
+      id: 'line-2',
+      type: 'Line',
+      options: {},
+      dataMapping: {
+        tableId: 0,
+        columns: {
+          time: 'Timestamp',
+          value: 'Val',
+        },
+      },
+    };
+
+    it('should read pre-converted epoch seconds directly', () => {
+      // Model's timeTranslator already produced TZ-adjusted seconds
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1704067200]],
+        ['Val', [42]],
+      ]);
+
+      const result = transformTableData(config, columnData);
+      expect(result).toEqual([{ time: 1704067200, value: 42 }]);
+    });
+
+    it('should floor fractional seconds', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [1704067200.999]],
+        ['Val', [42]],
+      ]);
+
+      const result = transformTableData(config, columnData);
+      expect(result).toEqual([{ time: 1704067200, value: 42 }]);
+    });
+
+    it('should skip rows with non-numeric time values', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', ['not-a-number', 1704067200, null]],
+        ['Val', [42, 43, 44]],
+      ]);
+
+      // Non-numeric times (string, null) are skipped at every index, not
+      // just i > 0. Otherwise an unparseable first row produces a phantom
+      // point at epoch (1970) that the chart draws as a near-vertical line
+      // entering from the left edge.
+      const result = transformTableData(config, columnData);
+      expect(result).toEqual([{ time: 1704067200, value: 43 }]);
+    });
+
+    it('should skip rows with NaN or Infinity time values', () => {
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [Number.NaN, 1704067200, Number.POSITIVE_INFINITY]],
+        ['Val', [10, 20, 30]],
+      ]);
+
+      const result = transformTableData(config, columnData);
+      expect(result).toEqual([{ time: 1704067200, value: 20 }]);
+    });
+
+    it('should skip time=0 for standard charts at any index', () => {
+      // time=0 means epoch 1970 — not a real Instant value, drop it.
+      const columnData = new Map<string, unknown[]>([
+        ['Timestamp', [0, 1704067200, 1704067260]],
+        ['Val', [10, 20, 30]],
+      ]);
+
+      const result = transformTableData(config, columnData);
+      expect(result).toEqual([
+        { time: 1704067200, value: 20 },
+        { time: 1704067260, value: 30 },
+      ]);
+    });
+  });
+});
+
+describe('getRequiredColumns', () => {
+  it('should return all column names from the data mapping', () => {
+    const config: TvlSeriesConfig = {
+      id: 'test',
+      type: 'Candlestick',
+      options: {},
+      dataMapping: {
+        tableId: 0,
+        columns: {
+          time: 'Timestamp',
+          open: 'Open',
+          high: 'High',
+          low: 'Low',
+          close: 'Close',
+        },
+      },
+    };
+
+    const cols = getRequiredColumns(config);
+    expect(cols).toEqual(['Timestamp', 'Open', 'High', 'Low', 'Close']);
+  });
+});
+
+describe('getAllColumnsForTable', () => {
+  it('should return unique columns for a specific table', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Candlestick',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'Timestamp', open: 'Open', close: 'Close' },
+        },
+      },
+      {
+        id: 's2',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'Timestamp', value: 'Volume' },
+        },
+      },
+    ];
+
+    const cols = getAllColumnsForTable(series, 0);
+    // 'Timestamp' appears in both but should only be listed once
+    expect(cols).toContain('Timestamp');
+    expect(cols).toContain('Open');
+    expect(cols).toContain('Close');
+    expect(cols).toContain('Volume');
+    expect(cols).toHaveLength(4);
+  });
+
+  it('should return columns only for the requested table', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'T', value: 'V1' },
+        },
+      },
+      {
+        id: 's2',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 1,
+          columns: { time: 'T', value: 'V2' },
+        },
+      },
+    ];
+
+    const cols0 = getAllColumnsForTable(series, 0);
+    expect(cols0).toEqual(['T', 'V1']);
+
+    const cols1 = getAllColumnsForTable(series, 1);
+    expect(cols1).toEqual(['T', 'V2']);
+  });
+
+  it('should return an empty array if no series match the table', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'T', value: 'V' },
+        },
+      },
+    ];
+
+    const cols = getAllColumnsForTable(series, 99);
+    expect(cols).toEqual([]);
+  });
+
+  it('should include columns from dynamic price lines', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'T', value: 'V' },
+        },
+        priceLines: [
+          { column: 'AvgPrice', color: 'blue', title: 'Avg' },
+          { column: 'MaxPrice', color: 'green', title: 'Max' },
+          { price: 100, color: 'gray', title: 'Static' },
+        ],
+      },
+    ];
+
+    const cols = getAllColumnsForTable(series, 0);
+    expect(cols).toContain('T');
+    expect(cols).toContain('V');
+    expect(cols).toContain('AvgPrice');
+    expect(cols).toContain('MaxPrice');
+    expect(cols).toHaveLength(4);
+  });
+
+  it('should not duplicate columns shared between series data and price lines', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'T', value: 'Price' },
+        },
+        priceLines: [{ column: 'Price', color: 'blue', title: 'Last' }],
+      },
+    ];
+
+    const cols = getAllColumnsForTable(series, 0);
+    expect(cols).toContain('T');
+    expect(cols).toContain('Price');
+    expect(cols).toHaveLength(2);
+  });
+});
+
+describe('transformTableData with yieldCurve chartType', () => {
+  const config: TvlSeriesConfig = {
+    id: 'yc-1',
+    type: 'Line',
+    options: {},
+    dataMapping: {
+      tableId: 0,
+      columns: { time: 'Maturity', value: 'Yield' },
+    },
+  };
+
+  it('should pass time values through as-is for yieldCurve', () => {
+    const columnData = new Map<string, unknown[]>([
+      ['Maturity', [1, 3, 6, 12, 24, 60, 120]],
+      ['Yield', [4.5, 4.6, 4.7, 4.8, 4.9, 5.0, 5.1]],
+    ]);
+    const result = transformTableData(config, columnData, 'yieldCurve');
+    expect(result).toEqual([
+      { time: 1, value: 4.5 },
+      { time: 3, value: 4.6 },
+      { time: 6, value: 4.7 },
+      { time: 12, value: 4.8 },
+      { time: 24, value: 4.9 },
+      { time: 60, value: 5.0 },
+      { time: 120, value: 5.1 },
+    ]);
+  });
+
+  it('should NOT apply timezone conversion for yieldCurve', () => {
+    const columnData = new Map<string, unknown[]>([
+      ['Maturity', [12]],
+      ['Yield', [4.8]],
+    ]);
+    const result = transformTableData(config, columnData, 'yieldCurve');
+    // Raw value 12 should be preserved, not timezone-shifted
+    expect((result[0] as Record<string, unknown>).time).toBe(12);
+  });
+
+  it('should allow time value of 0 for yieldCurve', () => {
+    const columnData = new Map<string, unknown[]>([
+      ['Maturity', [0, 1, 3]],
+      ['Yield', [4.0, 4.5, 4.6]],
+    ]);
+    const result = transformTableData(config, columnData, 'yieldCurve');
+    expect(result).toHaveLength(3);
+    expect((result[0] as Record<string, unknown>).time).toBe(0);
+  });
+});
+
+describe('transformTableData with options chartType', () => {
+  const config: TvlSeriesConfig = {
+    id: 'opt-1',
+    type: 'Line',
+    options: {},
+    dataMapping: {
+      tableId: 0,
+      columns: { time: 'Strike', value: 'Premium' },
+    },
+  };
+
+  it('should pass strike prices through as-is', () => {
+    const columnData = new Map<string, unknown[]>([
+      ['Strike', [90, 95, 100, 105, 110]],
+      ['Premium', [12.5, 8.3, 5.1, 3.2, 1.8]],
+    ]);
+    const result = transformTableData(config, columnData, 'options');
+    expect(result).toEqual([
+      { time: 90, value: 12.5 },
+      { time: 95, value: 8.3 },
+      { time: 100, value: 5.1 },
+      { time: 105, value: 3.2 },
+      { time: 110, value: 1.8 },
+    ]);
+  });
+
+  it('should NOT apply timezone conversion for options', () => {
+    const columnData = new Map<string, unknown[]>([
+      ['Strike', [100]],
+      ['Premium', [5.0]],
+    ]);
+    const result = transformTableData(config, columnData, 'options');
+    expect((result[0] as Record<string, unknown>).time).toBe(100);
+  });
+});
+
+describe('getAllColumnsForTable with markerSpec', () => {
+  it('should include marker spec columns for matching tableId', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'T', value: 'V' },
+        },
+        markerSpec: {
+          tableId: 1,
+          columns: { time: 'SignalTime', text: 'Label' },
+          defaults: { position: 'aboveBar', shape: 'circle', color: '#000' },
+        },
+      },
+    ];
+
+    const cols = getAllColumnsForTable(series, 1);
+    expect(cols).toContain('SignalTime');
+    expect(cols).toContain('Label');
+    expect(cols).toHaveLength(2);
+  });
+
+  it('should not include marker spec columns for non-matching tableId', () => {
+    const series: TvlSeriesConfig[] = [
+      {
+        id: 's1',
+        type: 'Line',
+        options: {},
+        dataMapping: {
+          tableId: 0,
+          columns: { time: 'T', value: 'V' },
+        },
+        markerSpec: {
+          tableId: 1,
+          columns: { time: 'SignalTime', text: 'Label' },
+          defaults: {},
+        },
+      },
+    ];
+
+    const cols = getAllColumnsForTable(series, 0);
+    expect(cols).toContain('T');
+    expect(cols).toContain('V');
+    expect(cols).not.toContain('SignalTime');
+    expect(cols).not.toContain('Label');
+  });
+});
+
+describe('buildMarkersFromTableData', () => {
+  const baseSpec: TvlMarkerSpec = {
+    tableId: 1,
+    columns: { time: 'Time' },
+    defaults: {
+      position: 'aboveBar',
+      shape: 'circle',
+      color: '#FF0000',
+      text: 'Signal',
+    },
+  };
+
+  it('should build markers with all fixed defaults', () => {
+    // Time values are pre-converted epoch seconds (from model's timeTranslator)
+    const columnData = new Map<string, unknown[]>([
+      ['Time', [1704067200, 1704153600]],
+    ]);
+
+    const result = buildMarkersFromTableData(baseSpec, columnData);
+
+    expect(result).toHaveLength(2);
+    expect(result[0].position).toBe('aboveBar');
+    expect(result[0].shape).toBe('circle');
+    expect(result[0].color).toBe('#FF0000');
+    expect(result[0].text).toBe('Signal');
+  });
+
+  it('should resolve per-row values from columns', () => {
+    const spec: TvlMarkerSpec = {
+      tableId: 1,
+      columns: {
+        time: 'Time',
+        text: 'Label',
+        color: 'Color',
+        position: 'Pos',
+      },
+      defaults: { shape: 'arrowUp' },
+    };
+
+    const columnData = new Map<string, unknown[]>([
+      ['Time', [1704067200, 1704153600]],
+      ['Label', ['Buy', 'Sell']],
+      ['Color', ['#00FF00', '#FF0000']],
+      ['Pos', ['belowBar', 'aboveBar']],
+    ]);
+
+    const result = buildMarkersFromTableData(spec, columnData);
+
+    expect(result).toHaveLength(2);
+    expect(result[0].text).toBe('Buy');
+    expect(result[0].color).toBe('#00FF00');
+    expect(result[0].position).toBe('belowBar');
+    expect(result[0].shape).toBe('arrowUp');
+    expect(result[1].text).toBe('Sell');
+    expect(result[1].color).toBe('#FF0000');
+    expect(result[1].position).toBe('aboveBar');
+  });
+
+  it('should map snake_case position and shape from columns', () => {
+    const spec: TvlMarkerSpec = {
+      tableId: 1,
+      columns: { time: 'Time', position: 'Pos', shape: 'Shape' },
+      defaults: { text: 'X', color: '#000' },
+    };
+
+    const columnData = new Map<string, unknown[]>([
+      ['Time', [1704067200]],
+      ['Pos', ['below_bar']],
+      ['Shape', ['arrow_up']],
+    ]);
+
+    const result = buildMarkersFromTableData(spec, columnData);
+
+    expect(result).toHaveLength(1);
+    expect(result[0].position).toBe('belowBar');
+    expect(result[0].shape).toBe('arrowUp');
+  });
+
+  it('should sort markers by time', () => {
+    const columnData = new Map<string, unknown[]>([
+      ['Time', [1704153600, 1704067200]],
+    ]);
+
+    const result = buildMarkersFromTableData(baseSpec, columnData);
+
+    expect(result).toHaveLength(2);
+    expect(result[0].time as number).toBeLessThan(result[1].time as number);
+  });
+
+  it('should return empty array when time column is missing', () => {
+    const columnData = new Map<string, unknown[]>([['Other', [1, 2, 3]]]);
+
+    const result = buildMarkersFromTableData(baseSpec, columnData);
+    expect(result).toEqual([]);
+  });
+
+  it('should pass through numeric time for yieldCurve chart type', () => {
+    const columnData = new Map<string, unknown[]>([['Time', [12, 24, 60]]]);
+
+    const result = buildMarkersFromTableData(
+      baseSpec,
+      columnData,
+      'yieldCurve'
+    );
+
+    expect(result).toHaveLength(3);
+    expect(result[0].time).toBe(12);
+    expect(result[1].time).toBe(24);
+    expect(result[2].time).toBe(60);
+  });
+
+  it('should include size when provided from column', () => {
+    const spec: TvlMarkerSpec = {
+      tableId: 1,
+      columns: { time: 'Time', size: 'Sz' },
+      defaults: {
+        text: 'X',
+        color: '#000',
+        position: 'aboveBar',
+        shape: 'circle',
+      },
+    };
+
+    const columnData = new Map<string, unknown[]>([
+      ['Time', [1704067200]],
+      ['Sz', [3]],
+    ]);
+
+    const result = buildMarkersFromTableData(spec, columnData);
+    expect(result[0].size).toBe(3);
+  });
+});
diff --git a/plugins/tradingview-lightweight/src/js/src/index.ts b/plugins/tradingview-lightweight/src/js/src/index.ts
new file mode 100644
index 000000000..385750c84
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/src/index.ts
@@ -0,0 +1,9 @@
+import { TradingViewPlugin } from './TradingViewPlugin';
+
+export { TradingViewPlugin } from './TradingViewPlugin';
+export { default as TradingViewChart } from './TradingViewChart';
+export { default as TradingViewChartModel } from './TradingViewChartModel';
+export { default as TradingViewChartRenderer } from './TradingViewChartRenderer';
+
+// Default export is the plugin
+export default TradingViewPlugin;
diff --git a/plugins/tradingview-lightweight/src/js/tsconfig.json b/plugins/tradingview-lightweight/src/js/tsconfig.json
new file mode 100644
index 000000000..ece69655d
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/tsconfig.json
@@ -0,0 +1,13 @@
+{
+  "extends": "@deephaven/tsconfig",
+  "compilerOptions": {
+    "composite": false,
+    "rootDir": "src/",
+    "outDir": "dist/",
+    "types": [],
+    "emitDeclarationOnly": false,
+    "noEmit": false
+  },
+  "include": ["src/**/*.ts", "src/**/*.tsx"],
+  "exclude": ["**/node_modules/**/*", "src/**/*.test.*", "dist/**/*"]
+}
diff --git a/plugins/tradingview-lightweight/src/js/vite.config.ts b/plugins/tradingview-lightweight/src/js/vite.config.ts
new file mode 100644
index 000000000..f0bb8aa32
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/vite.config.ts
@@ -0,0 +1,35 @@
+/* eslint-disable import/no-extraneous-dependencies */
+import { defineConfig } from 'vite';
+import react from '@vitejs/plugin-react-swc';
+
+// https://vitejs.dev/config/
+export default defineConfig(({ mode }) => ({
+  build: {
+    minify: false,
+    outDir: 'dist/bundle',
+    lib: {
+      entry: './src/index.ts',
+      fileName: () => 'index.js',
+      formats: ['cjs'],
+    },
+    rollupOptions: {
+      external: [
+        'react',
+        'react-dom',
+        'redux',
+        'react-redux',
+        '@deephaven/jsapi-bootstrap',
+        '@deephaven/log',
+        '@deephaven/components',
+        '@deephaven/dashboard',
+        '@deephaven/dashboard-core-plugins',
+        '@deephaven/icons',
+        '@deephaven/plugin',
+        '@deephaven/utils',
+      ],
+    },
+  },
+  define:
+    mode === 'production' ? { 'process.env.NODE_ENV': '"production"' } : {},
+  plugins: [react()],
+}));
diff --git a/plugins/tradingview-lightweight/src/js/vite.config.ts.timestamp-1782480962701-ac27b13b23c5d8.mjs b/plugins/tradingview-lightweight/src/js/vite.config.ts.timestamp-1782480962701-ac27b13b23c5d8.mjs
new file mode 100644
index 000000000..e92f5bdd0
--- /dev/null
+++ b/plugins/tradingview-lightweight/src/js/vite.config.ts.timestamp-1782480962701-ac27b13b23c5d8.mjs
@@ -0,0 +1,36 @@
+// vite.config.ts
+import { defineConfig } from "file:///home/dsmmcken/git/deephaven-plugins/node_modules/vite/dist/node/index.js";
+import react from "file:///home/dsmmcken/git/deephaven-plugins/node_modules/@vitejs/plugin-react-swc/index.js";
+var vite_config_default = defineConfig(({ mode }) => ({
+  build: {
+    minify: false,
+    outDir: "dist/bundle",
+    lib: {
+      entry: "./src/index.ts",
+      fileName: () => "index.js",
+      formats: ["cjs"]
+    },
+    rollupOptions: {
+      external: [
+        "react",
+        "react-dom",
+        "redux",
+        "react-redux",
+        "@deephaven/jsapi-bootstrap",
+        "@deephaven/log",
+        "@deephaven/components",
+        "@deephaven/dashboard",
+        "@deephaven/dashboard-core-plugins",
+        "@deephaven/icons",
+        "@deephaven/plugin",
+        "@deephaven/utils"
+      ]
+    }
+  },
+  define: mode === "production" ? { "process.env.NODE_ENV": '"production"' } : {},
+  plugins: [react()]
+}));
+export {
+  vite_config_default as default
+};
+//# sourceMappingURL=data:application/json;base64,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
diff --git a/plugins/tradingview-lightweight/test/__init__.py b/plugins/tradingview-lightweight/test/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/plugins/tradingview-lightweight/test/deephaven/__init__.py b/plugins/tradingview-lightweight/test/deephaven/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/__init__.py b/plugins/tradingview-lightweight/test/deephaven/plot/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/__init__.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_auto_bin.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_auto_bin.py
new file mode 100644
index 000000000..69bb70dec
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_auto_bin.py
@@ -0,0 +1,241 @@
+"""Unit tests for auto_bin pure helpers (nice_bin_width, parse_bin_width)."""
+
+from __future__ import annotations
+
+import os
+import sys
+from unittest.mock import MagicMock
+
+import pytest
+
+# Add src to path for namespace package resolution
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight import auto_bin  # noqa: E402
+
+
+class TestNiceBinWidth:
+    def test_zero_or_negative_range_returns_one(self) -> None:
+        assert auto_bin.nice_bin_width(0, 1000) == 1
+        assert auto_bin.nice_bin_width(-1, 1000) == 1
+
+    def test_target_zero_returns_one(self) -> None:
+        assert auto_bin.nice_bin_width(1_000_000, 0) == 1
+
+    def test_returns_value_from_nice_set(self) -> None:
+        for range_ns in [10**3, 10**6, 10**9, 60 * 10**9, 24 * 3600 * 10**9]:
+            w = auto_bin.nice_bin_width(range_ns, 5000)
+            assert (
+                w in auto_bin.NICE_BIN_WIDTHS_NS
+            ), f"{range_ns}/{5000} -> {w} not in nice set"
+
+    def test_one_day_target_5000_picks_seconds(self) -> None:
+        # 1 day / 5000 = ~17.28s -> nearest >= is 30s
+        day_ns = 24 * 3600 * 10**9
+        w = auto_bin.nice_bin_width(day_ns, 5000)
+        assert w == 30 * 10**9
+
+    def test_one_hour_target_60_picks_one_minute(self) -> None:
+        hour_ns = 3600 * 10**9
+        # 3600 / 60 = 60s -> nearest >=60s is 60s (1m)
+        w = auto_bin.nice_bin_width(hour_ns, 60)
+        assert w == 60 * 10**9
+
+    def test_huge_range_caps_at_largest(self) -> None:
+        # 100 years
+        century_ns = 100 * 365 * 24 * 3600 * 10**9
+        w = auto_bin.nice_bin_width(century_ns, 1)
+        assert w == auto_bin.NICE_BIN_WIDTHS_NS[-1]
+
+    def test_tiny_range_picks_smallest(self) -> None:
+        w = auto_bin.nice_bin_width(1, 1000)
+        assert w == 1
+
+    def test_monotonic_in_range(self) -> None:
+        # As range_ns grows, the chosen width is non-decreasing.
+        prev = 0
+        for r in [
+            10**3,
+            10**6,
+            10**9,
+            60 * 10**9,
+            3600 * 10**9,
+            86400 * 10**9,
+        ]:
+            w = auto_bin.nice_bin_width(r, 5000)
+            assert w >= prev
+            prev = w
+
+
+class TestParseBinWidth:
+    def test_int_passthrough(self) -> None:
+        assert auto_bin.parse_bin_width(123_456) == 123_456
+
+    def test_int_zero_or_negative_raises(self) -> None:
+        with pytest.raises(ValueError):
+            auto_bin.parse_bin_width(0)
+        with pytest.raises(ValueError):
+            auto_bin.parse_bin_width(-1)
+
+    def test_pt1s(self) -> None:
+        assert auto_bin.parse_bin_width("PT1S") == 1_000_000_000
+
+    def test_pt5m(self) -> None:
+        assert auto_bin.parse_bin_width("PT5M") == 5 * 60 * 1_000_000_000
+
+    def test_pt1h(self) -> None:
+        assert auto_bin.parse_bin_width("PT1H") == 3600 * 1_000_000_000
+
+    def test_p1d(self) -> None:
+        assert auto_bin.parse_bin_width("P1D") == 24 * 3600 * 1_000_000_000
+
+    def test_combined(self) -> None:
+        # 1 day + 2h + 30m + 15s
+        expected = (24 * 3600 + 2 * 3600 + 30 * 60 + 15) * 1_000_000_000
+        assert auto_bin.parse_bin_width("P1DT2H30M15S") == expected
+
+    def test_fractional_seconds(self) -> None:
+        # 0.5s = 500ms = 500_000_000 ns
+        assert auto_bin.parse_bin_width("PT0.5S") == 500_000_000
+
+    @pytest.mark.parametrize(
+        "spec",
+        ["", "P", "1H", "PT", "P1Y", "PT-1S", "abc", None],
+    )
+    def test_invalid_raises(self, spec: object) -> None:
+        with pytest.raises(ValueError):
+            auto_bin.parse_bin_width(spec)
+
+    def test_non_string_non_int_raises(self) -> None:
+        with pytest.raises(ValueError):
+            auto_bin.parse_bin_width(1.5)
+
+
+class TestHistogramApi:
+    """Surface-level checks on build_histogram_view: agg validation, missing DH."""
+
+    def test_invalid_agg_raises(self) -> None:
+        with pytest.raises(ValueError):
+            auto_bin.build_histogram_view(
+                None, "T", "V", 1_000_000_000, agg_mode="median"
+            )
+
+    def test_zero_bin_width_raises(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        # Force agg to be non-None so we get past the import check
+        monkeypatch.setattr(auto_bin, "agg", object())
+        with pytest.raises(ValueError):
+            auto_bin.build_histogram_view(None, "T", "V", 0)
+
+
+class TestScopedView:
+    """``_build_scoped_view`` routes between full-source and head+body+tail
+    builds based on whether body_range_ns is strictly inside full_range_ns."""
+
+    def _patches(self, monkeypatch: pytest.MonkeyPatch) -> dict:
+        """Mock the helpers so the routing logic can be observed without DH."""
+        calls: dict = {"common": [], "anchor": [], "merge": []}
+
+        def fake_common(raw, time_col, bw, aggs, out):
+            calls["common"].append({"raw": raw, "bw": bw, "out": tuple(out)})
+            return MagicMock(name="common", bin_width_ns=bw, body=False)
+
+        def fake_anchor(raw, time_col, slice_filter, aggs, out, time_pos):
+            calls["anchor"].append({"filter": slice_filter, "time_pos": time_pos})
+            return MagicMock(name=f"anchor_{time_pos}")
+
+        class _MergedTable:
+            def __init__(self, parts):
+                self.parts = parts
+
+            def sort(self, time_col):
+                self.sorted_by = time_col
+                return self
+
+        def fake_merge(parts):
+            calls["merge"].append(parts)
+            return _MergedTable(parts)
+
+        monkeypatch.setattr(auto_bin, "_common_aggregated_view", fake_common)
+        monkeypatch.setattr(auto_bin, "_build_anchor", fake_anchor)
+        monkeypatch.setattr(auto_bin, "dh_merge", fake_merge)
+        monkeypatch.setattr(auto_bin, "agg", MagicMock())
+        return calls
+
+    def test_no_body_range_uses_full_path(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        calls = self._patches(monkeypatch)
+        auto_bin.build_histogram_view(object(), "T", "V", 1_000_000_000, agg_mode="sum")
+        assert len(calls["common"]) == 1
+        assert calls["anchor"] == []
+        assert calls["merge"] == []
+
+    def test_body_covers_full_uses_full_path(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        calls = self._patches(monkeypatch)
+        auto_bin.build_histogram_view(
+            object(),
+            "T",
+            "V",
+            1_000_000_000,
+            agg_mode="sum",
+            body_range_ns=(0, 1_000),
+            full_range_ns=(0, 1_000),
+        )
+        assert len(calls["common"]) == 1
+        assert calls["anchor"] == []
+
+    def test_body_strictly_inside_uses_scoped_path(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        calls = self._patches(monkeypatch)
+        auto_bin.build_histogram_view(
+            MagicMock(name="raw"),
+            "T",
+            "V",
+            1_000_000_000,
+            agg_mode="sum",
+            body_range_ns=(100, 900),
+            full_range_ns=(0, 1_000),
+        )
+        # One body call (common) + two anchors (head, tail) + one merge.
+        assert len(calls["common"]) == 1
+        assert {a["time_pos"] for a in calls["anchor"]} == {"first", "last"}
+        assert len(calls["merge"]) == 1
+
+    def test_ohlc_scoped_path(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        calls = self._patches(monkeypatch)
+        auto_bin.build_ohlc_view(
+            MagicMock(name="raw"),
+            "T",
+            "O",
+            "H",
+            "L",
+            "C",
+            1_000_000_000,
+            body_range_ns=(100, 900),
+            full_range_ns=(0, 1_000),
+        )
+        assert len(calls["common"]) == 1
+        assert {a["time_pos"] for a in calls["anchor"]} == {"first", "last"}
+        assert len(calls["merge"]) == 1
+
+
+class TestOhlcApi:
+    def test_duplicate_columns_raise(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        monkeypatch.setattr(auto_bin, "agg", object())
+        with pytest.raises(ValueError):
+            auto_bin.build_ohlc_view(None, "T", "P", "P", "P", "P", 1_000_000_000)
+
+    def test_zero_bin_width_raises(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        monkeypatch.setattr(auto_bin, "agg", object())
+        with pytest.raises(ValueError):
+            auto_bin.build_ohlc_view(None, "T", "O", "H", "L", "C", 0)
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_chart.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_chart.py
new file mode 100644
index 000000000..ac547bfee
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_chart.py
@@ -0,0 +1,2916 @@
+"""Tests for chart creation and TvlChart class."""
+
+from __future__ import annotations
+
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock
+
+# Add src to path for namespace package resolution
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight.chart import (
+    TvlChart,
+    chart,
+    candlestick,
+    line,
+    area,
+    bar,
+    baseline,
+    histogram,
+    yield_curve,
+    options_chart,
+    custom_numeric,
+)
+from deephaven.plot.tradingview_lightweight.series import (
+    SeriesSpec,
+    candlestick_series,
+    line_series,
+    area_series,
+    bar_series,
+    baseline_series,
+    histogram_series,
+)
+from deephaven.plot.tradingview_lightweight.markers import Marker, PriceLine
+
+
+class TestTvlChart(unittest.TestCase):
+    """Tests for the TvlChart class."""
+
+    def setUp(self):
+        self.table1 = MagicMock(name="table1")
+        self.table2 = MagicMock(name="table2")
+
+    def test_properties(self):
+        s1 = line_series(self.table1)
+        c = TvlChart(series_list=[s1], chart_options={"fontSize": 14})
+        self.assertEqual(len(c.series_list), 1)
+        self.assertIs(c.series_list[0], s1)
+        self.assertEqual(c.chart_options, {"fontSize": 14})
+
+    def test_get_tables_single(self):
+        s1 = line_series(self.table1)
+        c = TvlChart(series_list=[s1], chart_options={})
+        tables = c.get_tables()
+        self.assertEqual(len(tables), 1)
+        self.assertIs(tables[0], self.table1)
+
+    def test_get_tables_multiple_unique(self):
+        s1 = line_series(self.table1)
+        s2 = area_series(self.table2)
+        c = TvlChart(series_list=[s1, s2], chart_options={})
+        tables = c.get_tables()
+        self.assertEqual(len(tables), 2)
+        self.assertIs(tables[0], self.table1)
+        self.assertIs(tables[1], self.table2)
+
+    def test_get_tables_deduplication(self):
+        """Same table used in two series should appear only once."""
+        s1 = line_series(self.table1, value="Price")
+        s2 = histogram_series(self.table1, value="Volume")
+        c = TvlChart(series_list=[s1, s2], chart_options={})
+        tables = c.get_tables()
+        self.assertEqual(len(tables), 1)
+        self.assertIs(tables[0], self.table1)
+
+    def test_to_dict(self):
+        s1 = line_series(self.table1, color="blue")
+        s2 = candlestick_series(self.table2, up_color="green")
+        c = TvlChart(
+            series_list=[s1, s2],
+            chart_options={"fontSize": 14, "attributionLogo": False},
+        )
+        table_id_map = {id(self.table1): 0, id(self.table2): 1}
+        result = c.to_dict(table_id_map)
+
+        self.assertIn("chartOptions", result)
+        self.assertIn("series", result)
+        self.assertEqual(result["chartOptions"]["fontSize"], 14)
+        self.assertEqual(result["chartOptions"]["attributionLogo"], False)
+
+        self.assertEqual(len(result["series"]), 2)
+        self.assertEqual(result["series"][0]["id"], "series_0")
+        self.assertEqual(result["series"][0]["type"], "Line")
+        self.assertEqual(result["series"][0]["dataMapping"]["tableId"], 0)
+        self.assertEqual(result["series"][1]["id"], "series_1")
+        self.assertEqual(result["series"][1]["type"], "Candlestick")
+        self.assertEqual(result["series"][1]["dataMapping"]["tableId"], 1)
+
+    def test_to_dict_empty_options(self):
+        s = line_series(self.table1)
+        c = TvlChart(series_list=[s], chart_options={})
+        table_id_map = {id(self.table1): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["chartOptions"], {})
+
+
+class TestChartFunction(unittest.TestCase):
+    """Tests for the chart() function."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_single_series(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(len(c.series_list), 1)
+        self.assertIs(c.series_list[0], s)
+
+    def test_multiple_series(self):
+        s1 = line_series(self.table, value="Price")
+        s2 = histogram_series(self.table, value="Volume")
+        c = chart(s1, s2)
+        self.assertEqual(len(c.series_list), 2)
+
+    def test_empty_options(self):
+        """chart() with no kwargs should only have the default font in layout."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertEqual(
+            c.chart_options,
+            {"layout": {"fontFamily": "Fira, sans-serif"}},
+        )
+
+    def test_layout_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            background_color="#1a1a2e",
+            text_color="#e0e0e0",
+            font_size=14,
+        )
+        layout = c.chart_options["layout"]
+        self.assertEqual(layout["background"], {"type": "solid", "color": "#1a1a2e"})
+        self.assertEqual(layout["textColor"], "#e0e0e0")
+        self.assertEqual(layout["fontSize"], 14)
+
+    def test_background_color_only(self):
+        """background_color alone should create a layout with just background."""
+        s = line_series(self.table)
+        c = chart(s, background_color="#000")
+        self.assertIn("layout", c.chart_options)
+        self.assertEqual(
+            c.chart_options["layout"]["background"],
+            {"type": "solid", "color": "#000"},
+        )
+
+    def test_grid_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            vert_lines_visible=True,
+            vert_lines_color="#333",
+            vert_lines_style="dashed",
+            horz_lines_visible=False,
+            horz_lines_color="#444",
+            horz_lines_style="dotted",
+        )
+        grid = c.chart_options["grid"]
+        self.assertTrue(grid["vertLines"]["visible"])
+        self.assertEqual(grid["vertLines"]["color"], "#333")
+        self.assertEqual(grid["vertLines"]["style"], 2)  # dashed
+        self.assertFalse(grid["horzLines"]["visible"])
+        self.assertEqual(grid["horzLines"]["color"], "#444")
+        self.assertEqual(grid["horzLines"]["style"], 1)  # dotted
+
+    def test_crosshair_mode_normal(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_mode="normal")
+        self.assertEqual(c.chart_options["crosshair"]["mode"], 0)
+
+    def test_crosshair_mode_magnet(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_mode="magnet")
+        self.assertEqual(c.chart_options["crosshair"]["mode"], 1)
+
+    def test_crosshair_mode_hidden(self):
+        """CrosshairMode 'hidden' serializes to integer 2."""
+        s = line_series(self.table)
+        c = chart(s, crosshair_mode="hidden")
+        self.assertEqual(c.chart_options["crosshair"]["mode"], 2)
+
+    def test_crosshair_mode_magnet_ohlc(self):
+        """CrosshairMode 'magnet_ohlc' serializes to integer 3."""
+        s = line_series(self.table)
+        c = chart(s, crosshair_mode="magnet_ohlc")
+        self.assertEqual(c.chart_options["crosshair"]["mode"], 3)
+
+    def test_crosshair_mode_all_four_values(self):
+        """All four CrosshairMode members map to the correct integers."""
+        expected = {"normal": 0, "magnet": 1, "hidden": 2, "magnet_ohlc": 3}
+        s = line_series(self.table)
+        for mode_name, mode_int in expected.items():
+            c = chart(s, crosshair_mode=mode_name)
+            self.assertEqual(
+                c.chart_options["crosshair"]["mode"],
+                mode_int,
+                f"crosshair_mode='{mode_name}' should map to {mode_int}",
+            )
+
+    def test_crosshair_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("crosshair", c.chart_options)
+
+    def test_crosshair_vert_line_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            crosshair_vert_line_width=8,
+            crosshair_vert_line_color="#C3BCDB44",
+            crosshair_vert_line_style="solid",
+            crosshair_vert_line_label_background_color="#9B7DFF",
+        )
+        vl = c.chart_options["crosshair"]["vertLine"]
+        self.assertEqual(vl["width"], 8)
+        self.assertEqual(vl["color"], "#C3BCDB44")
+        self.assertEqual(vl["style"], 0)  # solid
+        self.assertEqual(vl["labelBackgroundColor"], "#9B7DFF")
+
+    def test_crosshair_horz_line_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            crosshair_horz_line_color="#9B7DFF",
+            crosshair_horz_line_label_background_color="#9B7DFF",
+        )
+        hl = c.chart_options["crosshair"]["horzLine"]
+        self.assertEqual(hl["color"], "#9B7DFF")
+        self.assertEqual(hl["labelBackgroundColor"], "#9B7DFF")
+
+    def test_crosshair_mode_with_sub_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            crosshair_mode="normal",
+            crosshair_vert_line_width=4,
+        )
+        ch = c.chart_options["crosshair"]
+        self.assertEqual(ch["mode"], 0)
+        self.assertEqual(ch["vertLine"]["width"], 4)
+
+    def test_crosshair_sub_options_only(self):
+        """Setting sub-options without mode should still create crosshair."""
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_width=2)
+        self.assertIn("crosshair", c.chart_options)
+        self.assertNotIn("mode", c.chart_options["crosshair"])
+        self.assertEqual(c.chart_options["crosshair"]["vertLine"]["width"], 2)
+
+    def test_crosshair_vert_line_visible_true(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_visible=True)
+        self.assertTrue(c.chart_options["crosshair"]["vertLine"]["visible"])
+
+    def test_crosshair_vert_line_visible_false(self):
+        """visible=False must be serialized (not filtered out by _filter_none)."""
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_visible=False)
+        self.assertFalse(c.chart_options["crosshair"]["vertLine"]["visible"])
+
+    def test_crosshair_vert_line_label_visible_true(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_label_visible=True)
+        self.assertTrue(c.chart_options["crosshair"]["vertLine"]["labelVisible"])
+
+    def test_crosshair_vert_line_label_visible_false(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_label_visible=False)
+        self.assertFalse(c.chart_options["crosshair"]["vertLine"]["labelVisible"])
+
+    def test_crosshair_horz_line_visible_true(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_horz_line_visible=True)
+        self.assertTrue(c.chart_options["crosshair"]["horzLine"]["visible"])
+
+    def test_crosshair_horz_line_visible_false(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_horz_line_visible=False)
+        self.assertFalse(c.chart_options["crosshair"]["horzLine"]["visible"])
+
+    def test_crosshair_horz_line_label_visible_true(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_horz_line_label_visible=True)
+        self.assertTrue(c.chart_options["crosshair"]["horzLine"]["labelVisible"])
+
+    def test_crosshair_horz_line_label_visible_false(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_horz_line_label_visible=False)
+        self.assertFalse(c.chart_options["crosshair"]["horzLine"]["labelVisible"])
+
+    def test_crosshair_do_not_snap_to_hidden_series_true(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_do_not_snap_to_hidden_series=True)
+        self.assertTrue(c.chart_options["crosshair"]["doNotSnapToHiddenSeriesIndices"])
+
+    def test_crosshair_do_not_snap_to_hidden_series_false(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_do_not_snap_to_hidden_series=False)
+        self.assertFalse(c.chart_options["crosshair"]["doNotSnapToHiddenSeriesIndices"])
+
+    def test_crosshair_all_new_options(self):
+        """All five new crosshair params round-trip correctly together."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            crosshair_mode="hidden",
+            crosshair_vert_line_visible=False,
+            crosshair_vert_line_label_visible=False,
+            crosshair_horz_line_visible=True,
+            crosshair_horz_line_label_visible=False,
+            crosshair_do_not_snap_to_hidden_series=True,
+        )
+        ch = c.chart_options["crosshair"]
+        self.assertEqual(ch["mode"], 2)
+        self.assertFalse(ch["vertLine"]["visible"])
+        self.assertFalse(ch["vertLine"]["labelVisible"])
+        self.assertTrue(ch["horzLine"]["visible"])
+        self.assertFalse(ch["horzLine"]["labelVisible"])
+        self.assertTrue(ch["doNotSnapToHiddenSeriesIndices"])
+
+    def test_crosshair_vert_line_visible_not_set_by_default(self):
+        """visible key must not appear when param is not provided."""
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_color="#fff")  # trigger vertLine dict
+        self.assertNotIn("visible", c.chart_options["crosshair"]["vertLine"])
+
+    def test_crosshair_vert_line_label_visible_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_vert_line_color="#fff")
+        self.assertNotIn("labelVisible", c.chart_options["crosshair"]["vertLine"])
+
+    def test_crosshair_horz_line_visible_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_horz_line_color="#fff")
+        self.assertNotIn("visible", c.chart_options["crosshair"]["horzLine"])
+
+    def test_crosshair_horz_line_label_visible_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_horz_line_color="#fff")
+        self.assertNotIn("labelVisible", c.chart_options["crosshair"]["horzLine"])
+
+    def test_crosshair_do_not_snap_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s, crosshair_mode="normal")
+        self.assertNotIn("doNotSnapToHiddenSeriesIndices", c.chart_options["crosshair"])
+
+    def test_right_price_scale(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            right_price_scale_visible=True,
+            right_price_scale_border_visible=False,
+            right_price_scale_border_color="#555",
+            right_price_scale_auto_scale=True,
+            right_price_scale_mode="logarithmic",
+            right_price_scale_invert_scale=False,
+        )
+        rps = c.chart_options["rightPriceScale"]
+        self.assertTrue(rps["visible"])
+        self.assertFalse(rps["borderVisible"])
+        self.assertEqual(rps["borderColor"], "#555")
+        self.assertTrue(rps["autoScale"])
+        self.assertEqual(rps["mode"], 1)  # logarithmic
+        self.assertFalse(rps["invertScale"])
+
+    def test_left_price_scale(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            left_price_scale_visible=True,
+            left_price_scale_border_visible=True,
+            left_price_scale_border_color="#666",
+            left_price_scale_auto_scale=False,
+            left_price_scale_mode="percentage",
+            left_price_scale_invert_scale=True,
+        )
+        lps = c.chart_options["leftPriceScale"]
+        self.assertTrue(lps["visible"])
+        self.assertTrue(lps["borderVisible"])
+        self.assertEqual(lps["borderColor"], "#666")
+        self.assertFalse(lps["autoScale"])
+        self.assertEqual(lps["mode"], 2)  # percentage
+        self.assertTrue(lps["invertScale"])
+
+    def test_price_scale_modes(self):
+        """Test all four price scale mode mappings."""
+        modes = {
+            "normal": 0,
+            "logarithmic": 1,
+            "percentage": 2,
+            "indexed_to_100": 3,
+        }
+        s = line_series(self.table)
+        for mode_name, mode_value in modes.items():
+            c = chart(s, right_price_scale_mode=mode_name)
+            self.assertEqual(
+                c.chart_options["rightPriceScale"]["mode"],
+                mode_value,
+                f"Mode {mode_name} should map to {mode_value}",
+            )
+
+    def test_time_scale_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            time_visible=True,
+            seconds_visible=False,
+            time_scale_border_visible=True,
+            time_scale_border_color="#777",
+            right_offset=5,
+            bar_spacing=10.0,
+            min_bar_spacing=2.0,
+            fix_left_edge=True,
+            fix_right_edge=False,
+        )
+        ts = c.chart_options["timeScale"]
+        self.assertTrue(ts["timeVisible"])
+        self.assertFalse(ts["secondsVisible"])
+        self.assertTrue(ts["borderVisible"])
+        self.assertEqual(ts["borderColor"], "#777")
+        self.assertEqual(ts["rightOffset"], 5)
+        self.assertEqual(ts["barSpacing"], 10.0)
+        self.assertEqual(ts["minBarSpacing"], 2.0)
+        self.assertTrue(ts["fixLeftEdge"])
+        self.assertFalse(ts["fixRightEdge"])
+
+    def test_watermark_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_text="AAPL",
+            watermark_color="rgba(0,0,0,0.2)",
+            watermark_visible=True,
+            watermark_font_size=48,
+            watermark_horz_align="center",
+            watermark_vert_align="center",
+        )
+        wm = c.chart_options["watermark"]
+        self.assertEqual(wm["text"], "AAPL")
+        self.assertEqual(wm["color"], "rgba(0,0,0,0.2)")
+        self.assertTrue(wm["visible"])
+        self.assertEqual(wm["fontSize"], 48)
+        self.assertEqual(wm["horzAlign"], "center")
+        self.assertEqual(wm["vertAlign"], "center")
+
+    def test_watermark_text_auto_visible(self):
+        """Setting watermark_text without watermark_visible should set visible=True."""
+        s = line_series(self.table)
+        c = chart(s, watermark_text="Test")
+        wm = c.chart_options["watermark"]
+        self.assertTrue(wm["visible"])
+
+    def test_watermark_visible_false(self):
+        """Explicitly setting watermark_visible=False should be respected."""
+        s = line_series(self.table)
+        c = chart(s, watermark_text="Hidden", watermark_visible=False)
+        wm = c.chart_options["watermark"]
+        self.assertFalse(wm["visible"])
+
+    def test_price_formatter(self):
+        s = line_series(self.table)
+        c = chart(s, price_formatter="currency_eur")
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["priceFormatterName"], "currency_eur")
+
+    def test_price_formatter_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("localization", c.chart_options)
+
+    # --- Localization: locale ---
+
+    def test_locale_string(self):
+        """locale is passed through as-is into localization.locale."""
+        s = line_series(self.table)
+        c = chart(s, locale="de-DE")
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["locale"], "de-DE")
+
+    def test_locale_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("localization", c.chart_options)
+
+    def test_locale_various_tags(self):
+        """Spot-check that any BCP-47 tag is accepted (no validation)."""
+        for tag in ["en-US", "ja-JP", "zh-CN", "fr-FR", "ar-SA"]:
+            s = line_series(self.table)
+            c = chart(s, locale=tag)
+            self.assertEqual(c.chart_options["localization"]["locale"], tag)
+
+    # --- Localization: tickmarks_price_formatter ---
+
+    def test_tickmarks_price_formatter(self):
+        s = line_series(self.table)
+        c = chart(s, tickmarks_price_formatter="currency_usd")
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["tickmarksPriceFormatterName"], "currency_usd")
+
+    def test_tickmarks_price_formatter_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("localization", c.chart_options)
+
+    def test_all_tickmarks_price_formatter_presets(self):
+        presets = [
+            "currency_usd",
+            "currency_eur",
+            "currency_gbp",
+            "currency_jpy",
+            "percent",
+            "compact",
+            "scientific",
+        ]
+        s = line_series(self.table)
+        for preset in presets:
+            c = chart(s, tickmarks_price_formatter=preset)
+            self.assertEqual(
+                c.chart_options["localization"]["tickmarksPriceFormatterName"],
+                preset,
+            )
+
+    # --- Localization: percentage_formatter ---
+
+    def test_percentage_formatter(self):
+        s = line_series(self.table)
+        c = chart(s, percentage_formatter="percent")
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["percentageFormatterName"], "percent")
+
+    def test_all_percentage_formatter_presets(self):
+        presets = ["percent", "percent_1dp", "percent_0dp", "decimal"]
+        s = line_series(self.table)
+        for preset in presets:
+            c = chart(s, percentage_formatter=preset)
+            self.assertEqual(
+                c.chart_options["localization"]["percentageFormatterName"],
+                preset,
+            )
+
+    # --- Localization: tickmarks_percentage_formatter ---
+
+    def test_tickmarks_percentage_formatter(self):
+        s = line_series(self.table)
+        c = chart(s, tickmarks_percentage_formatter="percent_1dp")
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["tickmarksPercentageFormatterName"], "percent_1dp")
+
+    # --- Localization: combined options ---
+
+    def test_locale_with_price_formatter(self):
+        """locale and price_formatter can coexist in the same localization dict."""
+        s = line_series(self.table)
+        c = chart(s, locale="en-GB", price_formatter="currency_gbp")
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["locale"], "en-GB")
+        self.assertEqual(loc["priceFormatterName"], "currency_gbp")
+
+    def test_all_localization_options_combined(self):
+        """All five localization options together produce a single dict."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            locale="de-DE",
+            price_formatter="currency_eur",
+            tickmarks_price_formatter="compact",
+            percentage_formatter="percent_1dp",
+            tickmarks_percentage_formatter="percent_0dp",
+        )
+        loc = c.chart_options["localization"]
+        self.assertEqual(loc["locale"], "de-DE")
+        self.assertEqual(loc["priceFormatterName"], "currency_eur")
+        self.assertEqual(loc["tickmarksPriceFormatterName"], "compact")
+        self.assertEqual(loc["percentageFormatterName"], "percent_1dp")
+        self.assertEqual(loc["tickmarksPercentageFormatterName"], "percent_0dp")
+
+    def test_localization_absent_when_nothing_set(self):
+        """localization key must not appear when no localization param is given."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("localization", c.chart_options)
+
+    def test_none_options_not_in_output(self):
+        """Sections with all-None values should not appear in chart_options."""
+        s = line_series(self.table)
+        c = chart(s)  # all defaults are None
+        # layout is always present because fontFamily defaults to "Fira, sans-serif"
+        self.assertIn("layout", c.chart_options)
+        self.assertEqual(c.chart_options["layout"]["fontFamily"], "Fira, sans-serif")
+        self.assertNotIn("grid", c.chart_options)
+        self.assertNotIn("crosshair", c.chart_options)
+        self.assertNotIn("rightPriceScale", c.chart_options)
+        self.assertNotIn("leftPriceScale", c.chart_options)
+        self.assertNotIn("timeScale", c.chart_options)
+        self.assertNotIn("watermark", c.chart_options)
+        self.assertNotIn("trackingMode", c.chart_options)
+        self.assertNotIn("addDefaultPane", c.chart_options)
+
+    # --- tracking_mode_exit_mode tests ---
+
+    def test_tracking_mode_on_next_tap(self):
+        """tracking_mode_exit_mode='on_next_tap' should emit exitMode=1."""
+        s = line_series(self.table)
+        c = chart(s, tracking_mode_exit_mode="on_next_tap")
+        tm = c.chart_options["trackingMode"]
+        self.assertEqual(tm["exitMode"], 1)
+
+    def test_tracking_mode_on_touch_end(self):
+        """tracking_mode_exit_mode='on_touch_end' should emit exitMode=0."""
+        s = line_series(self.table)
+        c = chart(s, tracking_mode_exit_mode="on_touch_end")
+        tm = c.chart_options["trackingMode"]
+        self.assertEqual(tm["exitMode"], 0)
+
+    def test_tracking_mode_not_set_by_default(self):
+        """trackingMode should not appear in chart_options when not specified."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("trackingMode", c.chart_options)
+
+    def test_tracking_mode_all_values(self):
+        """Enumerate all TrackingModeExitMode values to verify correct mapping."""
+        s = line_series(self.table)
+        expected = {"on_touch_end": 0, "on_next_tap": 1}
+        for mode_name, mode_value in expected.items():
+            c = chart(s, tracking_mode_exit_mode=mode_name)
+            self.assertEqual(
+                c.chart_options["trackingMode"]["exitMode"],
+                mode_value,
+                f"tracking_mode_exit_mode={mode_name!r} should map to {mode_value}",
+            )
+
+    # --- add_default_pane tests ---
+
+    def test_add_default_pane_true(self):
+        """add_default_pane=True should set addDefaultPane to True."""
+        s = line_series(self.table)
+        c = chart(s, add_default_pane=True)
+        self.assertTrue(c.chart_options["addDefaultPane"])
+
+    def test_add_default_pane_false(self):
+        """add_default_pane=False suppresses the automatic initial pane."""
+        s = line_series(self.table)
+        c = chart(s, add_default_pane=False)
+        self.assertFalse(c.chart_options["addDefaultPane"])
+
+    def test_add_default_pane_not_set_by_default(self):
+        """addDefaultPane should not appear in chart_options when not specified."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("addDefaultPane", c.chart_options)
+
+    def test_partial_grid_only_vert(self):
+        """Setting only vertical grid lines should not create horzLines."""
+        s = line_series(self.table)
+        c = chart(s, vert_lines_visible=True)
+        grid = c.chart_options["grid"]
+        self.assertIn("vertLines", grid)
+        self.assertNotIn("horzLines", grid)
+
+    def test_precompute_conflation_priority(self):
+        """precompute_conflation_priority should pass through as a string."""
+        s = line_series(self.table)
+        c = chart(s, precompute_conflation_priority="background")
+        self.assertEqual(
+            c.chart_options["timeScale"]["precomputeConflationPriority"], "background"
+        )
+
+    def test_precompute_conflation_priority_user_visible(self):
+        s = line_series(self.table)
+        c = chart(s, precompute_conflation_priority="user-visible")
+        self.assertEqual(
+            c.chart_options["timeScale"]["precomputeConflationPriority"], "user-visible"
+        )
+
+    def test_precompute_conflation_priority_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        # timeScale should either be absent or not contain the key
+        ts = c.chart_options.get("timeScale", {})
+        self.assertNotIn("precomputeConflationPriority", ts)
+
+
+class TestLayoutOptions(unittest.TestCase):
+    """Tests for layout options: gradient background, attribution_logo, color_space."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    # --- Gradient background tests ---
+
+    def test_gradient_background(self):
+        """Both gradient params should produce a gradient background object."""
+        s = line_series(self.table)
+        c = chart(s, background_top_color="#ff0000", background_bottom_color="#0000ff")
+        layout = c.chart_options["layout"]
+        self.assertEqual(
+            layout["background"],
+            {"type": "gradient", "topColor": "#ff0000", "bottomColor": "#0000ff"},
+        )
+
+    def test_gradient_background_does_not_include_solid_key(self):
+        """Gradient background must not contain 'color' key."""
+        s = line_series(self.table)
+        c = chart(s, background_top_color="#aaa", background_bottom_color="#bbb")
+        bg = c.chart_options["layout"]["background"]
+        self.assertNotIn("color", bg)
+        self.assertEqual(bg["type"], "gradient")
+
+    def test_solid_background_still_works(self):
+        """Existing background_color usage must remain unchanged."""
+        s = line_series(self.table)
+        c = chart(s, background_color="#1a1a2e")
+        self.assertEqual(
+            c.chart_options["layout"]["background"],
+            {"type": "solid", "color": "#1a1a2e"},
+        )
+
+    def test_gradient_and_solid_conflict_raises(self):
+        """Providing both background_color and gradient params must raise ValueError."""
+        s = line_series(self.table)
+        with self.assertRaises(ValueError) as ctx:
+            chart(
+                s,
+                background_color="#000",
+                background_top_color="#111",
+                background_bottom_color="#222",
+            )
+        self.assertIn("background_color", str(ctx.exception))
+
+    def test_gradient_and_solid_conflict_with_only_top(self):
+        """background_color + background_top_color alone must raise ValueError."""
+        s = line_series(self.table)
+        with self.assertRaises(ValueError):
+            chart(s, background_color="#000", background_top_color="#111")
+
+    def test_gradient_missing_bottom_raises(self):
+        """Providing only background_top_color without background_bottom_color raises."""
+        s = line_series(self.table)
+        with self.assertRaises(ValueError) as ctx:
+            chart(s, background_top_color="#ff0000")
+        self.assertIn("background_bottom_color", str(ctx.exception))
+
+    def test_gradient_missing_top_raises(self):
+        """Providing only background_bottom_color without background_top_color raises."""
+        s = line_series(self.table)
+        with self.assertRaises(ValueError) as ctx:
+            chart(s, background_bottom_color="#0000ff")
+        self.assertIn("background_top_color", str(ctx.exception))
+
+    def test_gradient_with_other_layout_options(self):
+        """Gradient background can coexist with font_size and text_color."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            background_top_color="#000",
+            background_bottom_color="#333",
+            text_color="#fff",
+            font_size=13,
+        )
+        layout = c.chart_options["layout"]
+        self.assertEqual(layout["background"]["type"], "gradient")
+        self.assertEqual(layout["textColor"], "#fff")
+        self.assertEqual(layout["fontSize"], 13)
+
+    def test_no_background_params_omits_background_key(self):
+        """When no background param is set, layout must not contain 'background' key."""
+        s = line_series(self.table)
+        c = chart(s, text_color="#eee")
+        layout = c.chart_options["layout"]
+        self.assertNotIn("background", layout)
+
+    # --- attribution_logo tests ---
+
+    def test_attribution_logo_false(self):
+        """attribution_logo=False should set attributionLogo: false in layout."""
+        s = line_series(self.table)
+        c = chart(s, attribution_logo=False)
+        layout = c.chart_options["layout"]
+        self.assertFalse(layout["attributionLogo"])
+
+    def test_attribution_logo_true(self):
+        """attribution_logo=True should set attributionLogo: true in layout."""
+        s = line_series(self.table)
+        c = chart(s, attribution_logo=True)
+        layout = c.chart_options["layout"]
+        self.assertTrue(layout["attributionLogo"])
+
+    def test_attribution_logo_not_set_by_default(self):
+        """attributionLogo must not appear in layout unless explicitly set."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("attributionLogo", c.chart_options.get("layout", {}))
+
+    def test_attribution_logo_false_creates_layout_section(self):
+        """attribution_logo alone should produce a layout section."""
+        s = line_series(self.table)
+        c = chart(s, attribution_logo=False)
+        self.assertIn("layout", c.chart_options)
+        self.assertFalse(c.chart_options["layout"]["attributionLogo"])
+
+    # --- color_space tests ---
+
+    def test_color_space_srgb(self):
+        """color_space='srgb' should appear as 'colorSpace' in layout."""
+        s = line_series(self.table)
+        c = chart(s, color_space="srgb")
+        self.assertEqual(c.chart_options["layout"]["colorSpace"], "srgb")
+
+    def test_color_space_display_p3(self):
+        """color_space='display-p3' should appear verbatim in layout."""
+        s = line_series(self.table)
+        c = chart(s, color_space="display-p3")
+        self.assertEqual(c.chart_options["layout"]["colorSpace"], "display-p3")
+
+    def test_color_space_not_set_by_default(self):
+        """colorSpace must not appear in layout unless explicitly set."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("colorSpace", c.chart_options.get("layout", {}))
+
+    # --- Backwards compatibility tests ---
+
+    def test_backwards_compat_background_color_solid(self):
+        """Original background_color usage must produce identical output to before."""
+        s = line_series(self.table)
+        c = chart(s, background_color="#1a1a2e", text_color="#e0e0e0", font_size=14)
+        layout = c.chart_options["layout"]
+        self.assertEqual(layout["background"], {"type": "solid", "color": "#1a1a2e"})
+        self.assertEqual(layout["textColor"], "#e0e0e0")
+        self.assertEqual(layout["fontSize"], 14)
+        # No gradient keys should appear
+        self.assertNotIn("topColor", layout["background"])
+        self.assertNotIn("bottomColor", layout["background"])
+
+    def test_all_new_layout_params_omitted_does_not_break_existing(self):
+        """chart() with no new layout params should only have the default font."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertEqual(
+            c.chart_options,
+            {"layout": {"fontFamily": "Fira, sans-serif"}},
+        )
+
+    def test_chart_with_gradient_and_candlestick_series(self):
+        """Gradient background works with candlestick series via chart()."""
+        s = candlestick_series(self.table)
+        c = chart(
+            s,
+            background_top_color="#111",
+            background_bottom_color="#333",
+        )
+        layout = c.chart_options["layout"]
+        self.assertEqual(layout["background"]["type"], "gradient")
+
+    def test_all_layout_options_combined(self):
+        """All new layout options can be used together."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            background_top_color="#000",
+            background_bottom_color="#333",
+            text_color="#fff",
+            font_size=14,
+            attribution_logo=False,
+            color_space="display-p3",
+        )
+        layout = c.chart_options["layout"]
+        self.assertEqual(layout["background"]["type"], "gradient")
+        self.assertEqual(layout["background"]["topColor"], "#000")
+        self.assertEqual(layout["background"]["bottomColor"], "#333")
+        self.assertEqual(layout["textColor"], "#fff")
+        self.assertEqual(layout["fontSize"], 14)
+        self.assertEqual(layout["fontFamily"], "Fira, sans-serif")
+        self.assertFalse(layout["attributionLogo"])
+        self.assertEqual(layout["colorSpace"], "display-p3")
+
+
+class TestConvenienceFunctions(unittest.TestCase):
+    """Tests for convenience chart creation functions."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_candlestick_convenience(self):
+        c = candlestick(self.table)
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(len(c.series_list), 1)
+        self.assertEqual(c.series_list[0].series_type, "Candlestick")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "Timestamp")
+        self.assertEqual(c.series_list[0].column_mapping["open"], "Open")
+
+    def test_candlestick_custom(self):
+        # Chart-styling options moved to tvl.chart(...) in the unified API.
+        c = chart(
+            candlestick(
+                self.table,
+                timestamp="Date",
+                open="O",
+                high="H",
+                low="L",
+                close="C",
+                up_color="green",
+                down_color="red",
+                title="OHLC",
+            ),
+            background_color="#000",
+        )
+        series = c.series_list[0]
+        self.assertEqual(series.column_mapping["time"], "Date")
+        self.assertEqual(series.options["upColor"], "green")
+        self.assertEqual(series.options["title"], "OHLC")
+        self.assertIn("layout", c.chart_options)
+
+    def test_candlestick_with_markers(self):
+        m = Marker(time="2024-01-01", text="Signal")
+        c = candlestick(self.table, markers=[m])
+        self.assertEqual(len(c.series_list[0].markers), 1)
+
+    def test_candlestick_with_price_lines(self):
+        pl = PriceLine(price=100.0)
+        c = candlestick(self.table, price_lines=[pl])
+        self.assertEqual(len(c.series_list[0].price_lines), 1)
+
+    def test_line_convenience(self):
+        c = line(self.table, "Timestamp", "Value")
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(len(c.series_list), 1)
+        self.assertEqual(c.series_list[0].series_type, "Line")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Value")
+
+    def test_line_custom(self):
+        c = chart(
+            line(
+                self.table,
+                timestamp="ts",
+                value="price",
+                color="red",
+                line_width=3,
+                title="Close Price",
+            ),
+            watermark_text="MSFT",
+        )
+        series = c.series_list[0]
+        self.assertEqual(series.column_mapping["time"], "ts")
+        self.assertEqual(series.options["color"], "red")
+        self.assertIn("watermark", c.chart_options)
+
+    def test_area_convenience(self):
+        c = area(self.table, "Timestamp", "Value")
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(c.series_list[0].series_type, "Area")
+
+    def test_area_custom(self):
+        c = chart(
+            area(
+                self.table,
+                timestamp="T",
+                value="V",
+                line_color="blue",
+                top_color="rgba(0,0,255,0.3)",
+                bottom_color="rgba(0,0,255,0.0)",
+                line_width=2,
+                title="Depth",
+            ),
+            time_visible=True,
+        )
+        series = c.series_list[0]
+        self.assertEqual(series.options["lineColor"], "blue")
+        self.assertEqual(series.options["topColor"], "rgba(0,0,255,0.3)")
+        ts = c.chart_options["timeScale"]
+        self.assertTrue(ts["timeVisible"])
+
+    def test_bar_convenience(self):
+        c = bar(self.table)
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(c.series_list[0].series_type, "Bar")
+
+    def test_bar_custom(self):
+        c = chart(
+            bar(
+                self.table,
+                timestamp="Date",
+                up_color="#26a69a",
+                down_color="#ef5350",
+            ),
+            crosshair_mode="magnet",
+        )
+        series = c.series_list[0]
+        self.assertEqual(series.options["upColor"], "#26a69a")
+        self.assertEqual(c.chart_options["crosshair"]["mode"], 1)
+
+    def test_baseline_convenience(self):
+        c = baseline(self.table, "Timestamp", "Value")
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(c.series_list[0].series_type, "Baseline")
+
+    def test_baseline_custom(self):
+        c = chart(
+            baseline(
+                self.table,
+                timestamp="T",
+                value="V",
+                base_value=50.0,
+                top_line_color="green",
+                bottom_line_color="red",
+                line_width=2,
+                title="Profit/Loss",
+            ),
+            text_color="#ddd",
+        )
+        series = c.series_list[0]
+        self.assertEqual(series.options["baseValue"]["price"], 50.0)
+        self.assertEqual(series.options["topLineColor"], "green")
+        self.assertEqual(c.chart_options["layout"]["textColor"], "#ddd")
+
+    def test_histogram_convenience(self):
+        c = histogram(self.table, "Timestamp", "Value")
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(c.series_list[0].series_type, "Histogram")
+
+    def test_histogram_custom(self):
+        c = chart(
+            histogram(
+                self.table,
+                timestamp="T",
+                value="Volume",
+                color="teal",
+                color_column="VolumeColor",
+                title="Vol",
+            ),
+        )
+        series = c.series_list[0]
+        self.assertEqual(series.column_mapping["value"], "Volume")
+        self.assertEqual(series.column_mapping["color"], "VolumeColor")
+        self.assertEqual(series.options["color"], "teal")
+
+
+class TestChartFullSerialization(unittest.TestCase):
+    """Integration-style tests for full chart serialization."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_full_round_trip(self):
+        """Build a chart and serialize it, verifying the complete structure."""
+        m = Marker(
+            time="2024-06-01",
+            position="aboveBar",
+            shape="arrowDown",
+            color="red",
+            text="Sell",
+        )
+        pl = PriceLine(price=200.0, color="blue", title="Target")
+        s = line_series(
+            self.table,
+            timestamp="Date",
+            value="Close",
+            color="#2962FF",
+            line_width=2,
+            title="AAPL",
+            markers=[m],
+            price_lines=[pl],
+        )
+        c = chart(
+            s,
+            background_color="#131722",
+            text_color="#d1d4dc",
+            crosshair_mode="normal",
+            time_visible=True,
+            watermark_text="AAPL",
+        )
+
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+
+        # Chart options
+        self.assertEqual(
+            result["chartOptions"]["layout"]["background"]["color"], "#131722"
+        )
+        self.assertEqual(result["chartOptions"]["layout"]["textColor"], "#d1d4dc")
+        self.assertEqual(result["chartOptions"]["crosshair"]["mode"], 0)
+        self.assertEqual(result["chartOptions"]["timeScale"]["timeVisible"], True)
+        self.assertEqual(result["chartOptions"]["watermark"]["text"], "AAPL")
+        self.assertTrue(result["chartOptions"]["watermark"]["visible"])
+
+        # Series
+        self.assertEqual(len(result["series"]), 1)
+        series_dict = result["series"][0]
+        self.assertEqual(series_dict["id"], "series_0")
+        self.assertEqual(series_dict["type"], "Line")
+        self.assertEqual(series_dict["options"]["color"], "#2962FF")
+        self.assertEqual(series_dict["options"]["lineWidth"], 2)
+        self.assertEqual(series_dict["options"]["title"], "AAPL")
+        self.assertEqual(series_dict["dataMapping"]["tableId"], 0)
+        self.assertEqual(series_dict["dataMapping"]["columns"]["time"], "Date")
+        self.assertEqual(series_dict["dataMapping"]["columns"]["value"], "Close")
+
+        # Markers and price lines
+        self.assertEqual(len(series_dict["markers"]), 1)
+        self.assertEqual(series_dict["markers"][0]["text"], "Sell")
+        self.assertEqual(len(series_dict["priceLines"]), 1)
+        self.assertEqual(series_dict["priceLines"][0]["price"], 200.0)
+
+    def test_multi_series_multi_table(self):
+        """Chart with multiple series on different tables."""
+        table_a = MagicMock(name="table_a")
+        table_b = MagicMock(name="table_b")
+        s1 = candlestick_series(table_a, title="Stock A")
+        s2 = line_series(table_b, value="RSI", title="RSI")
+        c = chart(s1, s2)
+
+        table_id_map = {id(table_a): 0, id(table_b): 1}
+        result = c.to_dict(table_id_map)
+
+        self.assertEqual(len(result["series"]), 2)
+        self.assertEqual(result["series"][0]["dataMapping"]["tableId"], 0)
+        self.assertEqual(result["series"][1]["dataMapping"]["tableId"], 1)
+        self.assertEqual(result["series"][0]["type"], "Candlestick")
+        self.assertEqual(result["series"][1]["type"], "Line")
+
+
+class TestPaneSeparatorOptions(unittest.TestCase):
+    """Tests for pane separator chart options."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_pane_separator_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            pane_separator_color="#333",
+            pane_separator_hover_color="#555",
+            pane_enable_resize=False,
+        )
+        panes = c.chart_options["layout"]["panes"]
+        self.assertEqual(panes["separatorColor"], "#333")
+        self.assertEqual(panes["separatorHoverColor"], "#555")
+        self.assertFalse(panes["enableResize"])
+
+    def test_pane_separator_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("panes", c.chart_options.get("layout", {}))
+
+    def test_pane_separator_partial(self):
+        s = line_series(self.table)
+        c = chart(s, pane_separator_color="#333")
+        panes = c.chart_options["layout"]["panes"]
+        self.assertEqual(panes["separatorColor"], "#333")
+        self.assertNotIn("separatorHoverColor", panes)
+
+    def test_pane_separator_with_background(self):
+        """Pane options should coexist with other layout options."""
+        s = line_series(self.table)
+        c = chart(s, background_color="#000", pane_separator_color="#333")
+        layout = c.chart_options["layout"]
+        self.assertEqual(layout["background"]["color"], "#000")
+        self.assertEqual(layout["panes"]["separatorColor"], "#333")
+
+
+class TestPaneStretchFactors(unittest.TestCase):
+    """Tests for pane stretch factors."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_stretch_factors_serialization(self):
+        s1 = candlestick_series(self.table, pane=0)
+        s2 = histogram_series(self.table, pane=1)
+        c = chart(s1, s2, pane_stretch_factors=[3.0, 1.0])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["paneStretchFactors"], [3.0, 1.0])
+
+    def test_stretch_factors_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertNotIn("paneStretchFactors", result)
+
+    def test_stretch_factors_top_level(self):
+        """Stretch factors should be top-level, not under chartOptions."""
+        s = line_series(self.table)
+        c = chart(s, pane_stretch_factors=[2.0, 1.0])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertNotIn("paneStretchFactors", result.get("chartOptions", {}))
+        self.assertIn("paneStretchFactors", result)
+
+    def test_stretch_factors_property(self):
+        s = line_series(self.table)
+        c = chart(s, pane_stretch_factors=[3.0, 1.0])
+        self.assertEqual(c.pane_stretch_factors, [3.0, 1.0])
+
+    def test_stretch_factors_none_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertIsNone(c.pane_stretch_factors)
+
+    def test_existing_stretch_factors_unaffected(self):
+        """Adding pane_preserve_empty must not change paneStretchFactors behavior."""
+        s1 = candlestick_series(self.table, pane=0)
+        s2 = histogram_series(self.table, pane=1)
+        c = chart(s1, s2, pane_stretch_factors=[3.0, 1.0])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["paneStretchFactors"], [3.0, 1.0])
+        self.assertNotIn("panePreserveEmpty", result)
+
+
+class TestPanePreserveEmpty(unittest.TestCase):
+    """Tests for pane_preserve_empty on chart()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_preserve_empty_serialization(self):
+        """pane_preserve_empty list should appear as top-level panePreserveEmpty."""
+        s1 = candlestick_series(self.table, pane=0)
+        s2 = histogram_series(self.table, pane=1)
+        c = chart(s1, s2, pane_preserve_empty=[True, False])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["panePreserveEmpty"], [True, False])
+
+    def test_preserve_empty_not_set_by_default(self):
+        """panePreserveEmpty must be absent from output when not specified."""
+        s = line_series(self.table)
+        c = chart(s)
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertNotIn("panePreserveEmpty", result)
+
+    def test_preserve_empty_top_level(self):
+        """panePreserveEmpty must be top-level, not nested inside chartOptions."""
+        s = line_series(self.table)
+        c = chart(s, pane_preserve_empty=[True])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertNotIn("panePreserveEmpty", result.get("chartOptions", {}))
+        self.assertIn("panePreserveEmpty", result)
+
+    def test_preserve_empty_single_pane(self):
+        """Single-element list with True."""
+        s = line_series(self.table, pane=0)
+        c = chart(s, pane_preserve_empty=[True])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["panePreserveEmpty"], [True])
+
+    def test_preserve_empty_all_false(self):
+        """All False is a valid explicit list."""
+        s1 = line_series(self.table, pane=0)
+        s2 = histogram_series(self.table, pane=1)
+        c = chart(s1, s2, pane_preserve_empty=[False, False])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["panePreserveEmpty"], [False, False])
+
+    def test_preserve_empty_property_access(self):
+        """pane_preserve_empty should be accessible via property."""
+        s = line_series(self.table)
+        c = chart(s, pane_preserve_empty=[True, False])
+        self.assertEqual(c.pane_preserve_empty, [True, False])
+
+    def test_preserve_empty_none_property(self):
+        """pane_preserve_empty property returns None when not set."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertIsNone(c.pane_preserve_empty)
+
+    def test_preserve_empty_with_stretch_factors(self):
+        """pane_preserve_empty and pane_stretch_factors coexist as separate top-level keys."""
+        s1 = candlestick_series(self.table, pane=0)
+        s2 = histogram_series(self.table, pane=1)
+        c = chart(
+            s1, s2, pane_stretch_factors=[3.0, 1.0], pane_preserve_empty=[True, False]
+        )
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        self.assertEqual(result["paneStretchFactors"], [3.0, 1.0])
+        self.assertEqual(result["panePreserveEmpty"], [True, False])
+
+    def test_preserve_empty_more_entries_than_panes(self):
+        """Extra entries beyond pane count are valid (JS renderer ignores them)."""
+        s = line_series(self.table, pane=0)
+        c = chart(s, pane_preserve_empty=[True, True, True])
+        table_id_map = {id(self.table): 0}
+        result = c.to_dict(table_id_map)
+        # Serialized as-is; JS renderer bounds-checks against actual pane count
+        self.assertEqual(result["panePreserveEmpty"], [True, True, True])
+
+    def test_preserve_empty_tvl_chart_direct(self):
+        """TvlChart constructor should accept and store pane_preserve_empty."""
+        s = line_series(self.table)
+        c = TvlChart(
+            series_list=[s],
+            chart_options={},
+            pane_preserve_empty=[False, True],
+        )
+        self.assertEqual(c.pane_preserve_empty, [False, True])
+
+
+class TestTimeScaleOptions(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_new_time_scale_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            time_scale_ticks_visible=True,
+            shift_visible_range_on_new_bar=False,
+            lock_visible_time_range_on_resize=True,
+            right_bar_stays_on_scroll=True,
+            time_scale_minimum_height=40,
+            allow_bold_labels=False,
+            tick_mark_max_character_length=12,
+            uniform_distribution=True,
+            max_bar_spacing=20.0,
+            right_offset_pixels=50,
+            time_scale_visible=False,
+        )
+        ts = c.chart_options["timeScale"]
+        self.assertTrue(ts["ticksVisible"])
+        self.assertFalse(ts["shiftVisibleRangeOnNewBar"])
+        self.assertTrue(ts["lockVisibleTimeRangeOnResize"])
+        self.assertTrue(ts["rightBarStaysOnScroll"])
+        self.assertEqual(ts["minimumHeight"], 40)
+        self.assertFalse(ts["allowBoldLabels"])
+        self.assertEqual(ts["tickMarkMaxCharacterLength"], 12)
+        self.assertTrue(ts["uniformDistribution"])
+        self.assertEqual(ts["maxBarSpacing"], 20.0)
+        self.assertEqual(ts["rightOffsetPixels"], 50)
+        self.assertFalse(ts["visible"])
+
+    def test_conflation_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            enable_conflation=True,
+            conflation_threshold_factor=4.0,
+            precompute_conflation_on_init=True,
+        )
+        ts = c.chart_options["timeScale"]
+        self.assertTrue(ts["enableConflation"])
+        self.assertEqual(ts["conflationThresholdFactor"], 4.0)
+        self.assertTrue(ts["precomputeConflationOnInit"])
+
+    def test_whitespace_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            ignore_whitespace_indices=True,
+            allow_shift_visible_range_on_whitespace_replacement=True,
+        )
+        ts = c.chart_options["timeScale"]
+        self.assertTrue(ts["ignoreWhitespaceIndices"])
+        self.assertTrue(ts["allowShiftVisibleRangeOnWhitespaceReplacement"])
+
+    def test_defaults_omit_new_options(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("timeScale", c.chart_options)
+
+
+class TestPriceScaleNewOptions(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_right_price_scale_new_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            right_price_scale_ticks_visible=True,
+            right_price_scale_align_labels=False,
+            right_price_scale_text_color="#FF0000",
+            right_price_scale_entire_text_only=True,
+            right_price_scale_minimum_width=80,
+            right_price_scale_ensure_edge_tick_marks_visible=True,
+        )
+        rps = c.chart_options["rightPriceScale"]
+        self.assertTrue(rps["ticksVisible"])
+        self.assertFalse(rps["alignLabels"])
+        self.assertEqual(rps["textColor"], "#FF0000")
+        self.assertTrue(rps["entireTextOnly"])
+        self.assertEqual(rps["minimumWidth"], 80)
+        self.assertTrue(rps["ensureEdgeTickMarksVisible"])
+
+    def test_left_price_scale_new_options(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            left_price_scale_ticks_visible=True,
+            left_price_scale_minimum_width=60,
+        )
+        lps = c.chart_options["leftPriceScale"]
+        self.assertTrue(lps["ticksVisible"])
+        self.assertEqual(lps["minimumWidth"], 60)
+
+    def test_hovered_series_on_top(self):
+        """hoveredSeriesOnTop is set when supplied; absent when None."""
+        s = line_series(self.table)
+        c = chart(s, hovered_series_on_top=False)
+        self.assertEqual(c.chart_options["hoveredSeriesOnTop"], False)
+        c2 = chart(s, hovered_series_on_top=True)
+        self.assertEqual(c2.chart_options["hoveredSeriesOnTop"], True)
+        c3 = chart(s)
+        self.assertNotIn("hoveredSeriesOnTop", c3.chart_options)
+
+    def test_default_visible_price_scale_id(self):
+        """defaultVisiblePriceScaleId passes through 'left'/'right' values."""
+        s = line_series(self.table)
+        for value in ("left", "right"):
+            c = chart(s, default_visible_price_scale_id=value)
+            self.assertEqual(c.chart_options["defaultVisiblePriceScaleId"], value)
+        c_none = chart(s)
+        self.assertNotIn("defaultVisiblePriceScaleId", c_none.chart_options)
+
+    def test_tick_mark_density(self):
+        """tickMarkDensity is set on each of right/left/overlay price scales."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            right_price_scale_tick_mark_density=4.0,
+            left_price_scale_tick_mark_density=1.5,
+            overlay_price_scale_tick_mark_density=3.0,
+        )
+        self.assertEqual(c.chart_options["rightPriceScale"]["tickMarkDensity"], 4.0)
+        self.assertEqual(c.chart_options["leftPriceScale"]["tickMarkDensity"], 1.5)
+        self.assertEqual(c.chart_options["overlayPriceScales"]["tickMarkDensity"], 3.0)
+        # Default: not present
+        c_none = chart(s)
+        self.assertNotIn("rightPriceScale", c_none.chart_options)
+        self.assertNotIn("leftPriceScale", c_none.chart_options)
+        self.assertNotIn("overlayPriceScales", c_none.chart_options)
+
+    def test_overlay_price_scale_defaults(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            overlay_price_scale_border_visible=False,
+            overlay_price_scale_ticks_visible=True,
+            overlay_price_scale_minimum_width=50,
+            overlay_price_scale_margin_top=0.7,
+            overlay_price_scale_margin_bottom=0.0,
+        )
+        ops = c.chart_options["overlayPriceScales"]
+        self.assertFalse(ops["borderVisible"])
+        self.assertTrue(ops["ticksVisible"])
+        self.assertEqual(ops["minimumWidth"], 50)
+        self.assertEqual(ops["scaleMargins"]["top"], 0.7)
+        self.assertEqual(ops["scaleMargins"]["bottom"], 0.0)
+
+    def test_overlay_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("overlayPriceScales", c.chart_options)
+
+    # --- Right price scale scaleMargins tests ---
+
+    def test_right_price_scale_margins(self):
+        """scaleMargins nested dict is built for right price scale."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            right_price_scale_margin_top=0.2,
+            right_price_scale_margin_bottom=0.1,
+        )
+        rps = c.chart_options["rightPriceScale"]
+        self.assertIn("scaleMargins", rps)
+        self.assertEqual(rps["scaleMargins"]["top"], 0.2)
+        self.assertEqual(rps["scaleMargins"]["bottom"], 0.1)
+
+    def test_right_price_scale_margin_top_only(self):
+        """Providing only top margin still creates scaleMargins with only top key."""
+        s = line_series(self.table)
+        c = chart(s, right_price_scale_margin_top=0.3)
+        rps = c.chart_options["rightPriceScale"]
+        self.assertEqual(rps["scaleMargins"]["top"], 0.3)
+        self.assertNotIn("bottom", rps["scaleMargins"])
+
+    def test_right_price_scale_margin_with_other_props(self):
+        """scaleMargins coexists correctly with other right price scale properties."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            right_price_scale_visible=True,
+            right_price_scale_margin_top=0.15,
+            right_price_scale_margin_bottom=0.05,
+        )
+        rps = c.chart_options["rightPriceScale"]
+        self.assertTrue(rps["visible"])
+        self.assertEqual(rps["scaleMargins"], {"top": 0.15, "bottom": 0.05})
+
+    def test_right_price_scale_margins_not_set_by_default(self):
+        """No scaleMargins key in rightPriceScale when margin params are None."""
+        s = line_series(self.table)
+        c = chart(s, right_price_scale_visible=True)
+        rps = c.chart_options["rightPriceScale"]
+        self.assertNotIn("scaleMargins", rps)
+
+    # --- Left price scale scaleMargins tests ---
+
+    def test_left_price_scale_margins(self):
+        """scaleMargins nested dict is built for left price scale."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            left_price_scale_margin_top=0.1,
+            left_price_scale_margin_bottom=0.2,
+        )
+        lps = c.chart_options["leftPriceScale"]
+        self.assertIn("scaleMargins", lps)
+        self.assertEqual(lps["scaleMargins"]["top"], 0.1)
+        self.assertEqual(lps["scaleMargins"]["bottom"], 0.2)
+
+    def test_left_price_scale_margin_bottom_only(self):
+        """Providing only bottom margin produces scaleMargins with only bottom key."""
+        s = line_series(self.table)
+        c = chart(s, left_price_scale_margin_bottom=0.05)
+        lps = c.chart_options["leftPriceScale"]
+        self.assertNotIn("top", lps["scaleMargins"])
+        self.assertEqual(lps["scaleMargins"]["bottom"], 0.05)
+
+    # --- Overlay price scale: 8 new properties ---
+
+    def test_overlay_price_scale_auto_scale(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_auto_scale=True)
+        self.assertTrue(c.chart_options["overlayPriceScales"]["autoScale"])
+
+    def test_overlay_price_scale_mode(self):
+        """overlay_price_scale_mode is serialized via PRICE_SCALE_MODE_MAP."""
+        s = line_series(self.table)
+        modes = {
+            "normal": 0,
+            "logarithmic": 1,
+            "percentage": 2,
+            "indexed_to_100": 3,
+        }
+        for mode_name, expected in modes.items():
+            c = chart(s, overlay_price_scale_mode=mode_name)
+            self.assertEqual(
+                c.chart_options["overlayPriceScales"]["mode"],
+                expected,
+                f"Mode '{mode_name}' should map to {expected}",
+            )
+
+    def test_overlay_price_scale_invert_scale(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_invert_scale=True)
+        self.assertTrue(c.chart_options["overlayPriceScales"]["invertScale"])
+
+    def test_overlay_price_scale_align_labels(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_align_labels=False)
+        self.assertFalse(c.chart_options["overlayPriceScales"]["alignLabels"])
+
+    def test_overlay_price_scale_border_color(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_border_color="#aabbcc")
+        self.assertEqual(
+            c.chart_options["overlayPriceScales"]["borderColor"], "#aabbcc"
+        )
+
+    def test_overlay_price_scale_text_color(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_text_color="#ffffff")
+        self.assertEqual(c.chart_options["overlayPriceScales"]["textColor"], "#ffffff")
+
+    def test_overlay_price_scale_entire_text_only(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_entire_text_only=True)
+        self.assertTrue(c.chart_options["overlayPriceScales"]["entireTextOnly"])
+
+    def test_overlay_price_scale_ensure_edge_tick_marks_visible(self):
+        s = line_series(self.table)
+        c = chart(s, overlay_price_scale_ensure_edge_tick_marks_visible=True)
+        self.assertTrue(
+            c.chart_options["overlayPriceScales"]["ensureEdgeTickMarksVisible"]
+        )
+
+    def test_overlay_price_scale_all_new_props(self):
+        """All 8 new overlay props serialize correctly and coexist with the 4 existing ones."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            # existing props
+            overlay_price_scale_border_visible=True,
+            overlay_price_scale_ticks_visible=False,
+            overlay_price_scale_minimum_width=50,
+            overlay_price_scale_margin_top=0.1,
+            overlay_price_scale_margin_bottom=0.05,
+            # new props
+            overlay_price_scale_auto_scale=False,
+            overlay_price_scale_mode="percentage",
+            overlay_price_scale_invert_scale=True,
+            overlay_price_scale_align_labels=False,
+            overlay_price_scale_border_color="#111111",
+            overlay_price_scale_text_color="#eeeeee",
+            overlay_price_scale_entire_text_only=True,
+            overlay_price_scale_ensure_edge_tick_marks_visible=True,
+        )
+        ops = c.chart_options["overlayPriceScales"]
+        # existing
+        self.assertTrue(ops["borderVisible"])
+        self.assertFalse(ops["ticksVisible"])
+        self.assertEqual(ops["minimumWidth"], 50)
+        self.assertEqual(ops["scaleMargins"], {"top": 0.1, "bottom": 0.05})
+        # new
+        self.assertFalse(ops["autoScale"])
+        self.assertEqual(ops["mode"], 2)  # "percentage" -> 2
+        self.assertTrue(ops["invertScale"])
+        self.assertFalse(ops["alignLabels"])
+        self.assertEqual(ops["borderColor"], "#111111")
+        self.assertEqual(ops["textColor"], "#eeeeee")
+        self.assertTrue(ops["entireTextOnly"])
+        self.assertTrue(ops["ensureEdgeTickMarksVisible"])
+
+    def test_overlay_price_scale_not_set_by_default(self):
+        """overlayPriceScales key absent when no overlay params provided."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("overlayPriceScales", c.chart_options)
+
+
+class TestChartType(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_default_chart_type(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertEqual(c.chart_type, "standard")
+
+    def test_default_chart_type_in_to_dict(self):
+        s = line_series(self.table)
+        c = chart(s)
+        result = c.to_dict({id(self.table): 0})
+        self.assertEqual(result["chartType"], "standard")
+
+    def test_yield_curve_chart_type(self):
+        s = line_series(self.table, timestamp="Months", value="Yield")
+        c = chart(s, chart_type="yield_curve")
+        self.assertEqual(c.chart_type, "yieldCurve")
+
+    def test_yield_curve_in_to_dict(self):
+        s = line_series(self.table)
+        c = chart(s, chart_type="yield_curve")
+        result = c.to_dict({id(self.table): 0})
+        self.assertEqual(result["chartType"], "yieldCurve")
+
+    def test_options_chart_type(self):
+        s = line_series(self.table, timestamp="Strike", value="Premium")
+        c = chart(s, chart_type="options")
+        self.assertEqual(c.chart_type, "options")
+
+    def test_options_in_to_dict(self):
+        s = line_series(self.table)
+        c = chart(s, chart_type="options")
+        result = c.to_dict({id(self.table): 0})
+        self.assertEqual(result["chartType"], "options")
+
+    def test_yield_curve_options_serialized(self):
+        s = line_series(self.table)
+        c = chart(
+            s,
+            chart_type="yield_curve",
+            base_resolution=1,
+            minimum_time_range=120,
+            start_time_range=0,
+        )
+        self.assertIn("yieldCurve", c.chart_options)
+        self.assertEqual(c.chart_options["yieldCurve"]["baseResolution"], 1)
+        self.assertEqual(c.chart_options["yieldCurve"]["minimumTimeRange"], 120)
+        self.assertEqual(c.chart_options["yieldCurve"]["startTimeRange"], 0)
+
+    def test_yield_curve_options_omitted_when_not_set(self):
+        s = line_series(self.table)
+        c = chart(s, chart_type="yield_curve")
+        self.assertNotIn("yieldCurve", c.chart_options)
+
+    def test_yield_curve_rejects_candlestick(self):
+        s = candlestick_series(self.table)
+        with self.assertRaises(ValueError):
+            chart(s, chart_type="yield_curve")
+
+    def test_yield_curve_rejects_bar(self):
+        s = bar_series(self.table)
+        with self.assertRaises(ValueError):
+            chart(s, chart_type="yield_curve")
+
+    def test_yield_curve_rejects_histogram(self):
+        s = histogram_series(self.table)
+        with self.assertRaises(ValueError):
+            chart(s, chart_type="yield_curve")
+
+    def test_yield_curve_rejects_baseline(self):
+        s = baseline_series(self.table)
+        with self.assertRaises(ValueError):
+            chart(s, chart_type="yield_curve")
+
+    def test_yield_curve_allows_line(self):
+        s = line_series(self.table)
+        c = chart(s, chart_type="yield_curve")
+        self.assertEqual(c.chart_type, "yieldCurve")
+
+    def test_yield_curve_allows_area(self):
+        s = area_series(self.table)
+        c = chart(s, chart_type="yield_curve")
+        self.assertEqual(c.chart_type, "yieldCurve")
+
+    def test_options_allows_any_series_type(self):
+        for fn in [
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ]:
+            s = fn(self.table)
+            c = chart(s, chart_type="options")
+            self.assertEqual(c.chart_type, "options")
+
+    def test_unknown_chart_type_raises(self):
+        """Unrecognised chart_type should raise ValueError, not silently use 'standard'."""
+        s = line_series(self.table)
+        with self.assertRaises(ValueError) as ctx:
+            chart(s, chart_type="unknown_type")
+        self.assertIn("unknown_type", str(ctx.exception))
+        self.assertIn("createChartEx", str(ctx.exception))
+
+    def test_typo_chart_type_raises(self):
+        """Typos like 'yield-curve' or 'yieldcurve' should raise, not silently fall through."""
+        s = line_series(self.table)
+        with self.assertRaises(ValueError):
+            chart(s, chart_type="yieldcurve")  # missing underscore
+        with self.assertRaises(ValueError):
+            chart(s, chart_type="yield-curve")  # hyphen instead of underscore
+
+    def test_custom_numeric_chart_type(self):
+        """'custom_numeric' should be accepted and map to 'options' in the wire format."""
+        s = line_series(self.table, timestamp="X", value="Y")
+        c = chart(s, chart_type="custom_numeric")
+        # The Python-side chart_type stores the resolved JS value
+        self.assertEqual(c.chart_type, "options")
+
+    def test_custom_numeric_in_to_dict(self):
+        """JSON payload should emit 'options' for custom_numeric."""
+        s = line_series(self.table)
+        c = chart(s, chart_type="custom_numeric")
+        result = c.to_dict({id(self.table): 0})
+        self.assertEqual(result["chartType"], "options")
+
+    def test_none_chart_type_defaults_to_standard(self):
+        """chart_type=None should default to 'standard' without raising."""
+        s = line_series(self.table)
+        c = chart(s, chart_type=None)
+        self.assertEqual(c.chart_type, "standard")
+
+
+class TestYieldCurveConvenience(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        c = yield_curve(self.table)
+        self.assertEqual(c.chart_type, "yieldCurve")
+        self.assertEqual(len(c.series_list), 1)
+        self.assertEqual(c.series_list[0].series_type, "Line")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "Maturity")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Yield")
+
+    def test_area_series_type(self):
+        c = yield_curve(self.table, series_type="area")
+        self.assertEqual(c.series_list[0].series_type, "Area")
+
+    def test_custom_columns(self):
+        c = yield_curve(self.table, maturity="Months", value="Rate")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "Months")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Rate")
+
+    def test_yield_curve_options_pass_through(self):
+        c = yield_curve(self.table, base_resolution=1, minimum_time_range=240)
+        self.assertEqual(c.chart_options["yieldCurve"]["baseResolution"], 1)
+        self.assertEqual(c.chart_options["yieldCurve"]["minimumTimeRange"], 240)
+
+    def test_styling_pass_through(self):
+        c = yield_curve(self.table, color="#2962FF", line_width=2, title="Yield")
+        opts = c.series_list[0].options
+        self.assertEqual(opts["color"], "#2962FF")
+        self.assertEqual(opts["lineWidth"], 2)
+        self.assertEqual(opts["title"], "Yield")
+
+
+class TestOptionsChartConvenience(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        c = options_chart(self.table)
+        self.assertEqual(c.chart_type, "options")
+        self.assertEqual(len(c.series_list), 1)
+        self.assertEqual(c.series_list[0].series_type, "Line")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "Strike")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Value")
+
+    def test_custom_columns(self):
+        c = options_chart(self.table, strike="StrikePrice", value="Premium")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "StrikePrice")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Premium")
+
+    def test_area_series_type(self):
+        c = options_chart(self.table, series_type="area")
+        self.assertEqual(c.series_list[0].series_type, "Area")
+
+    def test_histogram_series_type(self):
+        c = options_chart(self.table, series_type="histogram")
+        self.assertEqual(c.series_list[0].series_type, "Histogram")
+
+
+class TestCustomNumericConvenience(unittest.TestCase):
+    """Tests for the custom_numeric() convenience function."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        """Default call: line series, x='X', value='Value', chartType='options'."""
+        c = custom_numeric(self.table)
+        self.assertIsInstance(c, TvlChart)
+        self.assertEqual(len(c.series_list), 1)
+        self.assertEqual(c.series_list[0].series_type, "Line")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "X")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Value")
+        self.assertEqual(c.chart_type, "options")  # wire value
+
+    def test_custom_columns(self):
+        c = custom_numeric(self.table, x="Frequency", value="Amplitude")
+        self.assertEqual(c.series_list[0].column_mapping["time"], "Frequency")
+        self.assertEqual(c.series_list[0].column_mapping["value"], "Amplitude")
+
+    def test_area_series_type(self):
+        c = custom_numeric(self.table, series_type="area")
+        self.assertEqual(c.series_list[0].series_type, "Area")
+
+    def test_histogram_series_type(self):
+        c = custom_numeric(self.table, series_type="histogram")
+        self.assertEqual(c.series_list[0].series_type, "Histogram")
+
+    def test_line_styling(self):
+        c = custom_numeric(self.table, color="#2962FF", line_width=2, title="IV Smile")
+        opts = c.series_list[0].options
+        self.assertEqual(opts["color"], "#2962FF")
+        self.assertEqual(opts["lineWidth"], 2)
+        self.assertEqual(opts["title"], "IV Smile")
+
+    def test_area_styling_passthrough(self):
+        c = custom_numeric(
+            self.table,
+            series_type="area",
+            line_color="#00f",
+            top_color="rgba(0,0,255,0.3)",
+            bottom_color="rgba(0,0,255,0.0)",
+        )
+        opts = c.series_list[0].options
+        self.assertEqual(opts["lineColor"], "#00f")
+        self.assertEqual(opts["topColor"], "rgba(0,0,255,0.3)")
+
+    def test_color_falls_back_to_line_color_for_area(self):
+        """When color is set but line_color is not, color should feed lineColor."""
+        c = custom_numeric(self.table, series_type="area", color="#ff0000")
+        opts = c.series_list[0].options
+        self.assertEqual(opts["lineColor"], "#ff0000")
+
+    def test_chart_options_pass_through(self):
+        c = custom_numeric(
+            self.table,
+            background_color="#000",
+            text_color="#fff",
+            crosshair_mode="normal",
+            watermark_text="VOL",
+        )
+        self.assertEqual(c.chart_options["layout"]["background"]["color"], "#000")
+        self.assertEqual(c.chart_options["layout"]["textColor"], "#fff")
+        self.assertEqual(c.chart_options["crosshair"]["mode"], 0)
+        self.assertEqual(c.chart_options["watermark"]["text"], "VOL")
+
+    def test_to_dict_structure(self):
+        c = custom_numeric(self.table, x="Strike", value="Delta")
+        result = c.to_dict({id(self.table): 0})
+        self.assertEqual(result["chartType"], "options")
+        self.assertEqual(len(result["series"]), 1)
+        self.assertEqual(
+            result["series"][0]["dataMapping"]["columns"]["time"], "Strike"
+        )
+        self.assertEqual(
+            result["series"][0]["dataMapping"]["columns"]["value"], "Delta"
+        )
+
+    def test_invalid_series_type_raises(self):
+        """Unknown series_type strings should raise ValueError."""
+        with self.assertRaises(ValueError):
+            custom_numeric(self.table, series_type="invalid")
+
+
+class TestLiveness(unittest.TestCase):
+    """Tests for LivenessScope integration."""
+
+    def test_liveness_scope_none_in_test_env(self):
+        """Without a real DH server, LivenessScope is None so _liveness_scope is None."""
+        table = MagicMock(name="table")
+        s = line_series(table)
+        c = TvlChart([s], {})
+        # In test env, LivenessScope import fails → _liveness_scope is None
+        self.assertIsNone(c._liveness_scope)
+
+    def test_partition_metadata_defaults(self):
+        table = MagicMock(name="table")
+        s = line_series(table, "T", "V")
+        c = TvlChart([s], {})
+        # No series carries a by template by default.
+        self.assertEqual(c.partitioned_series, [])
+        self.assertIsNone(c.series_list[0].by)
+        self.assertIsNone(c.series_list[0].partitioned_table)
+
+    def test_del_no_error_when_scope_none(self):
+        table = MagicMock(name="table")
+        s = line_series(table)
+        c = TvlChart([s], {})
+        # Should not raise even though _liveness_scope is None
+        del c
+
+
+class TestByParameter(unittest.TestCase):
+    """Tests for the by parameter on line() and area()."""
+
+    def _make_mock_partition(self, keys, rows_per_key=5):
+        """Create a mock PartitionedTable with constituent tables."""
+        constituents = []
+        for key in keys:
+            mock_table = MagicMock(name=f"table_{key}")
+            mock_table.size = rows_per_key
+            # Mock j_table.getColumnSource(col).get(0) → key string
+            key_source = MagicMock()
+            key_source.get = MagicMock(return_value=key)
+            mock_table.j_table.getColumnSource = MagicMock(return_value=key_source)
+            constituents.append(mock_table)
+
+        partitioned = MagicMock(name="partitioned_table")
+        partitioned.constituent_tables = constituents
+
+        meta_table = MagicMock()
+        meta_table.is_refreshing = False
+        partitioned.table = meta_table
+
+        return partitioned, constituents
+
+    def test_per_series_partition_in_to_dict(self):
+        """When `by=` is used, each series carries a `partition` block."""
+        from deephaven.plot.tradingview_lightweight.series import line_series
+
+        spec = line_series(MagicMock(name="t"), timestamp="Timestamp", value="Price")
+        spec.by = "Sym"
+        spec.partitioned_table = MagicMock(name="pt")
+
+        c = TvlChart([spec], {})
+        d = c.to_dict({id(spec.table): 0})
+        # No top-level partitionSpec anymore — it lives on each series.
+        self.assertNotIn("partitionSpec", d)
+        self.assertEqual(d["series"][0]["partition"]["byColumn"], "Sym")
+
+    def test_line_without_by_unchanged(self):
+        """line() without by should produce a single series, no partition state."""
+        table = MagicMock(name="table")
+        c = line(table, timestamp="T", value="V", color="red")
+        self.assertEqual(len(c.series_list), 1)
+        self.assertEqual(c.series_list[0].options.get("color"), "red")
+        self.assertIsNone(c.series_list[0].by)
+        self.assertIsNone(c.series_list[0].partitioned_table)
+
+    def test_area_without_by_unchanged(self):
+        table = MagicMock(name="table")
+        c = area(table, timestamp="T", value="V", line_color="blue")
+        self.assertEqual(len(c.series_list), 1)
+        self.assertIsNone(c.series_list[0].by)
+
+    def test_chart_compose_extracts_series_from_tvl_charts(self):
+        """tvl.chart accepts TvlChart sources and concatenates their series."""
+        table = MagicMock(name="t")
+        c1 = line(table, "T", "V", color="red")
+        c2 = histogram(table, "T", "V", pane=1)
+        combined = chart(c1, c2, pane_stretch_factors=[3, 1])
+        self.assertEqual(len(combined.series_list), 2)
+        self.assertEqual(combined.series_list[0].series_type, "Line")
+        self.assertEqual(combined.series_list[1].series_type, "Histogram")
+        self.assertEqual(combined.series_list[1].pane, 1)
+        self.assertEqual(combined.pane_stretch_factors, [3, 1])
+
+
+class TestColumnValidation(unittest.TestCase):
+    """Mapped data columns are validated against the table at build time."""
+
+    @staticmethod
+    def _table(*col_names):
+        """A mock table whose ``.columns`` expose the given names."""
+        cols = []
+        for n in col_names:
+            c = MagicMock()
+            c.name = n
+            cols.append(c)
+        t = MagicMock(name="table")
+        t.columns = cols
+        return t
+
+    def test_missing_value_column_raises(self):
+        t = self._table("Timestamp", "Value")
+        with self.assertRaises(ValueError) as ctx:
+            line(t, timestamp="Timestamp", value="Ema")
+        msg = str(ctx.exception)
+        self.assertIn("Ema", msg)
+        self.assertIn("Value", msg)  # available columns listed
+
+    def test_missing_timestamp_column_raises(self):
+        t = self._table("Timestamp", "Value")
+        with self.assertRaises(ValueError):
+            line(t, timestamp="Tstamp", value="Value")
+
+    def test_missing_color_column_raises(self):
+        t = self._table("Timestamp", "Value")
+        with self.assertRaises(ValueError):
+            line(t, timestamp="Timestamp", value="Value", color_column="Colr")
+
+    def test_valid_columns_ok(self):
+        t = self._table("Timestamp", "Value")
+        c = line(t, timestamp="Timestamp", value="Value")
+        self.assertEqual(len(c.series_list), 1)
+
+    def test_candlestick_missing_ohlc_column_raises(self):
+        t = self._table("Timestamp", "Open", "High", "Low", "Close")
+        with self.assertRaises(ValueError) as ctx:
+            candlestick(
+                t,
+                timestamp="Timestamp",
+                open="Open",
+                high="High",
+                low="Low",
+                close="Closee",
+            )
+        self.assertIn("Closee", str(ctx.exception))
+
+    def test_bare_series_spec_validated_in_chart(self):
+        """Bare SeriesSpec passed to chart() (internal-constructor path)."""
+        t = self._table("Timestamp", "Value")
+        spec = line_series(t, timestamp="Timestamp", value="Nope")
+        with self.assertRaises(ValueError):
+            chart(spec)
+
+    def test_mock_table_without_columns_skips_validation(self):
+        """Typeless mock tables (no real .columns) bypass validation."""
+        t = MagicMock(name="table")
+        type(t).columns = property(
+            lambda self: (_ for _ in ()).throw(TypeError("no columns"))
+        )
+        # Should not raise despite the nonexistent column.
+        line(t, timestamp="Timestamp", value="Whatever")
+
+    def test_missing_price_line_column_raises(self):
+        from deephaven.plot.tradingview_lightweight.markers import price_line
+
+        t = self._table("Timestamp", "Value")
+        with self.assertRaises(ValueError) as ctx:
+            line(
+                t,
+                timestamp="Timestamp",
+                value="Value",
+                price_lines=[price_line(column="Bogus")],
+            )
+        self.assertIn("Bogus", str(ctx.exception))
+
+    def test_valid_price_line_column_ok(self):
+        from deephaven.plot.tradingview_lightweight.markers import price_line
+
+        t = self._table("Timestamp", "Value")
+        line(
+            t,
+            timestamp="Timestamp",
+            value="Value",
+            price_lines=[price_line(column="Value")],
+        )
+
+    def test_static_price_line_not_validated(self):
+        from deephaven.plot.tradingview_lightweight.markers import price_line
+
+        t = self._table("Timestamp", "Value")
+        # A static price (no column) must not trip column validation.
+        line(
+            t,
+            timestamp="Timestamp",
+            value="Value",
+            price_lines=[price_line(price=100.0)],
+        )
+
+    def test_missing_marker_column_raises(self):
+        from deephaven.plot.tradingview_lightweight.markers import markers_from_table
+
+        series_tbl = self._table("Timestamp", "Value")
+        marker_tbl = self._table("Time", "Label")
+        spec = markers_from_table(marker_tbl, timestamp="Time", text_column="Nope")
+        with self.assertRaises(ValueError) as ctx:
+            line(
+                series_tbl,
+                timestamp="Timestamp",
+                value="Value",
+                marker_spec=spec,
+            )
+        self.assertIn("Nope", str(ctx.exception))
+
+    def test_valid_marker_columns_ok(self):
+        from deephaven.plot.tradingview_lightweight.markers import markers_from_table
+
+        series_tbl = self._table("Timestamp", "Value")
+        marker_tbl = self._table("Time", "Label")
+        spec = markers_from_table(marker_tbl, timestamp="Time", text_column="Label")
+        line(series_tbl, timestamp="Timestamp", value="Value", marker_spec=spec)
+
+
+class TestEnumMaps(unittest.TestCase):
+    """Verify all enum maps contain correct JS integer values."""
+
+    def test_crosshair_mode_map_complete(self):
+        from deephaven.plot.tradingview_lightweight.options import CROSSHAIR_MODE_MAP
+
+        self.assertEqual(CROSSHAIR_MODE_MAP["normal"], 0)
+        self.assertEqual(CROSSHAIR_MODE_MAP["magnet"], 1)
+        self.assertEqual(CROSSHAIR_MODE_MAP["hidden"], 2)
+        self.assertEqual(CROSSHAIR_MODE_MAP["magnet_ohlc"], 3)
+        self.assertEqual(len(CROSSHAIR_MODE_MAP), 4)
+
+    def test_last_price_animation_mode_map(self):
+        from deephaven.plot.tradingview_lightweight.options import (
+            LAST_PRICE_ANIMATION_MODE_MAP,
+        )
+
+        self.assertEqual(LAST_PRICE_ANIMATION_MODE_MAP["disabled"], 0)
+        self.assertEqual(LAST_PRICE_ANIMATION_MODE_MAP["continuous"], 1)
+        self.assertEqual(LAST_PRICE_ANIMATION_MODE_MAP["on_data_update"], 2)
+        self.assertEqual(len(LAST_PRICE_ANIMATION_MODE_MAP), 3)
+
+    def test_price_line_source_map(self):
+        from deephaven.plot.tradingview_lightweight.options import (
+            PRICE_LINE_SOURCE_MAP,
+        )
+
+        self.assertEqual(PRICE_LINE_SOURCE_MAP["last_bar"], 0)
+        self.assertEqual(PRICE_LINE_SOURCE_MAP["last_visible"], 1)
+        self.assertEqual(len(PRICE_LINE_SOURCE_MAP), 2)
+
+    def test_tracking_mode_exit_mode_map(self):
+        from deephaven.plot.tradingview_lightweight.options import (
+            TRACKING_MODE_EXIT_MODE_MAP,
+        )
+
+        self.assertEqual(TRACKING_MODE_EXIT_MODE_MAP["on_touch_end"], 0)
+        self.assertEqual(TRACKING_MODE_EXIT_MODE_MAP["on_next_tap"], 1)
+        self.assertEqual(len(TRACKING_MODE_EXIT_MODE_MAP), 2)
+
+    def test_all_new_enums_exported_from_package(self):
+        """All new enum Literals and maps should be importable from the package root."""
+        from deephaven.plot.tradingview_lightweight.options import (
+            ColorType,
+            LastPriceAnimationMode,
+            MarkerSign,
+            MismatchDirection,
+            PriceLineSource,
+            TickMarkType,
+            TrackingModeExitMode,
+        )
+
+        # Spot-check that they are typing constructs, not None or other types
+        self.assertIsNotNone(ColorType)
+        self.assertIsNotNone(LastPriceAnimationMode)
+        self.assertIsNotNone(MarkerSign)
+        self.assertIsNotNone(MismatchDirection)
+        self.assertIsNotNone(PriceLineSource)
+        self.assertIsNotNone(TickMarkType)
+        self.assertIsNotNone(TrackingModeExitMode)
+
+
+class TestLineWidth(unittest.TestCase):
+    """Tests that LineWidth annotation is exported and its values are accepted."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_linewidth_exported(self):
+        """LineWidth must be importable from the top-level package."""
+        from deephaven.plot.tradingview_lightweight.options import LineWidth
+        import typing
+
+        args = typing.get_args(LineWidth)
+        self.assertEqual(set(args), {1, 2, 3, 4})
+
+    def test_linewidth_values_accepted_in_chart(self):
+        """All four valid LineWidth values should serialize without error."""
+        s = line_series(self.table)
+        for w in (1, 2, 3, 4):
+            c = chart(s, crosshair_vert_line_width=w)
+            self.assertEqual(
+                c.chart_options["crosshair"]["vertLine"]["width"],
+                w,
+                f"Width {w} should pass through verbatim",
+            )
+
+    def test_linewidth_price_line_annotation(self):
+        """PriceLine.line_width accepts LineWidth-typed ints."""
+        pl = PriceLine(price=100.0, line_width=2)
+        self.assertEqual(pl.to_dict()["lineWidth"], 2)
+
+
+class TestPriceFormat(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_price_format_builtin_types_accepted(self):
+        """Valid built-in type values should not raise."""
+        from deephaven.plot.tradingview_lightweight.options import PriceFormat
+
+        for t in ("price", "volume", "percent"):
+            pf: PriceFormat = {"type": t, "precision": 2, "min_move": 0.01}
+            self.assertEqual(pf["type"], t)
+
+    def test_price_format_custom_type_not_in_literal(self):
+        """The 'custom' literal must not appear in PriceFormat.type."""
+        import typing
+        from deephaven.plot.tradingview_lightweight.options import PriceFormat
+
+        hints = typing.get_type_hints(PriceFormat)
+        type_args = typing.get_args(hints.get("type", None))
+        self.assertNotIn("custom", type_args)
+
+    def test_price_format_custom_raises_valueerror(self):
+        """Passing type='custom' to a series function should raise ValueError."""
+        with self.assertRaises(ValueError) as ctx:
+            line_series(self.table, price_format={"type": "custom"})
+        self.assertIn("custom", str(ctx.exception))
+
+    def test_price_format_custom_raises_in_all_series(self):
+        """All series creation functions should reject type='custom'."""
+        custom_pf = {"type": "custom"}
+        for fn in (
+            candlestick_series,
+            bar_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ):
+            with self.assertRaises(
+                ValueError, msg=f"{fn.__name__} should reject custom"
+            ):
+                if fn in (candlestick_series, bar_series):
+                    fn(self.table, price_format=custom_pf)
+                else:
+                    fn(self.table, price_format=custom_pf)
+
+
+class TestAlignTypes(unittest.TestCase):
+    def test_horz_align_literal_values(self):
+        """HorzAlign must be exactly {'left', 'center', 'right'}."""
+        import typing
+        from deephaven.plot.tradingview_lightweight.options import HorzAlign
+
+        args = typing.get_args(HorzAlign)
+        self.assertEqual(set(args), {"left", "center", "right"})
+
+    def test_vert_align_literal_values(self):
+        """VertAlign must be exactly {'top', 'center', 'bottom'}."""
+        import typing
+        from deephaven.plot.tradingview_lightweight.options import VertAlign
+
+        args = typing.get_args(VertAlign)
+        self.assertEqual(set(args), {"top", "center", "bottom"})
+
+    def test_horz_align_exported(self):
+        """HorzAlign must be importable from the top-level package."""
+        from deephaven.plot import tradingview_lightweight as tvl
+
+        self.assertTrue(hasattr(tvl, "HorzAlign"))
+
+    def test_vert_align_exported(self):
+        """VertAlign must be importable from the top-level package."""
+        from deephaven.plot import tradingview_lightweight as tvl
+
+        self.assertTrue(hasattr(tvl, "VertAlign"))
+
+    def test_watermark_horz_align_passthrough(self):
+        """watermark_horz_align should pass through to chartOptions."""
+        table = MagicMock(name="table")
+        s = line_series(table)
+        c = chart(s, watermark_text="TEST", watermark_horz_align="center")
+        self.assertEqual(c.chart_options["watermark"]["horzAlign"], "center")
+
+    def test_watermark_vert_align_passthrough(self):
+        """watermark_vert_align should pass through to chartOptions."""
+        table = MagicMock(name="table")
+        s = line_series(table)
+        c = chart(s, watermark_text="TEST", watermark_vert_align="top")
+        self.assertEqual(c.chart_options["watermark"]["vertAlign"], "top")
+
+
+class TestWatermarkOptions(unittest.TestCase):
+    """Tests for text, multi-line, and image watermark options."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    # --- Single-line new fields ---
+
+    def test_watermark_single_line_new_fields(self):
+        """fontStyle, lineHeight are forwarded in single-line mode."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_text="AAPL",
+            watermark_font_style="italic",
+            watermark_line_height=80.0,
+        )
+        wm = c.chart_options["watermark"]
+        self.assertEqual(wm["text"], "AAPL")
+        self.assertNotIn("fontFamily", wm)
+        self.assertEqual(wm["fontStyle"], "italic")
+        self.assertEqual(wm["lineHeight"], 80.0)
+        self.assertNotIn("lines", wm)  # still legacy shape
+
+    def test_watermark_single_line_omitted_new_fields(self):
+        """Omitted new fields do not appear in the serialised dict."""
+        s = line_series(self.table)
+        c = chart(s, watermark_text="AAPL")
+        wm = c.chart_options["watermark"]
+        self.assertNotIn("fontFamily", wm)
+        self.assertNotIn("fontStyle", wm)
+        self.assertNotIn("lineHeight", wm)
+
+    # --- Multi-line watermark ---
+
+    def test_watermark_multi_line_basic(self):
+        """watermark_lines produces a lines[] array in the watermark dict."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_lines=[
+                WatermarkLine(text="AAPL", font_size=72, font_style="italic"),
+                WatermarkLine(
+                    text="Apple Inc",
+                    font_size=32,
+                    color="rgba(100,100,100,0.3)",
+                ),
+            ],
+            watermark_horz_align="left",
+            watermark_vert_align="bottom",
+        )
+        wm = c.chart_options["watermark"]
+        self.assertTrue(wm["visible"])
+        self.assertEqual(wm["horzAlign"], "left")
+        self.assertEqual(wm["vertAlign"], "bottom")
+        self.assertEqual(len(wm["lines"]), 2)
+
+        line0 = wm["lines"][0]
+        self.assertEqual(line0["text"], "AAPL")
+        self.assertEqual(line0["fontSize"], 72)
+        self.assertEqual(line0["fontStyle"], "italic")
+        self.assertNotIn("color", line0)  # not specified -> omitted
+        self.assertNotIn("lineHeight", line0)
+
+        line1 = wm["lines"][1]
+        self.assertEqual(line1["text"], "Apple Inc")
+        self.assertEqual(line1["fontSize"], 32)
+        self.assertEqual(line1["color"], "rgba(100,100,100,0.3)")
+
+    def test_watermark_multi_line_no_text_key(self):
+        """Multi-line path must NOT produce a top-level 'text' key."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        c = chart(s, watermark_lines=[WatermarkLine(text="AAPL")])
+        wm = c.chart_options["watermark"]
+        self.assertNotIn("text", wm)
+        self.assertIn("lines", wm)
+
+    def test_watermark_multi_line_visible_false(self):
+        """watermark_visible=False is respected with watermark_lines."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_lines=[WatermarkLine(text="AAPL")],
+            watermark_visible=False,
+        )
+        wm = c.chart_options["watermark"]
+        self.assertFalse(wm["visible"])
+
+    def test_watermark_multi_line_auto_visible(self):
+        """watermark_lines without watermark_visible auto-sets visible=True."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        c = chart(s, watermark_lines=[WatermarkLine(text="AAPL")])
+        self.assertTrue(c.chart_options["watermark"]["visible"])
+
+    def test_watermark_line_height_in_line(self):
+        """lineHeight on a WatermarkLine is serialised correctly."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_lines=[WatermarkLine(text="X", line_height=90.0)],
+        )
+        line0 = c.chart_options["watermark"]["lines"][0]
+        self.assertEqual(line0["lineHeight"], 90.0)
+
+    def test_watermark_mutual_exclusion_raises(self):
+        """Providing both watermark_text and watermark_lines must raise ValueError."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        with self.assertRaises(ValueError) as ctx:
+            chart(
+                s,
+                watermark_text="AAPL",
+                watermark_lines=[WatermarkLine(text="AAPL")],
+            )
+        self.assertIn("watermark_text", str(ctx.exception))
+        self.assertIn("watermark_lines", str(ctx.exception))
+
+    # --- Image watermark ---
+
+    def test_watermark_image_basic(self):
+        """Image watermark params produce an 'imageWatermark' key."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_image_url="https://example.com/logo.png",
+            watermark_image_max_width=200,
+            watermark_image_max_height=100,
+            watermark_image_padding=10,
+            watermark_image_alpha=0.5,
+        )
+        img = c.chart_options["imageWatermark"]
+        self.assertEqual(img["url"], "https://example.com/logo.png")
+        self.assertEqual(img["maxWidth"], 200)
+        self.assertEqual(img["maxHeight"], 100)
+        self.assertEqual(img["padding"], 10)
+        self.assertEqual(img["alpha"], 0.5)
+        self.assertTrue(img["visible"])  # auto-set when url is provided
+
+    def test_watermark_image_no_url_no_key(self):
+        """No imageWatermark key when url is not given."""
+        s = line_series(self.table)
+        c = chart(s, watermark_image_max_width=200)
+        self.assertNotIn("imageWatermark", c.chart_options)
+
+    def test_watermark_image_visible_false(self):
+        """Image watermark visible=False is respected."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_image_url="https://example.com/logo.png",
+            watermark_image_visible=False,
+        )
+        self.assertFalse(c.chart_options["imageWatermark"]["visible"])
+
+    def test_watermark_image_url_only(self):
+        """Minimal image watermark with only url."""
+        s = line_series(self.table)
+        c = chart(s, watermark_image_url="https://example.com/logo.png")
+        img = c.chart_options["imageWatermark"]
+        self.assertEqual(img["url"], "https://example.com/logo.png")
+        self.assertNotIn("maxWidth", img)
+        self.assertNotIn("maxHeight", img)
+        self.assertNotIn("padding", img)
+        self.assertNotIn("alpha", img)
+
+    def test_watermark_image_and_text_coexist(self):
+        """Text and image watermarks can be set simultaneously."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_text="AAPL",
+            watermark_image_url="https://example.com/logo.png",
+        )
+        self.assertIn("watermark", c.chart_options)
+        self.assertIn("imageWatermark", c.chart_options)
+
+    def test_watermark_image_and_multiline_coexist(self):
+        """Multi-line text and image watermarks can be set simultaneously."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_lines=[WatermarkLine(text="AAPL")],
+            watermark_image_url="https://example.com/logo.png",
+        )
+        self.assertIn("watermark", c.chart_options)
+        self.assertIn("imageWatermark", c.chart_options)
+
+    # --- Backwards-compatibility regression guard ---
+
+    def test_watermark_options_backward_compat(self):
+        """Existing tests still pass: single-line params produce unchanged shape."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            watermark_text="AAPL",
+            watermark_color="rgba(0,0,0,0.2)",
+            watermark_visible=True,
+            watermark_font_size=48,
+            watermark_horz_align="center",
+            watermark_vert_align="center",
+        )
+        wm = c.chart_options["watermark"]
+        self.assertEqual(wm["text"], "AAPL")
+        self.assertEqual(wm["color"], "rgba(0,0,0,0.2)")
+        self.assertTrue(wm["visible"])
+        self.assertEqual(wm["fontSize"], 48)
+        self.assertEqual(wm["horzAlign"], "center")
+        self.assertEqual(wm["vertAlign"], "center")
+        self.assertNotIn("lines", wm)  # still legacy flat shape
+        self.assertNotIn("imageWatermark", c.chart_options)
+
+    # --- WatermarkLine.to_dict() ---
+
+    def test_watermark_line_to_dict(self):
+        """WatermarkLine.to_dict() returns camelCase keys and omits None values."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        wl = WatermarkLine(
+            text="AAPL", font_size=72, font_style="italic", line_height=90.0
+        )
+        d = wl.to_dict()
+        self.assertEqual(d["text"], "AAPL")
+        self.assertEqual(d["fontSize"], 72)
+        self.assertEqual(d["fontStyle"], "italic")
+        self.assertEqual(d["lineHeight"], 90.0)
+        self.assertNotIn("color", d)
+        self.assertNotIn("fontFamily", d)
+
+    def test_watermark_line_to_dict_minimal(self):
+        """WatermarkLine with only text produces minimal dict."""
+        from deephaven.plot.tradingview_lightweight.options import WatermarkLine
+
+        wl = WatermarkLine(text="X")
+        d = wl.to_dict()
+        self.assertEqual(d, {"text": "X"})
+
+    # --- WatermarkLine exported from package ---
+
+    def test_watermark_line_exported(self):
+        """WatermarkLine must be importable from the top-level package."""
+        from deephaven.plot import tradingview_lightweight as tvl
+
+        self.assertTrue(hasattr(tvl, "WatermarkLine"))
+
+
+class TestScrollScaleOptions(unittest.TestCase):
+    """Tests for handleScroll, handleScale, and kineticScroll options."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    # -----------------------------------------------------------------------
+    # HandleScroll — not set by default
+    # -----------------------------------------------------------------------
+
+    def test_handle_scroll_not_set_by_default(self):
+        """No scroll/scale keys should appear when no params are given."""
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("handleScroll", c.chart_options)
+        self.assertNotIn("handleScale", c.chart_options)
+        self.assertNotIn("kineticScroll", c.chart_options)
+
+    # -----------------------------------------------------------------------
+    # HandleScroll — boolean shorthand
+    # -----------------------------------------------------------------------
+
+    def test_handle_scroll_false_shorthand(self):
+        """handle_scroll=False should emit handleScroll: false (boolean)."""
+        s = line_series(self.table)
+        c = chart(s, handle_scroll=False)
+        self.assertIn("handleScroll", c.chart_options)
+        self.assertIs(c.chart_options["handleScroll"], False)
+
+    def test_handle_scroll_true_shorthand(self):
+        """handle_scroll=True should emit handleScroll: true (boolean)."""
+        s = line_series(self.table)
+        c = chart(s, handle_scroll=True)
+        self.assertIs(c.chart_options["handleScroll"], True)
+
+    def test_handle_scroll_shorthand_overrides_granular(self):
+        """When handle_scroll bool is set, granular sub-options are ignored."""
+        s = line_series(self.table)
+        c = chart(s, handle_scroll=False, handle_scroll_mouse_wheel=True)
+        # Must be boolean False, not an object
+        self.assertIs(c.chart_options["handleScroll"], False)
+
+    # -----------------------------------------------------------------------
+    # HandleScroll — granular sub-options
+    # -----------------------------------------------------------------------
+
+    def test_handle_scroll_mouse_wheel_false(self):
+        """handle_scroll_mouse_wheel=False emits object form."""
+        s = line_series(self.table)
+        c = chart(s, handle_scroll_mouse_wheel=False)
+        hs = c.chart_options["handleScroll"]
+        self.assertIsInstance(hs, dict)
+        self.assertFalse(hs["mouseWheel"])
+
+    def test_handle_scroll_pressed_mouse_move_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scroll_pressed_mouse_move=False)
+        hs = c.chart_options["handleScroll"]
+        self.assertIsInstance(hs, dict)
+        self.assertFalse(hs["pressedMouseMove"])
+
+    def test_handle_scroll_horz_touch_drag_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scroll_horz_touch_drag=False)
+        hs = c.chart_options["handleScroll"]
+        self.assertIsInstance(hs, dict)
+        self.assertFalse(hs["horzTouchDrag"])
+
+    def test_handle_scroll_vert_touch_drag_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scroll_vert_touch_drag=False)
+        hs = c.chart_options["handleScroll"]
+        self.assertIsInstance(hs, dict)
+        self.assertFalse(hs["vertTouchDrag"])
+
+    def test_handle_scroll_all_granular_options(self):
+        """All four granular scroll options should appear in the object."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            handle_scroll_mouse_wheel=True,
+            handle_scroll_pressed_mouse_move=False,
+            handle_scroll_horz_touch_drag=True,
+            handle_scroll_vert_touch_drag=False,
+        )
+        hs = c.chart_options["handleScroll"]
+        self.assertIsInstance(hs, dict)
+        self.assertTrue(hs["mouseWheel"])
+        self.assertFalse(hs["pressedMouseMove"])
+        self.assertTrue(hs["horzTouchDrag"])
+        self.assertFalse(hs["vertTouchDrag"])
+
+    def test_handle_scroll_partial_granular_only_set_keys_emitted(self):
+        """Only explicitly set granular keys should appear in the output dict."""
+        s = line_series(self.table)
+        c = chart(s, handle_scroll_mouse_wheel=False)
+        hs = c.chart_options["handleScroll"]
+        # Only "mouseWheel" should be present — not the others
+        self.assertIn("mouseWheel", hs)
+        self.assertNotIn("pressedMouseMove", hs)
+        self.assertNotIn("horzTouchDrag", hs)
+        self.assertNotIn("vertTouchDrag", hs)
+
+    # -----------------------------------------------------------------------
+    # HandleScale — boolean shorthand
+    # -----------------------------------------------------------------------
+
+    def test_handle_scale_false_shorthand(self):
+        """handle_scale=False should emit handleScale: false (boolean)."""
+        s = line_series(self.table)
+        c = chart(s, handle_scale=False)
+        self.assertIs(c.chart_options["handleScale"], False)
+
+    def test_handle_scale_true_shorthand(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scale=True)
+        self.assertIs(c.chart_options["handleScale"], True)
+
+    def test_handle_scale_shorthand_overrides_granular(self):
+        """When handle_scale bool is set, granular sub-options are ignored."""
+        s = line_series(self.table)
+        c = chart(s, handle_scale=False, handle_scale_pinch=True)
+        self.assertIs(c.chart_options["handleScale"], False)
+
+    # -----------------------------------------------------------------------
+    # HandleScale — granular sub-options
+    # -----------------------------------------------------------------------
+
+    def test_handle_scale_mouse_wheel_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scale_mouse_wheel=False)
+        hsc = c.chart_options["handleScale"]
+        self.assertIsInstance(hsc, dict)
+        self.assertFalse(hsc["mouseWheel"])
+
+    def test_handle_scale_pinch_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scale_pinch=False)
+        hsc = c.chart_options["handleScale"]
+        self.assertIsInstance(hsc, dict)
+        self.assertFalse(hsc["pinch"])
+
+    def test_handle_scale_axis_pressed_mouse_move_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scale_axis_pressed_mouse_move=False)
+        hsc = c.chart_options["handleScale"]
+        self.assertIsInstance(hsc, dict)
+        self.assertFalse(hsc["axisPressedMouseMove"])
+
+    def test_handle_scale_axis_double_click_reset_false(self):
+        s = line_series(self.table)
+        c = chart(s, handle_scale_axis_double_click_reset=False)
+        hsc = c.chart_options["handleScale"]
+        self.assertIsInstance(hsc, dict)
+        self.assertFalse(hsc["axisDoubleClickReset"])
+
+    def test_handle_scale_all_granular_options(self):
+        """All four granular scale options should appear in the object."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            handle_scale_mouse_wheel=True,
+            handle_scale_pinch=False,
+            handle_scale_axis_pressed_mouse_move=True,
+            handle_scale_axis_double_click_reset=False,
+        )
+        hsc = c.chart_options["handleScale"]
+        self.assertIsInstance(hsc, dict)
+        self.assertTrue(hsc["mouseWheel"])
+        self.assertFalse(hsc["pinch"])
+        self.assertTrue(hsc["axisPressedMouseMove"])
+        self.assertFalse(hsc["axisDoubleClickReset"])
+
+    def test_handle_scale_partial_granular_only_set_keys_emitted(self):
+        """Only explicitly set granular keys should appear in the output dict."""
+        s = line_series(self.table)
+        c = chart(s, handle_scale_pinch=False)
+        hsc = c.chart_options["handleScale"]
+        self.assertIn("pinch", hsc)
+        self.assertNotIn("mouseWheel", hsc)
+        self.assertNotIn("axisPressedMouseMove", hsc)
+        self.assertNotIn("axisDoubleClickReset", hsc)
+
+    # -----------------------------------------------------------------------
+    # KineticScroll
+    # -----------------------------------------------------------------------
+
+    def test_kinetic_scroll_touch_false(self):
+        """kinetic_scroll_touch=False should emit kineticScroll.touch: false."""
+        s = line_series(self.table)
+        c = chart(s, kinetic_scroll_touch=False)
+        ks = c.chart_options["kineticScroll"]
+        self.assertIsInstance(ks, dict)
+        self.assertFalse(ks["touch"])
+
+    def test_kinetic_scroll_mouse_true(self):
+        """kinetic_scroll_mouse=True should emit kineticScroll.mouse: true."""
+        s = line_series(self.table)
+        c = chart(s, kinetic_scroll_mouse=True)
+        ks = c.chart_options["kineticScroll"]
+        self.assertIsInstance(ks, dict)
+        self.assertTrue(ks["mouse"])
+
+    def test_kinetic_scroll_both_options(self):
+        s = line_series(self.table)
+        c = chart(s, kinetic_scroll_touch=True, kinetic_scroll_mouse=True)
+        ks = c.chart_options["kineticScroll"]
+        self.assertTrue(ks["touch"])
+        self.assertTrue(ks["mouse"])
+
+    def test_kinetic_scroll_not_set_by_default(self):
+        s = line_series(self.table)
+        c = chart(s)
+        self.assertNotIn("kineticScroll", c.chart_options)
+
+    def test_kinetic_scroll_partial_only_set_keys_emitted(self):
+        """Setting only mouse should not emit touch key."""
+        s = line_series(self.table)
+        c = chart(s, kinetic_scroll_mouse=False)
+        ks = c.chart_options["kineticScroll"]
+        self.assertIn("mouse", ks)
+        self.assertNotIn("touch", ks)
+
+    # -----------------------------------------------------------------------
+    # Combined: all three groups together
+    # -----------------------------------------------------------------------
+
+    def test_all_three_groups_combined(self):
+        """All three option groups can coexist in chart_options."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            handle_scroll=False,
+            handle_scale_pinch=False,
+            kinetic_scroll_mouse=True,
+        )
+        self.assertIs(c.chart_options["handleScroll"], False)
+        self.assertFalse(c.chart_options["handleScale"]["pinch"])
+        self.assertTrue(c.chart_options["kineticScroll"]["mouse"])
+
+    def test_scroll_scale_options_do_not_interfere_with_other_options(self):
+        """Adding scroll/scale options should not disturb layout or grid."""
+        s = line_series(self.table)
+        c = chart(
+            s,
+            background_color="#000",
+            vert_lines_visible=False,
+            handle_scroll=False,
+            handle_scale=False,
+            kinetic_scroll_touch=False,
+        )
+        self.assertIn("layout", c.chart_options)
+        self.assertIn("grid", c.chart_options)
+        self.assertIs(c.chart_options["handleScroll"], False)
+        self.assertIs(c.chart_options["handleScale"], False)
+        self.assertFalse(c.chart_options["kineticScroll"]["touch"])
+
+
+class TestTrackingTooltip(unittest.TestCase):
+    """Tests for the tracking-tooltip (``tooltip_*``) chart options."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_no_tooltip_by_default(self):
+        c = chart(line_series(self.table))
+        self.assertNotIn("tooltip", c.chart_options)
+
+    def test_visible_emits_block(self):
+        c = chart(line_series(self.table), tooltip_visible=True)
+        self.assertEqual(c.chart_options["tooltip"], {"visible": True})
+
+    def test_visible_false_omits_block(self):
+        c = chart(line_series(self.table), tooltip_visible=False)
+        self.assertNotIn("tooltip", c.chart_options)
+
+    def test_all_options(self):
+        c = chart(
+            line_series(self.table),
+            tooltip_visible=True,
+            tooltip_show_title=False,
+            tooltip_show_value=True,
+            tooltip_show_date=False,
+            tooltip_value_precision=3,
+        )
+        self.assertEqual(
+            c.chart_options["tooltip"],
+            {
+                "visible": True,
+                "showTitle": False,
+                "showValue": True,
+                "showDate": False,
+                "valuePrecision": 3,
+            },
+        )
+
+    def test_precision_zero_is_kept(self):
+        # 0 is falsy but a valid precision — must not be dropped by _filter_none.
+        c = chart(
+            line_series(self.table),
+            tooltip_visible=True,
+            tooltip_value_precision=0,
+        )
+        self.assertEqual(c.chart_options["tooltip"]["valuePrecision"], 0)
+
+    def test_details_without_visible_raise(self):
+        with self.assertRaises(ValueError) as ctx:
+            chart(line_series(self.table), tooltip_show_title=True)
+        self.assertIn("tooltip_visible=True", str(ctx.exception))
+
+    def test_details_without_visible_lists_offenders(self):
+        with self.assertRaises(ValueError) as ctx:
+            chart(
+                line_series(self.table),
+                tooltip_show_date=True,
+                tooltip_value_precision=2,
+            )
+        msg = str(ctx.exception)
+        self.assertIn("tooltip_show_date", msg)
+        self.assertIn("tooltip_value_precision", msg)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_event_dispatch.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_event_dispatch.py
new file mode 100644
index 000000000..61ebfc62a
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_event_dispatch.py
@@ -0,0 +1,394 @@
+"""Tests for press-event dispatch (Phase 3): registry, EVENT routing,
+arity, exec-context / liveness wrapping, exception swallowing, and the
+ns -> datetime time conversion.
+"""
+
+from __future__ import annotations
+
+import contextlib
+import json
+import os
+import sys
+import unittest
+from datetime import datetime, timezone
+from unittest.mock import MagicMock
+
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight.chart import TvlChart  # noqa: E402
+from deephaven.plot.tradingview_lightweight.series import line_series  # noqa: E402
+from deephaven.plot.tradingview_lightweight import events as events_module  # noqa: E402
+from deephaven.plot.tradingview_lightweight.events import (  # noqa: E402
+    ns_to_datetime,
+    ns_to_instant,
+    build_press_event,
+    time_converter_for,
+)
+from deephaven.plot.tradingview_lightweight.communication import (  # noqa: E402
+    listener as listener_module,
+)
+
+TvlChartListener = listener_module.TvlChartListener
+
+
+class _FakeDType:
+    def __init__(self, j_name):
+        self.j_name = j_name
+
+
+class _FakeColumn:
+    def __init__(self, name, j_name):
+        self.name = name
+        self.data_type = _FakeDType(j_name)
+
+
+def _table_with_time_type(j_name, time_col="Timestamp"):
+    """A mock table whose ``columns`` exposes one typed time column."""
+    table = MagicMock(name="table")
+    table.columns = [_FakeColumn(time_col, j_name), _FakeColumn("Value", "double")]
+    return table
+
+
+def _event_message(handler="press", **payload):
+    base = {
+        "type": "press",
+        "shiftKey": False,
+        "ctrlKey": False,
+        "metaKey": False,
+        "altKey": False,
+    }
+    base.update(payload)
+    return json.dumps({"type": "EVENT", "handler": handler, "payload": base}).encode()
+
+
+class TestNsToDatetime(unittest.TestCase):
+    def test_whole_second(self):
+        # 2021-01-01T00:00:00Z = 1609459200 s
+        dt = ns_to_datetime(1_609_459_200 * 1_000_000_000)
+        self.assertEqual(dt, datetime(2021, 1, 1, tzinfo=timezone.utc))
+
+    def test_sub_second_microsecond_precision(self):
+        dt = ns_to_datetime(1_609_459_200 * 1_000_000_000 + 123_456_789)
+        self.assertEqual(dt.microsecond, 123_456)  # ns truncated to us
+        self.assertEqual(dt.tzinfo, timezone.utc)
+
+
+class TestBuildPressEvent(unittest.TestCase):
+    def test_full_payload(self):
+        evt = build_press_event(
+            "press",
+            {
+                "hoveredSeries": "aaa",
+                "hoveredSeriesId": "series_0",
+                "seriesData": {"aaa": {"value": 10.5}},
+                "point": {"x": 10, "y": 20},
+                "logical": 5,
+                "paneIndex": 0,
+                "timeNs": 1_609_459_200 * 1_000_000_000,
+                "shiftKey": True,
+                "ctrlKey": False,
+                "metaKey": False,
+                "altKey": False,
+            },
+        )
+        self.assertEqual(evt["type"], "press")
+        self.assertEqual(evt["hoveredSeries"], "aaa")
+        self.assertEqual(evt["hoveredSeriesId"], "series_0")
+        self.assertEqual(evt["seriesData"], {"aaa": {"value": 10.5}})
+        self.assertEqual(evt["point"], {"x": 10, "y": 20})
+        self.assertEqual(evt["logical"], 5)
+        self.assertEqual(evt["paneIndex"], 0)
+        self.assertTrue(evt["shiftKey"])
+        self.assertEqual(evt["timestamp"], datetime(2021, 1, 1, tzinfo=timezone.utc))
+
+    def test_series_data_passthrough_keeps_ohlc_shape(self):
+        evt = build_press_event(
+            "press",
+            {
+                "hoveredSeries": "Price",
+                "hoveredSeriesId": "series_0",
+                "seriesData": {
+                    "Price": {
+                        "open": 100.0,
+                        "high": 105.0,
+                        "low": 99.0,
+                        "close": 103.0,
+                    },
+                },
+            },
+        )
+        self.assertEqual(evt["hoveredSeries"], "Price")
+        self.assertEqual(evt["hoveredSeriesId"], "series_0")
+        self.assertEqual(
+            evt["seriesData"]["Price"],
+            {"open": 100.0, "high": 105.0, "low": 99.0, "close": 103.0},
+        )
+
+    def test_empty_area_omits_time_and_series(self):
+        evt = build_press_event("press", {})
+        self.assertNotIn("timestamp", evt)
+        self.assertNotIn("hoveredSeries", evt)
+        self.assertNotIn("hoveredSeriesId", evt)
+        self.assertNotIn("seriesData", evt)
+        # modifiers always present
+        self.assertEqual(evt["shiftKey"], False)
+        self.assertEqual(evt["altKey"], False)
+
+    def test_double_press_type(self):
+        evt = build_press_event("doublePress", {})
+        self.assertEqual(evt["type"], "doublePress")
+
+    def test_uses_injected_time_converter(self):
+        evt = build_press_event(
+            "press",
+            {"timeNs": 42},
+            time_converter=lambda ns: ("converted", ns),
+        )
+        self.assertEqual(evt["timestamp"], ("converted", 42))
+
+    def test_bad_converter_falls_back_to_datetime(self):
+        def boom(_ns):
+            raise RuntimeError("no JVM")
+
+        evt = build_press_event(
+            "press", {"timeNs": 1_609_459_200 * 1_000_000_000}, time_converter=boom
+        )
+        # A failing converter must not lose the press; degrade to datetime.
+        self.assertEqual(evt["timestamp"], datetime(2021, 1, 1, tzinfo=timezone.utc))
+
+
+class TestTimeConverterFor(unittest.TestCase):
+    def test_instant_type(self):
+        self.assertIs(time_converter_for("java.time.Instant"), ns_to_instant)
+
+    def test_unknown_and_none_fall_back_to_datetime(self):
+        self.assertIs(time_converter_for(None), ns_to_datetime)
+        self.assertIs(time_converter_for("java.time.LocalDate"), ns_to_datetime)
+        self.assertIs(time_converter_for("double"), ns_to_datetime)
+
+    def test_zoned_returns_distinct_converter(self):
+        conv = time_converter_for("java.time.ZonedDateTime", "America/New_York")
+        # A dedicated zoned converter, not the instant/datetime ones.
+        self.assertIsNot(conv, ns_to_datetime)
+        self.assertIsNot(conv, ns_to_instant)
+        self.assertTrue(callable(conv))
+
+
+class TestSeriesIndexParsing(unittest.TestCase):
+    def test_plain_id(self):
+        self.assertEqual(listener_module._series_index("series_0"), 0)
+        self.assertEqual(listener_module._series_index("series_12"), 12)
+
+    def test_partitioned_id_keeps_leading_index(self):
+        self.assertEqual(listener_module._series_index("series_0_BBB"), 0)
+        self.assertEqual(listener_module._series_index("series_3_AAA_X"), 3)
+
+    def test_non_series_ids(self):
+        for bad in (None, "", "foo", "series_", "series_x", 5):
+            self.assertIsNone(listener_module._series_index(bad))
+
+
+class TestCommonTimeType(unittest.TestCase):
+    def test_all_same(self):
+        self.assertEqual(
+            listener_module._common_time_type(["java.time.Instant"] * 3),
+            "java.time.Instant",
+        )
+
+    def test_mixed_or_unresolved_is_none(self):
+        self.assertIsNone(
+            listener_module._common_time_type(
+                ["java.time.Instant", "java.time.ZonedDateTime"]
+            )
+        )
+        self.assertIsNone(
+            listener_module._common_time_type(["java.time.Instant", None])
+        )
+        self.assertIsNone(listener_module._common_time_type([]))
+
+
+class TestRegistry(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_registry_only_wired_handlers(self):
+        chart = TvlChart(
+            series_list=[line_series(self.table)],
+            chart_options={},
+            on_press=lambda e: None,
+        )
+        listener = TvlChartListener(chart, MagicMock())
+        self.assertIn("press", listener._handlers)
+        self.assertNotIn("doublePress", listener._handlers)
+
+    def test_no_handlers_empty_registry(self):
+        chart = TvlChart(series_list=[line_series(self.table)], chart_options={})
+        listener = TvlChartListener(chart, MagicMock())
+        self.assertEqual(listener._handlers, {})
+
+
+class TestListenerTimeTypeResolution(unittest.TestCase):
+    def _listener(self, table, **handlers):
+        chart = TvlChart(series_list=[line_series(table)], chart_options={}, **handlers)
+        return TvlChartListener(chart, MagicMock())
+
+    def test_resolves_instant_column(self):
+        listener = self._listener(
+            _table_with_time_type("java.time.Instant"), on_press=lambda e: None
+        )
+        self.assertEqual(listener._series_time_types, ["java.time.Instant"])
+        self.assertEqual(listener._default_time_type, "java.time.Instant")
+
+    def test_hit_series_drives_type(self):
+        listener = self._listener(
+            _table_with_time_type("java.time.ZonedDateTime"), on_press=lambda e: None
+        )
+        # Press names series_0 → that series' zoned column wins.
+        self.assertEqual(
+            listener._time_type_for_payload({"seriesId": "series_0"}),
+            "java.time.ZonedDateTime",
+        )
+        # Press between lines (no seriesId) → chart default (homogeneous here).
+        self.assertEqual(listener._time_type_for_payload({}), "java.time.ZonedDateTime")
+
+    def test_hovered_series_id_drives_type_when_friendly_key_is_title(self):
+        listener = self._listener(
+            _table_with_time_type("java.time.ZonedDateTime"), on_press=lambda e: None
+        )
+        self.assertEqual(
+            listener._time_type_for_payload(
+                {"hoveredSeries": "Readable Title", "hoveredSeriesId": "series_0"}
+            ),
+            "java.time.ZonedDateTime",
+        )
+
+    def test_no_handlers_skips_resolution(self):
+        listener = self._listener(_table_with_time_type("java.time.Instant"))
+        self.assertEqual(listener._series_time_types, [])
+        self.assertIsNone(listener._default_time_type)
+
+    def test_typeless_table_resolves_none(self):
+        # Mock table without a real columns schema → datetime fallback.
+        listener = self._listener(MagicMock(name="table"), on_press=lambda e: None)
+        self.assertEqual(listener._series_time_types, [None])
+        self.assertIsNone(listener._default_time_type)
+
+
+class TestDispatch(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def _listener(self, **handlers):
+        chart = TvlChart(
+            series_list=[line_series(self.table)], chart_options={}, **handlers
+        )
+        return TvlChartListener(chart, MagicMock())
+
+    def test_routes_to_correct_callable(self):
+        press_calls, dbl_calls = [], []
+        listener = self._listener(
+            on_press=lambda e: press_calls.append(e),
+            on_double_press=lambda e: dbl_calls.append(e),
+        )
+        listener.process_message(_event_message("press", hoveredSeries="aaa"), [])
+        self.assertEqual(len(press_calls), 1)
+        self.assertEqual(len(dbl_calls), 0)
+        self.assertEqual(press_calls[0]["hoveredSeries"], "aaa")
+
+        listener.process_message(_event_message("doublePress"), [])
+        self.assertEqual(len(dbl_calls), 1)
+
+    def test_zero_arg_handler(self):
+        seen = []
+        listener = self._listener(on_press=lambda: seen.append("called"))
+        listener.process_message(_event_message("press"), [])
+        self.assertEqual(seen, ["called"])
+
+    def test_one_arg_handler_receives_event(self):
+        seen = []
+        listener = self._listener(on_press=lambda e: seen.append(e))
+        listener.process_message(
+            _event_message(
+                "press",
+                hoveredSeries="aaa",
+                seriesData={"aaa": {"value": 42.0}},
+            ),
+            [],
+        )
+        self.assertEqual(seen[0]["seriesData"], {"aaa": {"value": 42.0}})
+
+    def test_unknown_handler_is_noop(self):
+        listener = self._listener(on_press=lambda e: None)
+        out, refs = listener.process_message(_event_message("doublePress"), [])
+        self.assertEqual(out, b"")
+        self.assertEqual(refs, [])
+
+    def test_event_produces_no_response(self):
+        listener = self._listener(on_press=lambda e: None)
+        out, refs = listener.process_message(_event_message("press"), [])
+        self.assertEqual(out, b"")
+        self.assertEqual(refs, [])
+
+    def test_handler_exception_is_swallowed(self):
+        def boom(e):
+            raise RuntimeError("handler bug")
+
+        listener = self._listener(on_press=boom)
+        # Must not raise; stream survives.
+        out, refs = listener.process_message(_event_message("press"), [])
+        self.assertEqual(out, b"")
+
+    def test_exec_ctx_and_liveness_wrapping(self):
+        order = []
+
+        @contextlib.contextmanager
+        def fake_exec_ctx():
+            order.append("ctx-enter")
+            yield
+            order.append("ctx-exit")
+
+        @contextlib.contextmanager
+        def fake_liveness():
+            order.append("liveness-enter")
+            yield
+            order.append("liveness-exit")
+
+        chart = TvlChart(
+            series_list=[line_series(self.table)],
+            chart_options={},
+            on_press=lambda e: order.append("handler"),
+        )
+        listener = TvlChartListener(chart, MagicMock(), exec_ctx=fake_exec_ctx())
+
+        orig = listener_module.liveness_scope
+        listener_module.liveness_scope = fake_liveness
+        try:
+            listener.process_message(_event_message("press"), [])
+        finally:
+            listener_module.liveness_scope = orig
+
+        self.assertEqual(
+            order,
+            ["ctx-enter", "liveness-enter", "handler", "liveness-exit", "ctx-exit"],
+        )
+
+    def test_handler_can_mutate_external_state(self):
+        # Stand-in for "a table op in a handler succeeds": the handler does
+        # real work (here, mutating a shared structure) and it takes effect.
+        state = {"count": 0}
+        listener = self._listener(
+            on_press=lambda e: state.__setitem__("count", state["count"] + 1)
+        )
+        listener.process_message(_event_message("press"), [])
+        listener.process_message(_event_message("press"), [])
+        self.assertEqual(state["count"], 2)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_events.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_events.py
new file mode 100644
index 000000000..32a3b1ba4
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_events.py
@@ -0,0 +1,159 @@
+"""Tests for press-event API surface (Phase 1).
+
+Covers ``wrap_callable`` arity adaptation, the ``enabledHandlers`` advertised
+in ``to_dict``, and that the per-type constructors and ``chart()`` forward
+``on_press`` / ``on_double_press`` onto the resulting :class:`TvlChart`.
+"""
+
+from __future__ import annotations
+
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock
+
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight.chart import (  # noqa: E402
+    TvlChart,
+    chart,
+    line,
+    area,
+    candlestick,
+    bar,
+    baseline,
+    histogram,
+)
+from deephaven.plot.tradingview_lightweight.series import (  # noqa: E402
+    line_series,
+)
+from deephaven.plot.tradingview_lightweight import events  # noqa: E402
+from deephaven.plot.tradingview_lightweight.events import wrap_callable  # noqa: E402
+
+
+class TestWrapCallable(unittest.TestCase):
+    def test_zero_arg_handler_invoked_with_no_args(self):
+        seen = []
+        wrapped = wrap_callable(lambda: seen.append("called"))
+        wrapped({"type": "press"})  # surplus arg dropped
+        self.assertEqual(seen, ["called"])
+
+    def test_one_arg_handler_receives_event(self):
+        seen = []
+        wrapped = wrap_callable(lambda e: seen.append(e))
+        evt = {"type": "press", "seriesId": "series_0"}
+        wrapped(evt)
+        self.assertEqual(seen, [evt])
+
+    def test_var_positional_handler_receives_event(self):
+        seen = []
+        wrapped = wrap_callable(lambda *a: seen.append(a))
+        wrapped({"type": "press"})
+        self.assertEqual(seen, [({"type": "press"},)])
+
+    def test_def_one_arg(self):
+        captured = {}
+
+        def handler(event):
+            captured["event"] = event
+
+        wrap_callable(handler)({"type": "doublePress"})
+        self.assertEqual(captured["event"], {"type": "doublePress"})
+
+    def test_builtin_without_signature_returns_callable(self):
+        # print() has no introspectable signature in some builds; wrapping
+        # must not raise and the result must remain callable.
+        wrapped = wrap_callable(print)
+        self.assertTrue(callable(wrapped))
+
+
+class TestEnabledHandlers(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_no_handlers_no_key(self):
+        c = TvlChart(series_list=[line_series(self.table)], chart_options={})
+        self.assertEqual(c.enabled_handlers(), [])
+        self.assertNotIn("enabledHandlers", c.to_dict({id(self.table): 0}))
+
+    def test_press_only(self):
+        c = TvlChart(
+            series_list=[line_series(self.table)],
+            chart_options={},
+            on_press=lambda e: None,
+        )
+        self.assertEqual(c.enabled_handlers(), ["press"])
+        d = c.to_dict({id(self.table): 0})
+        self.assertEqual(d["enabledHandlers"], ["press"])
+
+    def test_double_press_only(self):
+        c = TvlChart(
+            series_list=[line_series(self.table)],
+            chart_options={},
+            on_double_press=lambda: None,
+        )
+        self.assertEqual(c.enabled_handlers(), ["doublePress"])
+
+    def test_both_handlers_order(self):
+        c = TvlChart(
+            series_list=[line_series(self.table)],
+            chart_options={},
+            on_press=lambda e: None,
+            on_double_press=lambda e: None,
+        )
+        self.assertEqual(c.enabled_handlers(), ["press", "doublePress"])
+        self.assertEqual(
+            c.to_dict({id(self.table): 0})["enabledHandlers"],
+            ["press", "doublePress"],
+        )
+
+
+class TestConstructorForwarding(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_line_forwards_handlers(self):
+        p = lambda e: None
+        dp = lambda: None
+        c = line(self.table, "T", "V", on_press=p, on_double_press=dp)
+        self.assertIs(c.on_press, p)
+        self.assertIs(c.on_double_press, dp)
+        self.assertEqual(c.enabled_handlers(), ["press", "doublePress"])
+        # Handlers must NOT leak into the series spec / column mapping.
+        self.assertEqual(len(c.series_list), 1)
+
+    def test_all_per_type_constructors_accept_handlers(self):
+        p = lambda e: None
+        constructors = [
+            lambda: line(self.table, "T", "V", on_press=p),
+            lambda: area(self.table, "T", "V", on_press=p),
+            lambda: candlestick(self.table, on_press=p),
+            lambda: bar(self.table, on_press=p),
+            lambda: baseline(self.table, "T", "V", on_press=p),
+            lambda: histogram(self.table, "T", "V", on_press=p),
+        ]
+        for make in constructors:
+            c = make()
+            self.assertIs(c.on_press, p)
+            self.assertEqual(c.enabled_handlers(), ["press"])
+
+    def test_chart_handlers_win_over_source(self):
+        # tvl.chart(...) discards source chart-level state; its own handlers
+        # apply. The source's handler is dropped (documented behavior).
+        src_handler = lambda e: None
+        chart_handler = lambda e: None
+        src = line(self.table, "T", "V", on_press=src_handler)
+        composed = chart(src, on_double_press=chart_handler)
+        self.assertIsNone(composed.on_press)
+        self.assertIs(composed.on_double_press, chart_handler)
+        self.assertEqual(composed.enabled_handlers(), ["doublePress"])
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_listener.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_listener.py
new file mode 100644
index 000000000..fac82c754
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_listener.py
@@ -0,0 +1,524 @@
+"""Tests for the TvlChartListener auto-bin dispatch logic.
+
+These tests focus on the eligibility-decision and message-dispatch paths
+without exercising real Deephaven aggregation. The aggregation primitives
+(``build_histogram_view`` / ``build_ohlc_view``) are mocked to return a
+sentinel object and the per-table ``size`` attribute drives the threshold
+decisions.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+from types import SimpleNamespace
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight import auto_bin  # noqa: E402
+from deephaven.plot.tradingview_lightweight.communication import (  # noqa: E402
+    listener as listener_module,
+)
+
+
+def _fake_table(size: int, is_refreshing: bool = True) -> SimpleNamespace:
+    """Minimal stand-in for a DH Table — enough for eligibility checks."""
+    return SimpleNamespace(size=size, is_refreshing=is_refreshing)
+
+
+def _make_series(
+    table: SimpleNamespace,
+    series_type: str,
+    column_mapping: dict | None = None,
+    *,
+    auto_bin: object = None,
+    bin_width: object = None,
+    bin_count: object = None,
+    agg: object = None,
+):
+    if column_mapping is None:
+        if series_type == "Histogram":
+            column_mapping = {"time": "Timestamp", "value": "Volume"}
+        elif series_type in {"Candlestick", "Bar"}:
+            column_mapping = {
+                "time": "Timestamp",
+                "open": "Open",
+                "high": "High",
+                "low": "Low",
+                "close": "Close",
+            }
+        else:
+            column_mapping = {"time": "Timestamp", "value": "Value"}
+    return SimpleNamespace(
+        series_type=series_type,
+        table=table,
+        column_mapping=column_mapping,
+        auto_bin=auto_bin,
+        bin_width=bin_width,
+        bin_count=bin_count,
+        agg=agg,
+        marker_spec=None,
+        by=None,
+        partitioned_table=None,
+    )
+
+
+def _make_chart(series_list, chart_type: str = "standard") -> SimpleNamespace:
+    """Minimal stand-in for TvlChart."""
+    seen = []
+    tables = []
+    for s in series_list:
+        if id(s.table) not in seen:
+            seen.append(id(s.table))
+            tables.append(s.table)
+    return SimpleNamespace(
+        series_list=series_list,
+        chart_type=chart_type,
+        get_tables=lambda: tables,
+        to_dict=lambda tid_map: {
+            "chartType": chart_type,
+            "chartOptions": {},
+            "series": [
+                {
+                    "id": f"series_{i}",
+                    "type": s.series_type,
+                    "options": {},
+                    "dataMapping": {
+                        "tableId": tid_map[id(s.table)],
+                        "columns": s.column_mapping,
+                    },
+                }
+                for i, s in enumerate(series_list)
+            ],
+        },
+    )
+
+
+@pytest.fixture(autouse=True)
+def _stub_aggregation(monkeypatch: pytest.MonkeyPatch):
+    """Replace the real aggregation primitives with sentinel-returning fakes."""
+    range_ns = (1_700_000_000_000_000_000, 1_700_086_400_000_000_000)  # 1 day
+    monkeypatch.setattr(auto_bin, "get_full_range_ns", lambda table, time_col: range_ns)
+
+    def _fake_hist(
+        raw,
+        time_col,
+        value_col,
+        bin_width_ns,
+        agg_mode="sum",
+        color_col=None,
+        *,
+        body_range_ns=None,
+        full_range_ns=None,
+    ):
+        return SimpleNamespace(
+            kind="hist",
+            raw=raw,
+            bin_width_ns=bin_width_ns,
+            agg=agg_mode,
+            body_range_ns=body_range_ns,
+            full_range_ns=full_range_ns,
+        )
+
+    def _fake_ohlc(
+        raw,
+        time_col,
+        o,
+        h,
+        l,
+        c,
+        bin_width_ns,
+        *,
+        body_range_ns=None,
+        full_range_ns=None,
+    ):
+        return SimpleNamespace(
+            kind="ohlc",
+            raw=raw,
+            bin_width_ns=bin_width_ns,
+            body_range_ns=body_range_ns,
+            full_range_ns=full_range_ns,
+        )
+
+    monkeypatch.setattr(auto_bin, "build_histogram_view", _fake_hist)
+    monkeypatch.setattr(auto_bin, "build_ohlc_view", _fake_ohlc)
+
+
+def _retrieve(listener) -> dict:
+    payload, _refs = listener.process_message(
+        json.dumps({"type": "RETRIEVE"}).encode(), []
+    )
+    return json.loads(payload.decode())
+
+
+class TestEligibility:
+    def test_default_large_histogram_triggers_autobin(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" in msg["figure"]
+        assert "1" in msg["figure"]["autoBinMeta"]
+
+    def test_default_small_histogram_skips_autobin(self):
+        small_table = _fake_table(size=10)
+        series = _make_series(small_table, "Histogram")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" not in msg["figure"]
+
+    def test_auto_bin_false_opts_out(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram", auto_bin=False)
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" not in msg["figure"]
+
+    def test_auto_bin_true_forces_small_table(self):
+        small_table = _fake_table(size=5)
+        series = _make_series(small_table, "Histogram", auto_bin=True)
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" in msg["figure"]
+
+    def test_yield_curve_chart_skips_autobin(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram")
+        chart = _make_chart([series], chart_type="yieldCurve")
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" not in msg["figure"]
+
+    def test_line_series_does_not_autobin(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Line")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" not in msg["figure"]
+        # But it should still flag for JS-side downsample
+        assert "downsampleMeta" in msg["figure"]
+
+    def test_candlestick_triggers_autobin_with_distinct_cols(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Candlestick")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert "autoBinMeta" in msg["figure"]
+        meta = msg["figure"]["autoBinMeta"]["1"]
+        assert meta["series"]["series_0"]["agg"] == "ohlc"
+
+
+class TestBinWidthChoice:
+    def test_default_uses_nice_bin_width(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        bw = msg["figure"]["autoBinMeta"]["1"]["binWidthNs"]
+        assert bw in auto_bin.NICE_BIN_WIDTHS_NS
+
+    def test_explicit_bin_width_overrides(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram", bin_width="PT1M")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert msg["figure"]["autoBinMeta"]["1"]["binWidthNs"] == 60 * 10**9
+
+    def test_explicit_bin_count_overrides_target(self):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram", bin_count=200)
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        msg = _retrieve(listener)
+        assert msg["figure"]["autoBinMeta"]["1"]["targetBins"] == 200
+
+
+class TestAutoBinMessages:
+    def _setup(self, *, range_ns=None):
+        big_table = _fake_table(size=1_000_000)
+        series = _make_series(big_table, "Histogram")
+        chart = _make_chart([series])
+        listener = listener_module.TvlChartListener(chart, MagicMock())
+        _retrieve(listener)
+        return listener
+
+    def test_zoom_with_unknown_table_ref_returns_empty(self):
+        listener = self._setup()
+        payload, _refs = listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 99,
+                    "fromNs": 0,
+                    "toNs": 1,
+                }
+            ).encode(),
+            [],
+        )
+        assert payload == b""
+
+    def test_repeated_identical_zoom_is_noop(self):
+        """Sending the same AUTOBIN_ZOOM twice should not rebuild the second
+        time — bin width and range are unchanged so nothing has shifted."""
+        listener = self._setup()
+        msg = {
+            "type": "AUTOBIN_ZOOM",
+            "tableRef": 1,
+            "fromNs": 1_700_000_000_000_000_000,
+            "toNs": 1_700_010_000_000_000_000,
+        }
+        # First call rebuilds.
+        listener.process_message(json.dumps(msg).encode(), [])
+        # Second identical call is a no-op.
+        payload, _refs = listener.process_message(json.dumps(msg).encode(), [])
+        assert payload != b""
+        ack = json.loads(payload.decode())
+        assert ack["type"] == "AUTOBIN_FIGURE"
+        assert ack.get("noop") is True
+
+    def test_zoom_below_resolution_rebuilds(self):
+        listener = self._setup()
+        # Visible window of 1ms — far below the default bin width of seconds.
+        payload, refs = listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 0,
+                    "toNs": 1_000_000,  # 1ms
+                }
+            ).encode(),
+            [],
+        )
+        assert payload != b""
+        msg = json.loads(payload.decode())
+        assert msg["type"] == "AUTOBIN_FIGURE"
+        assert msg.get("noop") is not True
+        # The reference list contains the original table at idx 0 and the
+        # rebuilt aggregated table at idx 1.
+        assert len(refs) == 2
+
+    def test_zoom_out_after_zoom_in_coarsens_bins(self):
+        """Zooming back out past target_bins * MAX_VISIBLE_BINS_RATIO triggers
+        a rebuild at a coarser width. Without this the chart stays at the
+        previously-zoomed-in fine bin width and looks sub-pixel-dense."""
+        listener = self._setup()
+        # Force a zoom-in to a tight window so bin_width gets very fine.
+        listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 0,
+                    "toNs": 1_000_000,  # 1 ms
+                }
+            ).encode(),
+            [],
+        )
+        state = listener._autobin_states[1]
+        fine_width = state.bin_width_ns
+        assert fine_width != state.initial_bin_width_ns
+
+        # Now zoom back out to the full range. With the fine width, that's
+        # way more than target_bins * MAX_VISIBLE_BINS_RATIO visible bins,
+        # so the server must coarsen.
+        full = 86_400_000_000_000  # 1 day
+        payload, _refs = listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 0,
+                    "toNs": full,
+                }
+            ).encode(),
+            [],
+        )
+        msg = json.loads(payload.decode())
+        assert msg["type"] == "AUTOBIN_FIGURE"
+        assert msg.get("noop") is not True
+        # Bins should have coarsened (numerically larger bin_width_ns).
+        assert state.bin_width_ns > fine_width
+
+    def test_reset_after_zoom_restores_initial_width(self):
+        listener = self._setup()
+        # First, force a re-aggregation to a finer width.
+        listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 0,
+                    "toNs": 1_000_000,
+                }
+            ).encode(),
+            [],
+        )
+        state = listener._autobin_states[1]
+        assert state.bin_width_ns != state.initial_bin_width_ns
+
+        # Now reset
+        payload, _refs = listener.process_message(
+            json.dumps({"type": "AUTOBIN_RESET", "tableRef": 1}).encode(), []
+        )
+        msg = json.loads(payload.decode())
+        assert msg["type"] == "AUTOBIN_FIGURE"
+        assert state.bin_width_ns == state.initial_bin_width_ns
+
+    def test_zoom_inside_full_range_scopes_body(self):
+        """A zoom strictly inside the source extent should rebuild with
+        body_range_ns set to the visible window — head/tail anchors flank
+        it. The aggregation table reflects (from, to) as the body bounds."""
+        listener = self._setup()
+        from_ns = 1_700_000_000_000_000_000 + 1_000_000
+        to_ns = 1_700_000_000_000_000_000 + 1_000_000_000  # 1s window
+        payload, _refs = listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": from_ns,
+                    "toNs": to_ns,
+                }
+            ).encode(),
+            [],
+        )
+        msg = json.loads(payload.decode())
+        assert msg["type"] == "AUTOBIN_FIGURE"
+        assert msg.get("noop") is not True
+        state = listener._autobin_states[1]
+        assert state.body_range_ns == (from_ns, to_ns)
+        # The fake aggregation primitive captures body_range_ns.
+        assert state.aggregated_table.body_range_ns == (from_ns, to_ns)
+        assert state.aggregated_table.full_range_ns == state.full_range_ns
+
+    def test_zoom_at_live_edge_extends_body_to_max_long(self):
+        """When atLiveEdge is set, body_range_ns[1] becomes MAX_LONG so
+        live ticks past the visible window's right edge land in the body."""
+        listener = self._setup()
+        max_long = (1 << 63) - 1
+        from_ns = 1_700_000_000_000_000_000 + 1_000_000
+        to_ns = 1_700_086_000_000_000_000  # near full_end
+        payload, _refs = listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": from_ns,
+                    "toNs": to_ns,
+                    "atLiveEdge": True,
+                }
+            ).encode(),
+            [],
+        )
+        msg = json.loads(payload.decode())
+        assert msg["type"] == "AUTOBIN_FIGURE"
+        state = listener._autobin_states[1]
+        assert state.body_range_ns == (from_ns, max_long)
+
+    def test_reset_clears_body_range(self):
+        """After a scoped zoom, AUTOBIN_RESET must clear body_range_ns so
+        the aggregation reverts to a full-source build (no anchors)."""
+        listener = self._setup()
+        listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 0,
+                    "toNs": 1_000_000,
+                }
+            ).encode(),
+            [],
+        )
+        state = listener._autobin_states[1]
+        assert state.body_range_ns is not None
+
+        listener.process_message(
+            json.dumps({"type": "AUTOBIN_RESET", "tableRef": 1}).encode(), []
+        )
+        assert state.body_range_ns is None
+
+    def test_pan_with_unchanged_width_still_rebuilds(self):
+        """Pan changes the body window even when bin width is the same.
+        The old viewport-shift path treated this as a no-op; with body
+        scoping the server must rebuild so the body covers the new
+        window."""
+        listener = self._setup()
+        # First scoped zoom to establish body + a fine width.
+        listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 0,
+                    "toNs": 1_000_000_000,  # 1s window
+                }
+            ).encode(),
+            [],
+        )
+        state = listener._autobin_states[1]
+        width_after_zoom = state.bin_width_ns
+        # Now pan to the right by the same window duration → bin_width
+        # stays the same (same visible_ns) but body_range moves.
+        payload, _refs = listener.process_message(
+            json.dumps(
+                {
+                    "type": "AUTOBIN_ZOOM",
+                    "tableRef": 1,
+                    "fromNs": 1_000_000_000,
+                    "toNs": 2_000_000_000,
+                }
+            ).encode(),
+            [],
+        )
+        msg = json.loads(payload.decode())
+        assert msg["type"] == "AUTOBIN_FIGURE"
+        assert msg.get("noop") is not True
+        assert state.bin_width_ns == width_after_zoom
+        assert state.body_range_ns == (1_000_000_000, 2_000_000_000)
+
+    def test_unknown_message_type_returns_empty(self):
+        listener = self._setup()
+        payload, _refs = listener.process_message(
+            json.dumps({"type": "BOGUS"}).encode(), []
+        )
+        assert payload == b""
+
+    def test_invalid_payload_returns_empty(self):
+        listener = self._setup()
+        payload, _refs = listener.process_message(b"not json", [])
+        assert payload == b""
+
+
+class TestAutoBinThresholdEnv:
+    def test_threshold_overridable_via_env(self, monkeypatch: pytest.MonkeyPatch):
+        # Reload to re-evaluate env var
+        monkeypatch.setenv("TVL_AUTO_BIN_THRESHOLD", "100")
+        import importlib
+
+        importlib.reload(listener_module)
+        try:
+            assert listener_module.AUTO_BIN_THRESHOLD == 100
+        finally:
+            monkeypatch.delenv("TVL_AUTO_BIN_THRESHOLD")
+            importlib.reload(listener_module)
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_markers.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_markers.py
new file mode 100644
index 000000000..19721fc7f
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_markers.py
@@ -0,0 +1,1182 @@
+"""Tests for marker and price line creation."""
+
+from __future__ import annotations
+
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock
+
+# Add src to path for namespace package resolution
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight.markers import (
+    Marker,
+    PriceLine,
+    MarkerSpec,
+    marker,
+    price_line,
+    markers_from_table,
+    up_down_markers,
+)
+
+
+class TestMarkerDataclass(unittest.TestCase):
+    """Tests for the Marker dataclass directly."""
+
+    def test_defaults(self):
+        m = Marker(time="2024-01-01")
+        self.assertEqual(m.time, "2024-01-01")
+        self.assertEqual(m.position, "aboveBar")
+        self.assertEqual(m.shape, "circle")
+        self.assertIsNone(m.color)
+        self.assertEqual(m.text, "")
+        self.assertIsNone(m.size)
+        self.assertIsNone(m.id)
+        self.assertIsNone(m.price)
+
+    def test_custom_values(self):
+        m = Marker(
+            time=1704067200,
+            position="belowBar",
+            shape="arrowUp",
+            color="#ff0000",
+            text="Buy",
+            size=3,
+        )
+        self.assertEqual(m.time, 1704067200)
+        self.assertEqual(m.position, "belowBar")
+        self.assertEqual(m.shape, "arrowUp")
+        self.assertEqual(m.color, "#ff0000")
+        self.assertEqual(m.text, "Buy")
+        self.assertEqual(m.size, 3)
+
+    def test_to_dict_defaults(self):
+        m = Marker(time="2024-01-01")
+        d = m.to_dict()
+        self.assertEqual(d["time"], "2024-01-01")
+        self.assertEqual(d["position"], "aboveBar")
+        self.assertEqual(d["shape"], "circle")
+        self.assertNotIn("color", d)
+        self.assertEqual(d["text"], "")
+        self.assertNotIn("size", d)
+
+    def test_to_dict_with_size(self):
+        m = Marker(time="2024-01-01", size=2)
+        d = m.to_dict()
+        self.assertEqual(d["size"], 2)
+
+    def test_to_dict_all_fields(self):
+        m = Marker(
+            time="2024-06-15",
+            position="inBar",
+            shape="square",
+            color="green",
+            text="Signal",
+            size=5,
+        )
+        d = m.to_dict()
+        expected = {
+            "time": "2024-06-15",
+            "position": "inBar",
+            "shape": "square",
+            "color": "green",
+            "text": "Signal",
+            "size": 5,
+        }
+        self.assertEqual(d, expected)
+
+    def test_time_types(self):
+        """Marker time can be string, int, or float."""
+        m_str = Marker(time="2024-01-01")
+        m_int = Marker(time=1704067200)
+        m_float = Marker(time=1704067200.5)
+        self.assertEqual(m_str.to_dict()["time"], "2024-01-01")
+        self.assertEqual(m_int.to_dict()["time"], 1704067200)
+        self.assertEqual(m_float.to_dict()["time"], 1704067200.5)
+
+
+class TestMarkerFunction(unittest.TestCase):
+    """Tests for the marker() factory function."""
+
+    def test_defaults(self):
+        m = marker(time="2024-01-01")
+        self.assertIsInstance(m, Marker)
+        self.assertEqual(m.time, "2024-01-01")
+        self.assertEqual(m.position, "aboveBar")
+        self.assertEqual(m.shape, "circle")
+        self.assertIsNone(m.color)
+        self.assertEqual(m.text, "")
+        self.assertIsNone(m.size)
+        self.assertIsNone(m.id)
+        self.assertIsNone(m.price)
+
+    def test_position_mapping(self):
+        """Python-friendly position names should be converted to camelCase."""
+        m_above = marker(time="t", position="above_bar")
+        self.assertEqual(m_above.position, "aboveBar")
+
+        m_below = marker(time="t", position="below_bar")
+        self.assertEqual(m_below.position, "belowBar")
+
+        m_in = marker(time="t", position="in_bar")
+        self.assertEqual(m_in.position, "inBar")
+
+    def test_shape_mapping(self):
+        """Python-friendly shape names should be converted to camelCase."""
+        m_circle = marker(time="t", shape="circle")
+        self.assertEqual(m_circle.shape, "circle")
+
+        m_square = marker(time="t", shape="square")
+        self.assertEqual(m_square.shape, "square")
+
+        m_up = marker(time="t", shape="arrow_up")
+        self.assertEqual(m_up.shape, "arrowUp")
+
+        m_down = marker(time="t", shape="arrow_down")
+        self.assertEqual(m_down.shape, "arrowDown")
+
+    def test_custom_values(self):
+        m = marker(
+            time=1704067200,
+            position="below_bar",
+            shape="arrow_up",
+            color="#00ff00",
+            text="Buy Signal",
+            size=4,
+        )
+        self.assertEqual(m.time, 1704067200)
+        self.assertEqual(m.position, "belowBar")
+        self.assertEqual(m.shape, "arrowUp")
+        self.assertEqual(m.color, "#00ff00")
+        self.assertEqual(m.text, "Buy Signal")
+        self.assertEqual(m.size, 4)
+
+    def test_to_dict_from_factory(self):
+        m = marker(
+            time="2024-03-15",
+            position="above_bar",
+            shape="arrow_down",
+            color="red",
+            text="Sell",
+            size=2,
+        )
+        d = m.to_dict()
+        self.assertEqual(d["time"], "2024-03-15")
+        self.assertEqual(d["position"], "aboveBar")
+        self.assertEqual(d["shape"], "arrowDown")
+        self.assertEqual(d["color"], "red")
+        self.assertEqual(d["text"], "Sell")
+        self.assertEqual(d["size"], 2)
+
+    def test_unknown_position_fallback(self):
+        """Unknown position should fall back to 'aboveBar'."""
+        m = marker(time="t", position="invalid")
+        self.assertEqual(m.position, "aboveBar")
+
+    def test_unknown_shape_fallback(self):
+        """Unknown shape should fall back to 'circle'."""
+        m = marker(time="t", shape="star")
+        self.assertEqual(m.shape, "circle")
+
+
+class TestMarkerIdAndPrice(unittest.TestCase):
+    """Tests for the new 'id' and 'price' fields on Marker."""
+
+    def test_id_default_is_none(self):
+        m = Marker(time="2024-01-01")
+        self.assertIsNone(m.id)
+
+    def test_price_default_is_none(self):
+        m = Marker(time="2024-01-01")
+        self.assertIsNone(m.price)
+
+    def test_id_not_emitted_when_none(self):
+        m = Marker(time="2024-01-01")
+        d = m.to_dict()
+        self.assertNotIn("id", d)
+
+    def test_price_not_emitted_when_none(self):
+        m = Marker(time="2024-01-01")
+        d = m.to_dict()
+        self.assertNotIn("price", d)
+
+    def test_id_emitted_when_set(self):
+        m = Marker(time="2024-01-01", id="marker-42")
+        d = m.to_dict()
+        self.assertEqual(d["id"], "marker-42")
+
+    def test_price_emitted_when_set(self):
+        m = Marker(time="2024-01-01", position="atPriceTop", price=150.5)
+        d = m.to_dict()
+        self.assertEqual(d["price"], 150.5)
+
+    def test_factory_id_param(self):
+        m = marker(time="t", id="sig-001")
+        self.assertEqual(m.id, "sig-001")
+        self.assertEqual(m.to_dict()["id"], "sig-001")
+
+    def test_factory_price_param(self):
+        m = marker(time="t", position="at_price_top", price=200.0)
+        self.assertEqual(m.price, 200.0)
+        self.assertEqual(m.to_dict()["price"], 200.0)
+
+    def test_factory_id_and_price_together(self):
+        m = marker(
+            time="2024-06-01",
+            position="at_price_middle",
+            price=175.25,
+            id="signal-x",
+            color="orange",
+            text="Mid",
+        )
+        d = m.to_dict()
+        self.assertEqual(d["id"], "signal-x")
+        self.assertEqual(d["price"], 175.25)
+        self.assertEqual(d["position"], "atPriceMiddle")
+
+
+class TestPriceBasedPositions(unittest.TestCase):
+    """Tests for atPriceTop, atPriceBottom, atPriceMiddle positions."""
+
+    def test_at_price_top_mapping(self):
+        m = marker(time="t", position="at_price_top", price=100.0)
+        self.assertEqual(m.position, "atPriceTop")
+
+    def test_at_price_bottom_mapping(self):
+        m = marker(time="t", position="at_price_bottom", price=100.0)
+        self.assertEqual(m.position, "atPriceBottom")
+
+    def test_at_price_middle_mapping(self):
+        m = marker(time="t", position="at_price_middle", price=100.0)
+        self.assertEqual(m.position, "atPriceMiddle")
+
+    def test_at_price_top_in_position_map(self):
+        from deephaven.plot.tradingview_lightweight.options import MARKER_POSITION_MAP
+
+        self.assertEqual(MARKER_POSITION_MAP["at_price_top"], "atPriceTop")
+        self.assertEqual(MARKER_POSITION_MAP["at_price_bottom"], "atPriceBottom")
+        self.assertEqual(MARKER_POSITION_MAP["at_price_middle"], "atPriceMiddle")
+
+    def test_price_position_without_price_raises(self):
+        """Using a price-based position without price= must raise ValueError."""
+        with self.assertRaises(ValueError):
+            Marker(time="t", position="atPriceTop")
+
+    def test_price_position_without_price_raises_via_factory(self):
+        with self.assertRaises(ValueError):
+            marker(time="t", position="at_price_top")  # no price=
+
+    def test_bar_position_without_price_is_fine(self):
+        """Bar positions do not require price."""
+        m = marker(time="t", position="above_bar")
+        self.assertIsNone(m.price)
+
+    def test_price_serialized_for_price_position(self):
+        m = marker(time="2024-01-15", position="at_price_bottom", price=99.5)
+        d = m.to_dict()
+        self.assertEqual(d["position"], "atPriceBottom")
+        self.assertEqual(d["price"], 99.5)
+
+    def test_all_six_positions_map_correctly(self):
+        from deephaven.plot.tradingview_lightweight.options import MARKER_POSITION_MAP
+
+        expected = {
+            "above_bar": "aboveBar",
+            "below_bar": "belowBar",
+            "in_bar": "inBar",
+            "at_price_top": "atPriceTop",
+            "at_price_bottom": "atPriceBottom",
+            "at_price_middle": "atPriceMiddle",
+        }
+        self.assertEqual(MARKER_POSITION_MAP, expected)
+
+
+class TestUpDownMarkers(unittest.TestCase):
+    """Tests for the up_down_markers() convenience factory."""
+
+    def test_returns_list_of_markers(self):
+        result = up_down_markers(["2024-01-01"], ["2024-01-02"])
+        self.assertIsInstance(result, list)
+        self.assertTrue(all(isinstance(m, Marker) for m in result))
+
+    def test_total_count(self):
+        result = up_down_markers(["t1", "t2", "t3"], ["t4"])
+        self.assertEqual(len(result), 4)
+
+    def test_up_marker_defaults(self):
+        result = up_down_markers(["t1"], [])
+        m = result[0]
+        self.assertEqual(m.position, "belowBar")
+        self.assertEqual(m.shape, "arrowUp")
+        self.assertIsNone(m.color)
+        self.assertEqual(m.text, "")
+        self.assertIsNone(m.size)
+
+    def test_down_marker_defaults(self):
+        result = up_down_markers([], ["t1"])
+        m = result[0]
+        self.assertEqual(m.position, "aboveBar")
+        self.assertEqual(m.shape, "arrowDown")
+        self.assertIsNone(m.color)
+        self.assertEqual(m.text, "")
+        self.assertIsNone(m.size)
+
+    def test_custom_colors(self):
+        result = up_down_markers(["t1"], ["t2"], up_color="blue", down_color="orange")
+        self.assertEqual(result[0].color, "blue")  # up marker
+        self.assertEqual(result[1].color, "orange")  # down marker
+
+    def test_custom_text(self):
+        result = up_down_markers(["t1"], ["t2"], up_text="Buy", down_text="Sell")
+        self.assertEqual(result[0].text, "Buy")
+        self.assertEqual(result[1].text, "Sell")
+
+    def test_custom_size(self):
+        result = up_down_markers(["t1"], ["t2"], up_size=3, down_size=2)
+        self.assertEqual(result[0].size, 3)
+        self.assertEqual(result[1].size, 2)
+
+    def test_empty_up_list(self):
+        result = up_down_markers([], ["t1", "t2"])
+        self.assertEqual(len(result), 2)
+        self.assertTrue(all(m.shape == "arrowDown" for m in result))
+
+    def test_empty_down_list(self):
+        result = up_down_markers(["t1", "t2"], [])
+        self.assertEqual(len(result), 2)
+        self.assertTrue(all(m.shape == "arrowUp" for m in result))
+
+    def test_empty_both(self):
+        result = up_down_markers([], [])
+        self.assertEqual(result, [])
+
+    def test_time_values_preserved(self):
+        result = up_down_markers(["2024-01-01", 1704067200], ["2024-02-01"])
+        self.assertEqual(result[0].time, "2024-01-01")
+        self.assertEqual(result[1].time, 1704067200)
+        self.assertEqual(result[2].time, "2024-02-01")
+
+    def test_ordering_up_then_down(self):
+        """Up markers are first in the returned list."""
+        result = up_down_markers(["u1", "u2"], ["d1"])
+        self.assertEqual(result[0].shape, "arrowUp")
+        self.assertEqual(result[1].shape, "arrowUp")
+        self.assertEqual(result[2].shape, "arrowDown")
+
+    def test_serializes_correctly_in_series(self):
+        """Combined list can be attached to a series and serializes cleanly."""
+        from deephaven.plot.tradingview_lightweight.series import candlestick_series
+
+        table = MagicMock(name="table")
+        markers = up_down_markers(["2024-01-05"], ["2024-01-10"])
+        spec = candlestick_series(table, markers=markers)
+        d = spec.to_dict("s0", 0)
+        self.assertEqual(len(d["markers"]), 2)
+        self.assertEqual(d["markers"][0]["shape"], "arrowUp")
+        self.assertEqual(d["markers"][0]["position"], "belowBar")
+        self.assertEqual(d["markers"][1]["shape"], "arrowDown")
+        self.assertEqual(d["markers"][1]["position"], "aboveBar")
+
+
+class TestMarkerSpecPriceAndId(unittest.TestCase):
+    """Tests for price, price_column, and id_column on MarkerSpec."""
+
+    def test_price_default_is_none(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table)
+        self.assertIsNone(spec.price)
+
+    def test_price_column_default_is_none(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table)
+        self.assertIsNone(spec.price_column)
+
+    def test_id_column_default_is_none(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table)
+        self.assertIsNone(spec.id_column)
+
+    def test_static_price_in_defaults(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, price=123.45)
+        d = spec.to_dict(table_id=0)
+        self.assertEqual(d["defaults"]["price"], 123.45)
+        self.assertNotIn("price", d["columns"])
+
+    def test_price_not_in_defaults_when_none(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table)
+        d = spec.to_dict(table_id=0)
+        self.assertNotIn("price", d["defaults"])
+
+    def test_price_column_in_columns(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, price_column="BidPrice")
+        d = spec.to_dict(table_id=0)
+        self.assertEqual(d["columns"]["price"], "BidPrice")
+        self.assertNotIn("price", d["defaults"])
+
+    def test_id_column_in_columns(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, id_column="MarkerId")
+        d = spec.to_dict(table_id=0)
+        self.assertEqual(d["columns"]["id"], "MarkerId")
+
+    def test_price_and_price_column_raises(self):
+        table = MagicMock(name="table")
+        with self.assertRaises(ValueError):
+            MarkerSpec(table=table, price=100.0, price_column="PriceCol")
+
+    def test_get_columns_includes_price_column(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, timestamp="T", price_column="Px")
+        cols = spec.get_columns()
+        self.assertIn("Px", cols)
+
+    def test_get_columns_includes_id_column(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, timestamp="T", id_column="Mid")
+        cols = spec.get_columns()
+        self.assertIn("Mid", cols)
+
+    def test_markers_from_table_price_param(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(table, price=99.0)
+        self.assertEqual(spec.price, 99.0)
+
+    def test_markers_from_table_price_column(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(table, price_column="AskPrice")
+        self.assertEqual(spec.price_column, "AskPrice")
+
+    def test_markers_from_table_id_column(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(table, id_column="EventId")
+        self.assertEqual(spec.id_column, "EventId")
+
+
+class TestPriceLineDataclass(unittest.TestCase):
+    """Tests for the PriceLine dataclass directly."""
+
+    def test_defaults(self):
+        pl = PriceLine(price=100.0)
+        self.assertEqual(pl.price, 100.0)
+        self.assertIsNone(pl.color)
+        self.assertIsNone(pl.line_width)
+        self.assertIsNone(pl.line_style)
+        self.assertIsNone(pl.axis_label_visible)
+        self.assertIsNone(pl.title)
+
+    def test_custom_values(self):
+        pl = PriceLine(
+            price=150.0,
+            color="red",
+            line_width=2,
+            line_style="dashed",
+            axis_label_visible=True,
+            title="Resistance",
+        )
+        self.assertEqual(pl.price, 150.0)
+        self.assertEqual(pl.color, "red")
+        self.assertEqual(pl.line_width, 2)
+        self.assertEqual(pl.line_style, "dashed")
+        self.assertTrue(pl.axis_label_visible)
+        self.assertEqual(pl.title, "Resistance")
+
+    def test_to_dict_minimal(self):
+        pl = PriceLine(price=50.0)
+        d = pl.to_dict()
+        self.assertEqual(d, {"price": 50.0})
+
+    def test_to_dict_all_fields(self):
+        pl = PriceLine(
+            price=200.0,
+            color="blue",
+            line_width=3,
+            line_style="dotted",
+            axis_label_visible=False,
+            title="Target",
+        )
+        d = pl.to_dict()
+        self.assertEqual(d["price"], 200.0)
+        self.assertEqual(d["color"], "blue")
+        self.assertEqual(d["lineWidth"], 3)
+        self.assertEqual(d["lineStyle"], 1)  # dotted -> 1
+        self.assertFalse(d["axisLabelVisible"])
+        self.assertEqual(d["title"], "Target")
+
+    def test_to_dict_line_style_conversion(self):
+        """line_style string should be converted to integer in to_dict."""
+        styles = {
+            "solid": 0,
+            "dotted": 1,
+            "dashed": 2,
+            "large_dashed": 3,
+            "sparse_dotted": 4,
+        }
+        for style_name, style_value in styles.items():
+            pl = PriceLine(price=100.0, line_style=style_name)
+            d = pl.to_dict()
+            self.assertEqual(
+                d["lineStyle"],
+                style_value,
+                f"Style {style_name} should map to {style_value}",
+            )
+
+    def test_to_dict_partial(self):
+        """Only set fields should appear in the dict (besides price)."""
+        pl = PriceLine(price=75.0, color="green")
+        d = pl.to_dict()
+        self.assertEqual(d["price"], 75.0)
+        self.assertEqual(d["color"], "green")
+        self.assertNotIn("lineWidth", d)
+        self.assertNotIn("lineStyle", d)
+        self.assertNotIn("axisLabelVisible", d)
+        self.assertNotIn("title", d)
+
+    def test_new_fields_default_to_none(self):
+        """New fields must default to None (not emitted in to_dict)."""
+        pl = PriceLine(price=100.0)
+        self.assertIsNone(pl.id)
+        self.assertIsNone(pl.line_visible)
+        self.assertIsNone(pl.axis_label_color)
+        self.assertIsNone(pl.axis_label_text_color)
+
+    def test_new_fields_absent_from_dict_when_none(self):
+        """to_dict() must not emit new keys when their values are None."""
+        pl = PriceLine(price=100.0)
+        d = pl.to_dict()
+        self.assertNotIn("id", d)
+        self.assertNotIn("lineVisible", d)
+        self.assertNotIn("axisLabelColor", d)
+        self.assertNotIn("axisLabelTextColor", d)
+
+    def test_id_field(self):
+        pl = PriceLine(price=100.0, id="support-1")
+        self.assertEqual(pl.id, "support-1")
+        d = pl.to_dict()
+        self.assertEqual(d["id"], "support-1")
+
+    def test_id_empty_string(self):
+        """Empty string id should be emitted (it is a valid non-None value)."""
+        pl = PriceLine(price=100.0, id="")
+        d = pl.to_dict()
+        self.assertIn("id", d)
+        self.assertEqual(d["id"], "")
+
+    def test_line_visible_true(self):
+        pl = PriceLine(price=100.0, line_visible=True)
+        d = pl.to_dict()
+        self.assertTrue(d["lineVisible"])
+
+    def test_line_visible_false(self):
+        pl = PriceLine(price=100.0, line_visible=False)
+        d = pl.to_dict()
+        self.assertFalse(d["lineVisible"])
+
+    def test_line_visible_hidden_with_label_shown(self):
+        """Typical use: hide line rule but keep axis label."""
+        pl = PriceLine(price=200.0, line_visible=False, axis_label_visible=True)
+        d = pl.to_dict()
+        self.assertFalse(d["lineVisible"])
+        self.assertTrue(d["axisLabelVisible"])
+
+    def test_axis_label_color(self):
+        pl = PriceLine(price=100.0, axis_label_color="#FF0000")
+        d = pl.to_dict()
+        self.assertEqual(d["axisLabelColor"], "#FF0000")
+
+    def test_axis_label_color_independent_of_line_color(self):
+        """axis_label_color and color are independent fields."""
+        pl = PriceLine(price=100.0, color="blue", axis_label_color="red")
+        d = pl.to_dict()
+        self.assertEqual(d["color"], "blue")
+        self.assertEqual(d["axisLabelColor"], "red")
+
+    def test_axis_label_text_color(self):
+        pl = PriceLine(price=100.0, axis_label_text_color="#FFFFFF")
+        d = pl.to_dict()
+        self.assertEqual(d["axisLabelTextColor"], "#FFFFFF")
+
+    def test_axis_label_colors_together(self):
+        """Both label color fields can be set independently."""
+        pl = PriceLine(
+            price=100.0,
+            axis_label_color="#333333",
+            axis_label_text_color="#EEEEEE",
+        )
+        d = pl.to_dict()
+        self.assertEqual(d["axisLabelColor"], "#333333")
+        self.assertEqual(d["axisLabelTextColor"], "#EEEEEE")
+
+    def test_to_dict_all_new_and_existing_fields(self):
+        """All 10 JS PriceLineOptions properties should serialize correctly."""
+        pl = PriceLine(
+            price=150.0,
+            id="target",
+            color="#0000FF",
+            line_width=2,
+            line_style="dashed",
+            line_visible=True,
+            axis_label_visible=True,
+            title="Target",
+            axis_label_color="#0000FF",
+            axis_label_text_color="#FFFFFF",
+        )
+        d = pl.to_dict()
+        self.assertEqual(d["id"], "target")
+        self.assertEqual(d["price"], 150.0)
+        self.assertEqual(d["color"], "#0000FF")
+        self.assertEqual(d["lineWidth"], 2)
+        self.assertEqual(d["lineStyle"], 2)  # dashed -> 2
+        self.assertTrue(d["lineVisible"])
+        self.assertTrue(d["axisLabelVisible"])
+        self.assertEqual(d["title"], "Target")
+        self.assertEqual(d["axisLabelColor"], "#0000FF")
+        self.assertEqual(d["axisLabelTextColor"], "#FFFFFF")
+
+
+class TestPriceLineFunction(unittest.TestCase):
+    """Tests for the price_line() factory function."""
+
+    def test_defaults(self):
+        pl = price_line(price=100.0)
+        self.assertIsInstance(pl, PriceLine)
+        self.assertEqual(pl.price, 100.0)
+        self.assertIsNone(pl.color)
+        self.assertIsNone(pl.line_width)
+        self.assertIsNone(pl.line_style)
+        self.assertIsNone(pl.axis_label_visible)
+        self.assertIsNone(pl.title)
+
+    def test_custom_values(self):
+        pl = price_line(
+            price=250.0,
+            color="orange",
+            line_width=1,
+            line_style="dashed",
+            axis_label_visible=True,
+            title="Stop Loss",
+        )
+        self.assertEqual(pl.price, 250.0)
+        self.assertEqual(pl.color, "orange")
+        self.assertEqual(pl.line_width, 1)
+        self.assertEqual(pl.line_style, "dashed")
+        self.assertTrue(pl.axis_label_visible)
+        self.assertEqual(pl.title, "Stop Loss")
+
+    def test_serialization(self):
+        pl = price_line(price=300.0, color="purple", title="Entry")
+        d = pl.to_dict()
+        self.assertEqual(d["price"], 300.0)
+        self.assertEqual(d["color"], "purple")
+        self.assertEqual(d["title"], "Entry")
+
+    def test_new_params_default_to_none(self):
+        pl = price_line(price=100.0)
+        self.assertIsNone(pl.id)
+        self.assertIsNone(pl.line_visible)
+        self.assertIsNone(pl.axis_label_color)
+        self.assertIsNone(pl.axis_label_text_color)
+
+    def test_new_params_pass_through(self):
+        pl = price_line(
+            price=100.0,
+            id="resistance",
+            line_visible=False,
+            axis_label_color="#FF0000",
+            axis_label_text_color="#FFFFFF",
+        )
+        self.assertEqual(pl.id, "resistance")
+        self.assertFalse(pl.line_visible)
+        self.assertEqual(pl.axis_label_color, "#FF0000")
+        self.assertEqual(pl.axis_label_text_color, "#FFFFFF")
+
+    def test_new_params_serialized(self):
+        pl = price_line(
+            price=100.0,
+            id="resistance",
+            line_visible=False,
+            axis_label_color="#FF0000",
+            axis_label_text_color="#FFFFFF",
+        )
+        d = pl.to_dict()
+        self.assertEqual(d["id"], "resistance")
+        self.assertFalse(d["lineVisible"])
+        self.assertEqual(d["axisLabelColor"], "#FF0000")
+        self.assertEqual(d["axisLabelTextColor"], "#FFFFFF")
+
+    def test_column_with_new_fields(self):
+        """Dynamic price line (column=) should work with all new fields."""
+        pl = price_line(
+            column="AvgClose",
+            id="avg-close",
+            line_visible=True,
+            axis_label_color="green",
+            axis_label_text_color="white",
+        )
+        d = pl.to_dict()
+        self.assertEqual(d["column"], "AvgClose")
+        self.assertEqual(d["id"], "avg-close")
+        self.assertTrue(d["lineVisible"])
+        self.assertEqual(d["axisLabelColor"], "green")
+        self.assertEqual(d["axisLabelTextColor"], "white")
+        self.assertNotIn("price", d)
+
+
+class TestMarkerSpec(unittest.TestCase):
+    """Tests for the MarkerSpec dataclass."""
+
+    def test_defaults(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table)
+        self.assertIs(spec.table, table)
+        self.assertEqual(spec.timestamp, "Timestamp")
+        self.assertEqual(spec.position, "above_bar")
+        self.assertEqual(spec.shape, "circle")
+        self.assertIsNone(spec.color)
+        self.assertEqual(spec.text, "")
+        self.assertIsNone(spec.size)
+
+    def test_custom_values(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(
+            table=table,
+            timestamp="Date",
+            position="below_bar",
+            shape="arrow_up",
+            color="red",
+            text="alert",
+            size=3,
+        )
+        self.assertEqual(spec.timestamp, "Date")
+        self.assertEqual(spec.position, "below_bar")
+        self.assertEqual(spec.shape, "arrow_up")
+        self.assertEqual(spec.color, "red")
+        self.assertEqual(spec.text, "alert")
+        self.assertEqual(spec.size, 3)
+
+
+class TestMarkersFromTable(unittest.TestCase):
+    """Tests for the markers_from_table() function."""
+
+    def test_defaults(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(table)
+        self.assertIsInstance(spec, MarkerSpec)
+        self.assertIs(spec.table, table)
+        self.assertEqual(spec.timestamp, "Timestamp")
+        self.assertEqual(spec.position, "above_bar")
+        self.assertEqual(spec.shape, "circle")
+        self.assertIsNone(spec.color)
+        self.assertEqual(spec.text, "")
+        self.assertIsNone(spec.size)
+
+    def test_custom_values(self):
+        table = MagicMock(name="marker_table")
+        spec = markers_from_table(
+            table,
+            timestamp="EventTime",
+            position="in_bar",
+            shape="square",
+            color="#ff6600",
+            text="event",
+            size=2,
+        )
+        self.assertIs(spec.table, table)
+        self.assertEqual(spec.timestamp, "EventTime")
+        self.assertEqual(spec.position, "in_bar")
+        self.assertEqual(spec.shape, "square")
+        self.assertEqual(spec.color, "#ff6600")
+        self.assertEqual(spec.text, "event")
+        self.assertEqual(spec.size, 2)
+
+
+class TestMarkerIntegration(unittest.TestCase):
+    """Integration tests for markers used within series."""
+
+    def test_markers_serialize_in_series(self):
+        """Markers attached to a series should serialize properly."""
+        from deephaven.plot.tradingview_lightweight.series import line_series
+
+        table = MagicMock(name="table")
+        m1 = marker(
+            time="2024-01-15",
+            position="above_bar",
+            shape="arrow_down",
+            color="red",
+            text="Sell",
+        )
+        m2 = marker(
+            time="2024-02-15",
+            position="below_bar",
+            shape="arrow_up",
+            color="green",
+            text="Buy",
+        )
+        pl = price_line(price=100.0, color="gray", line_style="dashed", title="Support")
+
+        spec = line_series(table, markers=[m1, m2], price_lines=[pl])
+        result = spec.to_dict("s0", 0)
+
+        self.assertEqual(len(result["markers"]), 2)
+        self.assertEqual(result["markers"][0]["position"], "aboveBar")
+        self.assertEqual(result["markers"][0]["shape"], "arrowDown")
+        self.assertEqual(result["markers"][0]["text"], "Sell")
+        self.assertEqual(result["markers"][1]["position"], "belowBar")
+        self.assertEqual(result["markers"][1]["shape"], "arrowUp")
+        self.assertEqual(result["markers"][1]["text"], "Buy")
+
+        self.assertEqual(len(result["priceLines"]), 1)
+        self.assertEqual(result["priceLines"][0]["price"], 100.0)
+        self.assertEqual(result["priceLines"][0]["lineStyle"], 2)  # dashed
+        self.assertEqual(result["priceLines"][0]["title"], "Support")
+
+
+class TestDynamicPriceLine(unittest.TestCase):
+    """Tests for column-based dynamic price lines."""
+
+    def test_column_creates_dynamic_price_line(self):
+        pl = PriceLine(column="AvgPrice")
+        self.assertIsNone(pl.price)
+        self.assertEqual(pl.column, "AvgPrice")
+
+    def test_column_to_dict(self):
+        pl = PriceLine(column="MaxPrice", color="green", title="High")
+        d = pl.to_dict()
+        self.assertEqual(d["column"], "MaxPrice")
+        self.assertEqual(d["color"], "green")
+        self.assertEqual(d["title"], "High")
+        self.assertNotIn("price", d)
+
+    def test_static_to_dict_no_column(self):
+        pl = PriceLine(price=100.0)
+        d = pl.to_dict()
+        self.assertEqual(d["price"], 100.0)
+        self.assertNotIn("column", d)
+
+    def test_validation_neither(self):
+        with self.assertRaises(ValueError):
+            PriceLine()
+
+    def test_validation_both(self):
+        with self.assertRaises(ValueError):
+            PriceLine(price=100.0, column="AvgPrice")
+
+    def test_factory_with_column(self):
+        pl = price_line(column="MinPrice", color="red", title="Low")
+        self.assertIsInstance(pl, PriceLine)
+        self.assertIsNone(pl.price)
+        self.assertEqual(pl.column, "MinPrice")
+        self.assertEqual(pl.color, "red")
+        self.assertEqual(pl.title, "Low")
+
+    def test_factory_column_with_styling(self):
+        pl = price_line(
+            column="AvgPrice",
+            color="blue",
+            line_width=2,
+            line_style="dashed",
+            axis_label_visible=True,
+            title="Average",
+        )
+        d = pl.to_dict()
+        self.assertEqual(d["column"], "AvgPrice")
+        self.assertEqual(d["color"], "blue")
+        self.assertEqual(d["lineWidth"], 2)
+        self.assertEqual(d["lineStyle"], 2)  # dashed
+        self.assertTrue(d["axisLabelVisible"])
+        self.assertEqual(d["title"], "Average")
+        self.assertNotIn("price", d)
+
+    def test_dynamic_in_series(self):
+        from deephaven.plot.tradingview_lightweight.series import candlestick_series
+
+        table = MagicMock(name="table")
+        pl_static = price_line(price=100.0, color="gray", title="Static")
+        pl_dynamic = price_line(column="AvgPrice", color="blue", title="Average")
+
+        spec = candlestick_series(table, price_lines=[pl_static, pl_dynamic])
+        result = spec.to_dict("s0", 0)
+
+        self.assertEqual(len(result["priceLines"]), 2)
+        self.assertEqual(result["priceLines"][0]["price"], 100.0)
+        self.assertNotIn("column", result["priceLines"][0])
+        self.assertEqual(result["priceLines"][1]["column"], "AvgPrice")
+        self.assertNotIn("price", result["priceLines"][1])
+
+    def test_dynamic_price_line_all_fields_in_series(self):
+        from deephaven.plot.tradingview_lightweight.series import line_series
+
+        table = MagicMock(name="table")
+        pl = price_line(
+            column="Signal",
+            id="signal-line",
+            color="purple",
+            line_visible=False,
+            axis_label_color="purple",
+            axis_label_text_color="#FFF",
+            title="Signal",
+        )
+        spec = line_series(table, price_lines=[pl])
+        result = spec.to_dict("s0", 0)
+        pl_dict = result["priceLines"][0]
+
+        self.assertEqual(pl_dict["column"], "Signal")
+        self.assertEqual(pl_dict["id"], "signal-line")
+        self.assertEqual(pl_dict["color"], "purple")
+        self.assertFalse(pl_dict["lineVisible"])
+        self.assertEqual(pl_dict["axisLabelColor"], "purple")
+        self.assertEqual(pl_dict["axisLabelTextColor"], "#FFF")
+        self.assertEqual(pl_dict["title"], "Signal")
+        self.assertNotIn("price", pl_dict)
+
+
+class TestMarkerSpecToDict(unittest.TestCase):
+    """Tests for the updated MarkerSpec with to_dict and get_columns."""
+
+    def test_all_fixed_defaults(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, timestamp="SignalTime", text="Buy")
+        d = spec.to_dict(table_id=1)
+        self.assertEqual(d["tableId"], 1)
+        self.assertEqual(d["columns"], {"time": "SignalTime"})
+        self.assertEqual(d["defaults"]["position"], "aboveBar")
+        self.assertEqual(d["defaults"]["shape"], "circle")
+        self.assertNotIn("color", d["defaults"])
+        self.assertEqual(d["defaults"]["text"], "Buy")
+
+    def test_column_overrides(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(
+            table=table,
+            timestamp="Time",
+            text_column="Label",
+            color_column="Color",
+        )
+        d = spec.to_dict(table_id=2)
+        self.assertEqual(d["columns"]["time"], "Time")
+        self.assertEqual(d["columns"]["text"], "Label")
+        self.assertEqual(d["columns"]["color"], "Color")
+        # Defaults should not include text/color since they come from columns
+        self.assertNotIn("text", d["defaults"])
+        self.assertNotIn("color", d["defaults"])
+        # Position and shape should still be in defaults
+        self.assertEqual(d["defaults"]["position"], "aboveBar")
+        self.assertEqual(d["defaults"]["shape"], "circle")
+
+    def test_all_columns(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(
+            table=table,
+            timestamp="T",
+            position_column="Pos",
+            shape_column="Shape",
+            color_column="Col",
+            text_column="Txt",
+            size_column="Sz",
+        )
+        d = spec.to_dict(table_id=0)
+        self.assertEqual(
+            d["columns"],
+            {
+                "time": "T",
+                "position": "Pos",
+                "shape": "Shape",
+                "color": "Col",
+                "text": "Txt",
+                "size": "Sz",
+            },
+        )
+        # No defaults except possibly size (which has no default when None)
+        self.assertEqual(d["defaults"], {})
+
+    def test_position_shape_mapping(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(
+            table=table,
+            timestamp="T",
+            position="below_bar",
+            shape="arrow_up",
+        )
+        d = spec.to_dict(table_id=0)
+        self.assertEqual(d["defaults"]["position"], "belowBar")
+        self.assertEqual(d["defaults"]["shape"], "arrowUp")
+
+    def test_get_columns_time_only(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, timestamp="SignalTime")
+        self.assertEqual(spec.get_columns(), ["SignalTime"])
+
+    def test_get_columns_with_overrides(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(
+            table=table,
+            timestamp="Time",
+            text_column="Label",
+            color_column="Color",
+        )
+        cols = spec.get_columns()
+        self.assertIn("Time", cols)
+        self.assertIn("Label", cols)
+        self.assertIn("Color", cols)
+        self.assertEqual(len(cols), 3)
+
+    def test_size_in_defaults(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, timestamp="T", size=3)
+        d = spec.to_dict(table_id=0)
+        self.assertEqual(d["defaults"]["size"], 3)
+
+    def test_size_not_in_defaults_when_none(self):
+        table = MagicMock(name="table")
+        spec = MarkerSpec(table=table, timestamp="T")
+        d = spec.to_dict(table_id=0)
+        self.assertNotIn("size", d["defaults"])
+
+
+class TestMarkersFromTableUpdated(unittest.TestCase):
+    """Tests for the updated markers_from_table with *_column params."""
+
+    def test_with_text_column(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(table, timestamp="SignalTime", text_column="Label")
+        self.assertEqual(spec.timestamp, "SignalTime")
+        self.assertEqual(spec.text_column, "Label")
+        self.assertIsNone(spec.position_column)
+
+    def test_with_all_columns(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(
+            table,
+            timestamp="T",
+            position_column="Pos",
+            shape_column="Shape",
+            color_column="Col",
+            text_column="Txt",
+            size_column="Sz",
+        )
+        self.assertEqual(spec.position_column, "Pos")
+        self.assertEqual(spec.shape_column, "Shape")
+        self.assertEqual(spec.color_column, "Col")
+        self.assertEqual(spec.text_column, "Txt")
+        self.assertEqual(spec.size_column, "Sz")
+
+    def test_mixed_fixed_and_columns(self):
+        table = MagicMock(name="table")
+        spec = markers_from_table(
+            table,
+            timestamp="T",
+            text_column="Label",
+            position="below_bar",
+            color="#FF0000",
+        )
+        d = spec.to_dict(table_id=1)
+        self.assertEqual(d["columns"]["text"], "Label")
+        self.assertEqual(d["defaults"]["position"], "belowBar")
+        self.assertEqual(d["defaults"]["color"], "#FF0000")
+
+
+class TestMarkerSpecInSeries(unittest.TestCase):
+    """Tests for marker_spec integration in series and chart."""
+
+    def test_marker_spec_in_candlestick_series(self):
+        from deephaven.plot.tradingview_lightweight.series import candlestick_series
+
+        table = MagicMock(name="data")
+        marker_table = MagicMock(name="markers")
+        ms = MarkerSpec(table=marker_table, timestamp="SignalTime", text="Buy")
+
+        spec = candlestick_series(table, marker_spec=ms)
+        self.assertIs(spec.marker_spec, ms)
+
+    def test_marker_spec_serialized_in_to_dict(self):
+        from deephaven.plot.tradingview_lightweight.series import line_series
+
+        table = MagicMock(name="data")
+        marker_table = MagicMock(name="markers")
+        ms = MarkerSpec(table=marker_table, timestamp="T", text_column="Lbl")
+
+        spec = line_series(table, marker_spec=ms)
+        result = spec.to_dict("s0", 0, marker_table_id=1)
+
+        self.assertIn("markerSpec", result)
+        self.assertEqual(result["markerSpec"]["tableId"], 1)
+        self.assertEqual(result["markerSpec"]["columns"]["time"], "T")
+        self.assertEqual(result["markerSpec"]["columns"]["text"], "Lbl")
+
+    def test_marker_spec_not_serialized_without_table_id(self):
+        from deephaven.plot.tradingview_lightweight.series import line_series
+
+        table = MagicMock(name="data")
+        marker_table = MagicMock(name="markers")
+        ms = MarkerSpec(table=marker_table, timestamp="T")
+
+        spec = line_series(table, marker_spec=ms)
+        result = spec.to_dict("s0", 0)  # no marker_table_id
+        self.assertNotIn("markerSpec", result)
+
+    def test_all_series_types_accept_marker_spec(self):
+        from deephaven.plot.tradingview_lightweight.series import (
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        )
+
+        table = MagicMock(name="data")
+        marker_table = MagicMock(name="markers")
+        ms = MarkerSpec(table=marker_table, timestamp="T")
+
+        for fn in (
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ):
+            spec = fn(table, marker_spec=ms)
+            self.assertIs(spec.marker_spec, ms)
+
+    def test_chart_get_tables_includes_marker_table(self):
+        from deephaven.plot.tradingview_lightweight.series import line_series
+        from deephaven.plot.tradingview_lightweight.chart import TvlChart
+
+        data = MagicMock(name="data")
+        marker_table = MagicMock(name="markers")
+        ms = MarkerSpec(table=marker_table, timestamp="T")
+        s = line_series(data, marker_spec=ms)
+        c = TvlChart([s], {})
+        tables = c.get_tables()
+        self.assertIn(data, tables)
+        self.assertIn(marker_table, tables)
+        self.assertEqual(len(tables), 2)
+
+    def test_chart_to_dict_includes_marker_spec(self):
+        from deephaven.plot.tradingview_lightweight.series import line_series
+        from deephaven.plot.tradingview_lightweight.chart import TvlChart
+
+        data = MagicMock(name="data")
+        marker_table = MagicMock(name="markers")
+        ms = MarkerSpec(table=marker_table, timestamp="T", text="Signal")
+        s = line_series(data, marker_spec=ms)
+        c = TvlChart([s], {})
+        table_id_map = {id(data): 0, id(marker_table): 1}
+        d = c.to_dict(table_id_map)
+        self.assertIn("markerSpec", d["series"][0])
+        self.assertEqual(d["series"][0]["markerSpec"]["tableId"], 1)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_series.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_series.py
new file mode 100644
index 000000000..91674a395
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_series.py
@@ -0,0 +1,1290 @@
+"""Tests for series creation functions."""
+
+from __future__ import annotations
+
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock
+
+# Add src to path for namespace package resolution
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight.series import (
+    SeriesSpec,
+    candlestick_series,
+    bar_series,
+    line_series,
+    area_series,
+    baseline_series,
+    histogram_series,
+)
+from deephaven.plot.tradingview_lightweight.markers import Marker, PriceLine
+
+
+class TestCandlestickSeries(unittest.TestCase):
+    """Tests for candlestick_series()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        spec = candlestick_series(self.table)
+        self.assertEqual(spec.series_type, "Candlestick")
+        self.assertIs(spec.table, self.table)
+        self.assertEqual(
+            spec.column_mapping,
+            {
+                "time": "Timestamp",
+                "open": "Open",
+                "high": "High",
+                "low": "Low",
+                "close": "Close",
+            },
+        )
+        # No optional style options set, so options dict should be empty
+        self.assertEqual(spec.options, {})
+        self.assertIsNone(spec.markers)
+        self.assertIsNone(spec.price_lines)
+
+    def test_custom_columns(self):
+        spec = candlestick_series(
+            self.table,
+            timestamp="ts",
+            open="o",
+            high="h",
+            low="l",
+            close="c",
+        )
+        self.assertEqual(
+            spec.column_mapping,
+            {"time": "ts", "open": "o", "high": "h", "low": "l", "close": "c"},
+        )
+
+    def test_style_options(self):
+        spec = candlestick_series(
+            self.table,
+            up_color="#00ff00",
+            down_color="#ff0000",
+            border_up_color="#008800",
+            border_down_color="#880000",
+            wick_up_color="#004400",
+            wick_down_color="#440000",
+            border_visible=False,
+            wick_visible=True,
+            title="AAPL",
+            visible=True,
+            price_scale_id="right",
+        )
+        self.assertEqual(spec.options["upColor"], "#00ff00")
+        self.assertEqual(spec.options["downColor"], "#ff0000")
+        self.assertEqual(spec.options["borderUpColor"], "#008800")
+        self.assertEqual(spec.options["borderDownColor"], "#880000")
+        self.assertEqual(spec.options["wickUpColor"], "#004400")
+        self.assertEqual(spec.options["wickDownColor"], "#440000")
+        self.assertFalse(spec.options["borderVisible"])
+        self.assertTrue(spec.options["wickVisible"])
+        self.assertEqual(spec.options["title"], "AAPL")
+        self.assertTrue(spec.options["visible"])
+        self.assertEqual(spec.options["priceScaleId"], "right")
+
+    def test_none_options_filtered(self):
+        """Options that are None should not appear in the dict."""
+        spec = candlestick_series(self.table, up_color="#00ff00")
+        self.assertIn("upColor", spec.options)
+        self.assertNotIn("downColor", spec.options)
+        self.assertNotIn("borderUpColor", spec.options)
+        self.assertNotIn("title", spec.options)
+
+    def test_with_markers_and_price_lines(self):
+        m = Marker(time="2024-01-01", color="#fff")
+        pl = PriceLine(price=100.0, color="red")
+        spec = candlestick_series(self.table, markers=[m], price_lines=[pl])
+        self.assertEqual(spec.markers, [m])
+        self.assertEqual(spec.price_lines, [pl])
+
+    def test_to_dict(self):
+        m = Marker(time="2024-01-01", color="#fff")
+        pl = PriceLine(price=50.0, title="Support")
+        spec = candlestick_series(
+            self.table,
+            up_color="#0f0",
+            title="My Series",
+            markers=[m],
+            price_lines=[pl],
+        )
+        result = spec.to_dict("series_0", 42)
+        self.assertEqual(result["id"], "series_0")
+        self.assertEqual(result["type"], "Candlestick")
+        self.assertEqual(result["options"]["upColor"], "#0f0")
+        self.assertEqual(result["options"]["title"], "My Series")
+        self.assertEqual(result["dataMapping"]["tableId"], 42)
+        self.assertEqual(result["dataMapping"]["columns"]["time"], "Timestamp")
+        self.assertEqual(len(result["markers"]), 1)
+        self.assertEqual(result["markers"][0]["time"], "2024-01-01")
+        self.assertEqual(len(result["priceLines"]), 1)
+        self.assertEqual(result["priceLines"][0]["price"], 50.0)
+
+    def test_to_dict_no_markers(self):
+        """When no markers/price_lines, those keys should be absent."""
+        spec = candlestick_series(self.table)
+        result = spec.to_dict("s0", 0)
+        self.assertNotIn("markers", result)
+        self.assertNotIn("priceLines", result)
+
+    def test_price_format(self):
+        # minMove (camelCase) is the correct key -- matches TVL JS API
+        pf = {"type": "price", "precision": 4, "minMove": 0.0001}
+        spec = candlestick_series(self.table, price_format=pf)
+        self.assertEqual(spec.options["priceFormat"]["minMove"], 0.0001)
+        self.assertEqual(spec.options["priceFormat"]["precision"], 4)
+        # min_move (old snake_case key) must NOT appear
+        self.assertNotIn("min_move", spec.options["priceFormat"])
+
+    def test_border_color(self):
+        spec = candlestick_series(self.table, border_color="#378658")
+        self.assertEqual(spec.options["borderColor"], "#378658")
+
+    def test_wick_color(self):
+        spec = candlestick_series(self.table, wick_color="#737375")
+        self.assertEqual(spec.options["wickColor"], "#737375")
+
+    def test_border_color_not_present_when_none(self):
+        spec = candlestick_series(self.table)
+        self.assertNotIn("borderColor", spec.options)
+
+    def test_wick_color_not_present_when_none(self):
+        spec = candlestick_series(self.table)
+        self.assertNotIn("wickColor", spec.options)
+
+    def test_generic_and_directional_colors_together(self):
+        """Generic and directional colors can coexist -- JS resolves precedence."""
+        spec = candlestick_series(
+            self.table,
+            border_color="#111",
+            border_up_color="#00ff00",
+            border_down_color="#ff0000",
+            wick_color="#555",
+            wick_up_color="#008800",
+            wick_down_color="#880000",
+        )
+        self.assertEqual(spec.options["borderColor"], "#111")
+        self.assertEqual(spec.options["borderUpColor"], "#00ff00")
+        self.assertEqual(spec.options["borderDownColor"], "#ff0000")
+        self.assertEqual(spec.options["wickColor"], "#555")
+        self.assertEqual(spec.options["wickUpColor"], "#008800")
+        self.assertEqual(spec.options["wickDownColor"], "#880000")
+
+
+class TestBarSeries(unittest.TestCase):
+    """Tests for bar_series()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        spec = bar_series(self.table)
+        self.assertEqual(spec.series_type, "Bar")
+        self.assertEqual(
+            spec.column_mapping,
+            {
+                "time": "Timestamp",
+                "open": "Open",
+                "high": "High",
+                "low": "Low",
+                "close": "Close",
+            },
+        )
+        self.assertEqual(spec.options, {})
+
+    def test_custom_params(self):
+        spec = bar_series(
+            self.table,
+            timestamp="Date",
+            open="O",
+            high="H",
+            low="L",
+            close="C",
+            up_color="green",
+            down_color="red",
+            open_visible=False,
+            thin_bars=True,
+            title="BARS",
+        )
+        self.assertEqual(spec.column_mapping["time"], "Date")
+        self.assertEqual(spec.options["upColor"], "green")
+        self.assertEqual(spec.options["downColor"], "red")
+        self.assertFalse(spec.options["openVisible"])
+        self.assertTrue(spec.options["thinBars"])
+        self.assertEqual(spec.options["title"], "BARS")
+
+    def test_to_dict(self):
+        spec = bar_series(self.table, up_color="green")
+        result = spec.to_dict("series_1", 7)
+        self.assertEqual(result["type"], "Bar")
+        self.assertEqual(result["dataMapping"]["tableId"], 7)
+        self.assertEqual(result["options"]["upColor"], "green")
+
+
+class TestLineSeries(unittest.TestCase):
+    """Tests for line_series()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        spec = line_series(self.table)
+        self.assertEqual(spec.series_type, "Line")
+        self.assertEqual(spec.column_mapping, {"time": "Timestamp", "value": "Value"})
+        self.assertEqual(spec.options, {})
+
+    def test_custom_params(self):
+        spec = line_series(
+            self.table,
+            timestamp="ts",
+            value="price",
+            color="blue",
+            line_width=3,
+            title="Price Line",
+            visible=False,
+            crosshair_marker_visible=True,
+            crosshair_marker_radius=5.0,
+            price_scale_id="left",
+        )
+        self.assertEqual(spec.column_mapping, {"time": "ts", "value": "price"})
+        self.assertEqual(spec.options["color"], "blue")
+        self.assertEqual(spec.options["lineWidth"], 3)
+        self.assertEqual(spec.options["title"], "Price Line")
+        self.assertFalse(spec.options["visible"])
+        self.assertTrue(spec.options["crosshairMarkerVisible"])
+        self.assertEqual(spec.options["crosshairMarkerRadius"], 5.0)
+        self.assertEqual(spec.options["priceScaleId"], "left")
+
+    def test_line_style_conversion(self):
+        """Line style enum strings should be converted to integers."""
+        spec = line_series(self.table, line_style="dashed")
+        self.assertEqual(spec.options["lineStyle"], 2)
+
+        spec2 = line_series(self.table, line_style="solid")
+        self.assertEqual(spec2.options["lineStyle"], 0)
+
+        spec3 = line_series(self.table, line_style="dotted")
+        self.assertEqual(spec3.options["lineStyle"], 1)
+
+        spec4 = line_series(self.table, line_style="large_dashed")
+        self.assertEqual(spec4.options["lineStyle"], 3)
+
+        spec5 = line_series(self.table, line_style="sparse_dotted")
+        self.assertEqual(spec5.options["lineStyle"], 4)
+
+    def test_line_type_conversion(self):
+        """Line type enum strings should be converted to integers."""
+        spec = line_series(self.table, line_type="simple")
+        self.assertEqual(spec.options["lineType"], 0)
+
+        spec2 = line_series(self.table, line_type="with_steps")
+        self.assertEqual(spec2.options["lineType"], 1)
+
+        spec3 = line_series(self.table, line_type="curved")
+        self.assertEqual(spec3.options["lineType"], 2)
+
+    def test_no_style_when_none(self):
+        """lineStyle/lineType should not be in options when not specified."""
+        spec = line_series(self.table)
+        self.assertNotIn("lineStyle", spec.options)
+        self.assertNotIn("lineType", spec.options)
+
+    def test_to_dict(self):
+        spec = line_series(self.table, color="red", line_width=2)
+        result = spec.to_dict("series_2", 10)
+        self.assertEqual(result["type"], "Line")
+        self.assertEqual(
+            result["dataMapping"]["columns"], {"time": "Timestamp", "value": "Value"}
+        )
+        self.assertEqual(result["options"]["color"], "red")
+        self.assertEqual(result["options"]["lineWidth"], 2)
+
+
+class TestAreaSeries(unittest.TestCase):
+    """Tests for area_series()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        spec = area_series(self.table)
+        self.assertEqual(spec.series_type, "Area")
+        self.assertEqual(spec.column_mapping, {"time": "Timestamp", "value": "Value"})
+        self.assertEqual(spec.options, {})
+
+    def test_custom_params(self):
+        spec = area_series(
+            self.table,
+            timestamp="date",
+            value="vol",
+            line_color="#0000ff",
+            top_color="rgba(0,0,255,0.4)",
+            bottom_color="rgba(0,0,255,0.0)",
+            line_width=2,
+            line_style="dashed",
+            line_type="curved",
+            crosshair_marker_visible=False,
+            title="Volume Area",
+        )
+        self.assertEqual(spec.options["lineColor"], "#0000ff")
+        self.assertEqual(spec.options["topColor"], "rgba(0,0,255,0.4)")
+        self.assertEqual(spec.options["bottomColor"], "rgba(0,0,255,0.0)")
+        self.assertEqual(spec.options["lineWidth"], 2)
+        self.assertEqual(spec.options["lineStyle"], 2)  # dashed
+        self.assertEqual(spec.options["lineType"], 2)  # curved
+        self.assertFalse(spec.options["crosshairMarkerVisible"])
+        self.assertEqual(spec.options["title"], "Volume Area")
+
+    def test_relative_gradient(self):
+        spec = area_series(self.table, relative_gradient=True)
+        self.assertTrue(spec.options["relativeGradient"])
+
+    def test_relative_gradient_false(self):
+        spec = area_series(self.table, relative_gradient=False)
+        self.assertFalse(spec.options["relativeGradient"])
+
+    def test_invert_filled_area(self):
+        spec = area_series(self.table, invert_filled_area=True)
+        self.assertTrue(spec.options["invertFilledArea"])
+
+    def test_relative_gradient_not_present_when_none(self):
+        spec = area_series(self.table)
+        self.assertNotIn("relativeGradient", spec.options)
+        self.assertNotIn("invertFilledArea", spec.options)
+
+    def test_to_dict(self):
+        spec = area_series(self.table, top_color="blue")
+        result = spec.to_dict("area_0", 3)
+        self.assertEqual(result["type"], "Area")
+        self.assertEqual(result["options"]["topColor"], "blue")
+
+
+class TestBaselineSeries(unittest.TestCase):
+    """Tests for baseline_series()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        spec = baseline_series(self.table)
+        self.assertEqual(spec.series_type, "Baseline")
+        self.assertEqual(spec.column_mapping, {"time": "Timestamp", "value": "Value"})
+        # base_value defaults to None — omitted when not set
+        self.assertNotIn("baseValue", spec.options)
+
+    def test_custom_params(self):
+        spec = baseline_series(
+            self.table,
+            base_value=100.0,
+            top_line_color="green",
+            top_fill_color1="rgba(0,255,0,0.4)",
+            top_fill_color2="rgba(0,255,0,0.0)",
+            bottom_line_color="red",
+            bottom_fill_color1="rgba(255,0,0,0.4)",
+            bottom_fill_color2="rgba(255,0,0,0.0)",
+            line_width=2,
+            line_style="dotted",
+            title="Baseline Chart",
+        )
+        self.assertEqual(spec.options["baseValue"], {"type": "price", "price": 100.0})
+        self.assertEqual(spec.options["topLineColor"], "green")
+        self.assertEqual(spec.options["topFillColor1"], "rgba(0,255,0,0.4)")
+        self.assertEqual(spec.options["topFillColor2"], "rgba(0,255,0,0.0)")
+        self.assertEqual(spec.options["bottomLineColor"], "red")
+        self.assertEqual(spec.options["bottomFillColor1"], "rgba(255,0,0,0.4)")
+        self.assertEqual(spec.options["bottomFillColor2"], "rgba(255,0,0,0.0)")
+        self.assertEqual(spec.options["lineWidth"], 2)
+        self.assertEqual(spec.options["lineStyle"], 1)  # dotted
+        self.assertEqual(spec.options["title"], "Baseline Chart")
+
+    def test_base_value_structure(self):
+        """base_value should always be wrapped in a type/price dict."""
+        spec = baseline_series(self.table, base_value=50.5)
+        bv = spec.options["baseValue"]
+        self.assertEqual(bv["type"], "price")
+        self.assertEqual(bv["price"], 50.5)
+
+    def test_line_type_simple(self):
+        spec = baseline_series(self.table, line_type="simple")
+        self.assertEqual(spec.options["lineType"], 0)
+
+    def test_line_type_with_steps(self):
+        spec = baseline_series(self.table, line_type="with_steps")
+        self.assertEqual(spec.options["lineType"], 1)
+
+    def test_line_type_curved(self):
+        spec = baseline_series(self.table, line_type="curved")
+        self.assertEqual(spec.options["lineType"], 2)
+
+    def test_line_type_not_present_when_none(self):
+        spec = baseline_series(self.table)
+        self.assertNotIn("lineType", spec.options)
+
+    def test_relative_gradient(self):
+        spec = baseline_series(self.table, relative_gradient=True)
+        self.assertTrue(spec.options["relativeGradient"])
+
+    def test_relative_gradient_not_present_when_none(self):
+        spec = baseline_series(self.table)
+        self.assertNotIn("relativeGradient", spec.options)
+
+    def test_to_dict(self):
+        spec = baseline_series(self.table, base_value=25.0, title="BL")
+        result = spec.to_dict("bl_0", 5)
+        self.assertEqual(result["type"], "Baseline")
+        self.assertEqual(result["options"]["baseValue"]["price"], 25.0)
+        self.assertEqual(result["options"]["title"], "BL")
+
+
+class TestHistogramSeries(unittest.TestCase):
+    """Tests for histogram_series()."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_defaults(self):
+        spec = histogram_series(self.table)
+        self.assertEqual(spec.series_type, "Histogram")
+        self.assertEqual(spec.column_mapping, {"time": "Timestamp", "value": "Value"})
+        self.assertEqual(spec.options, {})
+
+    def test_custom_params(self):
+        spec = histogram_series(
+            self.table,
+            timestamp="Date",
+            value="Volume",
+            color="rgba(0,150,136,0.8)",
+            title="Volume",
+        )
+        self.assertEqual(spec.column_mapping, {"time": "Date", "value": "Volume"})
+        self.assertEqual(spec.options["color"], "rgba(0,150,136,0.8)")
+        self.assertEqual(spec.options["title"], "Volume")
+
+    def test_color_column(self):
+        """color_column should add 'color' to column_mapping."""
+        spec = histogram_series(self.table, color_column="BarColor")
+        self.assertIn("color", spec.column_mapping)
+        self.assertEqual(spec.column_mapping["color"], "BarColor")
+
+    def test_no_color_column_by_default(self):
+        """Without color_column, 'color' should not be in column_mapping."""
+        spec = histogram_series(self.table)
+        self.assertNotIn("color", spec.column_mapping)
+
+    def test_base_zero(self):
+        spec = histogram_series(self.table, base=0.0)
+        self.assertEqual(spec.options["base"], 0.0)
+
+    def test_base_positive(self):
+        spec = histogram_series(self.table, base=100.0)
+        self.assertEqual(spec.options["base"], 100.0)
+
+    def test_base_negative(self):
+        spec = histogram_series(self.table, base=-50.5)
+        self.assertEqual(spec.options["base"], -50.5)
+
+    def test_base_not_present_when_none(self):
+        spec = histogram_series(self.table)
+        self.assertNotIn("base", spec.options)
+
+    def test_to_dict(self):
+        spec = histogram_series(self.table, color="#ff0000", color_column="Clr")
+        result = spec.to_dict("hist_0", 99)
+        self.assertEqual(result["type"], "Histogram")
+        self.assertEqual(result["options"]["color"], "#ff0000")
+        self.assertEqual(result["dataMapping"]["columns"]["color"], "Clr")
+
+
+class TestSeriesSpecDataclass(unittest.TestCase):
+    """Tests for the SeriesSpec dataclass directly."""
+
+    def test_to_dict_basic(self):
+        table = MagicMock(name="table")
+        spec = SeriesSpec(
+            series_type="Line",
+            table=table,
+            column_mapping={"time": "ts", "value": "val"},
+            options={"color": "blue"},
+        )
+        result = spec.to_dict("test_id", 0)
+        self.assertEqual(result["id"], "test_id")
+        self.assertEqual(result["type"], "Line")
+        self.assertEqual(result["options"], {"color": "blue"})
+        self.assertEqual(result["dataMapping"]["tableId"], 0)
+        self.assertEqual(
+            result["dataMapping"]["columns"], {"time": "ts", "value": "val"}
+        )
+        self.assertNotIn("markers", result)
+        self.assertNotIn("priceLines", result)
+
+    def test_to_dict_with_markers_and_price_lines(self):
+        table = MagicMock(name="table")
+        m1 = Marker(time="2024-01-01", text="Buy")
+        m2 = Marker(time="2024-02-01", text="Sell")
+        pl = PriceLine(price=150.0, color="red", title="Resistance")
+        spec = SeriesSpec(
+            series_type="Line",
+            table=table,
+            column_mapping={"time": "ts", "value": "val"},
+            options={},
+            markers=[m1, m2],
+            price_lines=[pl],
+        )
+        result = spec.to_dict("s1", 1)
+        self.assertEqual(len(result["markers"]), 2)
+        self.assertEqual(result["markers"][0]["text"], "Buy")
+        self.assertEqual(result["markers"][1]["text"], "Sell")
+        self.assertEqual(len(result["priceLines"]), 1)
+        self.assertEqual(result["priceLines"][0]["price"], 150.0)
+        self.assertEqual(result["priceLines"][0]["color"], "red")
+        self.assertEqual(result["priceLines"][0]["title"], "Resistance")
+
+    def test_empty_markers_list_excluded(self):
+        """An empty markers list should still be excluded (falsy)."""
+        table = MagicMock(name="table")
+        spec = SeriesSpec(
+            series_type="Line",
+            table=table,
+            column_mapping={"time": "ts", "value": "val"},
+            markers=[],
+            price_lines=[],
+        )
+        result = spec.to_dict("s0", 0)
+        self.assertNotIn("markers", result)
+        self.assertNotIn("priceLines", result)
+
+
+class TestLastValueVisible(unittest.TestCase):
+    """lastValueVisible should work on all series types."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_candlestick(self):
+        spec = candlestick_series(self.table, last_value_visible=False)
+        self.assertFalse(spec.options["lastValueVisible"])
+
+    def test_bar(self):
+        spec = bar_series(self.table, last_value_visible=False)
+        self.assertFalse(spec.options["lastValueVisible"])
+
+    def test_line(self):
+        spec = line_series(self.table, last_value_visible=False)
+        self.assertFalse(spec.options["lastValueVisible"])
+
+    def test_area(self):
+        spec = area_series(self.table, last_value_visible=False)
+        self.assertFalse(spec.options["lastValueVisible"])
+
+    def test_baseline(self):
+        spec = baseline_series(self.table, last_value_visible=False)
+        self.assertFalse(spec.options["lastValueVisible"])
+
+    def test_histogram(self):
+        spec = histogram_series(self.table, last_value_visible=False)
+        self.assertFalse(spec.options["lastValueVisible"])
+
+    def test_not_present_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("lastValueVisible", spec.options)
+
+
+class TestCrosshairMarkerOnAreaAndBaseline(unittest.TestCase):
+    """crosshairMarkerRadius should work on area and baseline series."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_area_crosshair_marker_radius(self):
+        spec = area_series(self.table, crosshair_marker_radius=5.0)
+        self.assertEqual(spec.options["crosshairMarkerRadius"], 5.0)
+
+    def test_baseline_crosshair_marker_visible(self):
+        spec = baseline_series(self.table, crosshair_marker_visible=False)
+        self.assertFalse(spec.options["crosshairMarkerVisible"])
+
+    def test_baseline_crosshair_marker_radius(self):
+        spec = baseline_series(self.table, crosshair_marker_radius=3.0)
+        self.assertEqual(spec.options["crosshairMarkerRadius"], 3.0)
+
+
+class TestPerDatapointColor(unittest.TestCase):
+    """Per-datapoint color columns on OHLC series."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_candlestick_color_column(self):
+        spec = candlestick_series(self.table, color_column="BarColor")
+        self.assertEqual(spec.column_mapping["color"], "BarColor")
+
+    def test_candlestick_border_color_column(self):
+        spec = candlestick_series(self.table, border_color_column="BorderClr")
+        self.assertEqual(spec.column_mapping["borderColor"], "BorderClr")
+
+    def test_candlestick_wick_color_column(self):
+        spec = candlestick_series(self.table, wick_color_column="WickClr")
+        self.assertEqual(spec.column_mapping["wickColor"], "WickClr")
+
+    def test_candlestick_no_color_columns_by_default(self):
+        spec = candlestick_series(self.table)
+        self.assertNotIn("color", spec.column_mapping)
+        self.assertNotIn("borderColor", spec.column_mapping)
+        self.assertNotIn("wickColor", spec.column_mapping)
+
+    def test_bar_color_column(self):
+        spec = bar_series(self.table, color_column="Clr")
+        self.assertEqual(spec.column_mapping["color"], "Clr")
+
+    def test_bar_no_color_column_by_default(self):
+        spec = bar_series(self.table)
+        self.assertNotIn("color", spec.column_mapping)
+
+    # --- Line series per-point color ---
+
+    def test_line_color_column(self):
+        spec = line_series(self.table, color_column="PointColor")
+        self.assertEqual(spec.column_mapping["color"], "PointColor")
+
+    def test_line_no_color_column_by_default(self):
+        spec = line_series(self.table)
+        self.assertNotIn("color", spec.column_mapping)
+
+    def test_line_color_column_in_to_dict(self):
+        spec = line_series(self.table, color_column="Clr")
+        result = spec.to_dict("s0", 0)
+        self.assertEqual(result["dataMapping"]["columns"]["color"], "Clr")
+
+    # --- Area series per-point color ---
+
+    def test_area_line_color_column(self):
+        spec = area_series(self.table, line_color_column="LineClr")
+        self.assertEqual(spec.column_mapping["lineColor"], "LineClr")
+
+    def test_area_top_color_column(self):
+        spec = area_series(self.table, top_color_column="TopClr")
+        self.assertEqual(spec.column_mapping["topColor"], "TopClr")
+
+    def test_area_bottom_color_column(self):
+        spec = area_series(self.table, bottom_color_column="BotClr")
+        self.assertEqual(spec.column_mapping["bottomColor"], "BotClr")
+
+    def test_area_no_color_columns_by_default(self):
+        spec = area_series(self.table)
+        self.assertNotIn("lineColor", spec.column_mapping)
+        self.assertNotIn("topColor", spec.column_mapping)
+        self.assertNotIn("bottomColor", spec.column_mapping)
+
+    def test_area_all_color_columns(self):
+        spec = area_series(
+            self.table,
+            line_color_column="LC",
+            top_color_column="TC",
+            bottom_color_column="BC",
+        )
+        self.assertEqual(spec.column_mapping["lineColor"], "LC")
+        self.assertEqual(spec.column_mapping["topColor"], "TC")
+        self.assertEqual(spec.column_mapping["bottomColor"], "BC")
+
+    def test_area_color_columns_in_to_dict(self):
+        spec = area_series(
+            self.table,
+            line_color_column="LC",
+            top_color_column="TC",
+            bottom_color_column="BC",
+        )
+        result = spec.to_dict("a0", 1)
+        cols = result["dataMapping"]["columns"]
+        self.assertEqual(cols["lineColor"], "LC")
+        self.assertEqual(cols["topColor"], "TC")
+        self.assertEqual(cols["bottomColor"], "BC")
+
+    # --- Baseline series per-point color ---
+
+    def test_baseline_top_line_color_column(self):
+        spec = baseline_series(self.table, top_line_color_column="TLC")
+        self.assertEqual(spec.column_mapping["topLineColor"], "TLC")
+
+    def test_baseline_top_fill_color1_column(self):
+        spec = baseline_series(self.table, top_fill_color1_column="TFC1")
+        self.assertEqual(spec.column_mapping["topFillColor1"], "TFC1")
+
+    def test_baseline_top_fill_color2_column(self):
+        spec = baseline_series(self.table, top_fill_color2_column="TFC2")
+        self.assertEqual(spec.column_mapping["topFillColor2"], "TFC2")
+
+    def test_baseline_bottom_line_color_column(self):
+        spec = baseline_series(self.table, bottom_line_color_column="BLC")
+        self.assertEqual(spec.column_mapping["bottomLineColor"], "BLC")
+
+    def test_baseline_bottom_fill_color1_column(self):
+        spec = baseline_series(self.table, bottom_fill_color1_column="BFC1")
+        self.assertEqual(spec.column_mapping["bottomFillColor1"], "BFC1")
+
+    def test_baseline_bottom_fill_color2_column(self):
+        spec = baseline_series(self.table, bottom_fill_color2_column="BFC2")
+        self.assertEqual(spec.column_mapping["bottomFillColor2"], "BFC2")
+
+    def test_baseline_no_color_columns_by_default(self):
+        spec = baseline_series(self.table)
+        self.assertNotIn("topLineColor", spec.column_mapping)
+        self.assertNotIn("topFillColor1", spec.column_mapping)
+        self.assertNotIn("topFillColor2", spec.column_mapping)
+        self.assertNotIn("bottomLineColor", spec.column_mapping)
+        self.assertNotIn("bottomFillColor1", spec.column_mapping)
+        self.assertNotIn("bottomFillColor2", spec.column_mapping)
+
+    def test_baseline_all_color_columns(self):
+        spec = baseline_series(
+            self.table,
+            top_line_color_column="TLC",
+            top_fill_color1_column="TFC1",
+            top_fill_color2_column="TFC2",
+            bottom_line_color_column="BLC",
+            bottom_fill_color1_column="BFC1",
+            bottom_fill_color2_column="BFC2",
+        )
+        self.assertEqual(spec.column_mapping["topLineColor"], "TLC")
+        self.assertEqual(spec.column_mapping["topFillColor1"], "TFC1")
+        self.assertEqual(spec.column_mapping["topFillColor2"], "TFC2")
+        self.assertEqual(spec.column_mapping["bottomLineColor"], "BLC")
+        self.assertEqual(spec.column_mapping["bottomFillColor1"], "BFC1")
+        self.assertEqual(spec.column_mapping["bottomFillColor2"], "BFC2")
+
+    def test_baseline_color_columns_in_to_dict(self):
+        spec = baseline_series(
+            self.table,
+            top_line_color_column="TLC",
+            bottom_fill_color2_column="BFC2",
+        )
+        result = spec.to_dict("bl0", 2)
+        cols = result["dataMapping"]["columns"]
+        self.assertEqual(cols["topLineColor"], "TLC")
+        self.assertEqual(cols["bottomFillColor2"], "BFC2")
+        # Others should not be present
+        self.assertNotIn("topFillColor1", cols)
+        self.assertNotIn("bottomLineColor", cols)
+
+
+class TestPriceScaleOptions(unittest.TestCase):
+    """Per-series priceScaleOptions (autoScale, scaleMargins)."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_auto_scale(self):
+        spec = line_series(self.table, auto_scale=False)
+        self.assertFalse(spec.price_scale_options["autoScale"])
+
+    def test_scale_margins(self):
+        spec = line_series(self.table, scale_margin_top=0.1, scale_margin_bottom=0.2)
+        self.assertEqual(spec.price_scale_options["scaleMargins"]["top"], 0.1)
+        self.assertEqual(spec.price_scale_options["scaleMargins"]["bottom"], 0.2)
+
+    def test_combined(self):
+        spec = candlestick_series(
+            self.table, auto_scale=False, scale_margin_top=0.1, scale_margin_bottom=0.3
+        )
+        self.assertFalse(spec.price_scale_options["autoScale"])
+        self.assertEqual(spec.price_scale_options["scaleMargins"]["top"], 0.1)
+        self.assertEqual(spec.price_scale_options["scaleMargins"]["bottom"], 0.3)
+
+    def test_empty_by_default(self):
+        spec = line_series(self.table)
+        self.assertEqual(spec.price_scale_options, {})
+
+    def test_to_dict_includes_price_scale_options(self):
+        spec = line_series(self.table, auto_scale=False, scale_margin_top=0.1)
+        result = spec.to_dict("s0", 0)
+        self.assertIn("priceScaleOptions", result)
+        self.assertFalse(result["priceScaleOptions"]["autoScale"])
+
+    def test_to_dict_excludes_empty_price_scale_options(self):
+        spec = line_series(self.table)
+        result = spec.to_dict("s0", 0)
+        self.assertNotIn("priceScaleOptions", result)
+
+    def test_all_series_types(self):
+        """All series types should support price scale options."""
+        for fn in [
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ]:
+            spec = fn(self.table, scale_margin_top=0.2)
+            self.assertEqual(spec.price_scale_options["scaleMargins"]["top"], 0.2)
+
+
+class TestPaneParameter(unittest.TestCase):
+    """Tests for per-series pane parameter."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_pane_on_line_series(self):
+        spec = line_series(self.table, pane=1)
+        self.assertEqual(spec.pane, 1)
+
+    def test_pane_on_histogram_series(self):
+        spec = histogram_series(self.table, pane=2)
+        self.assertEqual(spec.pane, 2)
+
+    def test_pane_default_is_none(self):
+        spec = line_series(self.table)
+        self.assertIsNone(spec.pane)
+
+    def test_to_dict_includes_pane_index(self):
+        spec = line_series(self.table, pane=1)
+        result = spec.to_dict("s0", 0)
+        self.assertEqual(result["paneIndex"], 1)
+
+    def test_to_dict_excludes_pane_index_when_none(self):
+        spec = line_series(self.table)
+        result = spec.to_dict("s0", 0)
+        self.assertNotIn("paneIndex", result)
+
+    def test_pane_zero(self):
+        """pane=0 (main pane) should still be serialized."""
+        spec = candlestick_series(self.table, pane=0)
+        result = spec.to_dict("s0", 0)
+        self.assertEqual(result["paneIndex"], 0)
+
+    def test_all_series_types_support_pane(self):
+        """All series types should accept the pane parameter."""
+        for fn in [
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ]:
+            spec = fn(self.table, pane=1)
+            self.assertEqual(spec.pane, 1)
+
+
+class TestExtendedPriceScaleOptions(unittest.TestCase):
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_new_scale_options_on_line_series(self):
+        spec = line_series(
+            self.table,
+            scale_mode="logarithmic",
+            scale_invert=True,
+            scale_align_labels=False,
+            scale_border_visible=False,
+            scale_border_color="#333",
+            scale_text_color="#FF0000",
+            scale_entire_text_only=True,
+            scale_visible=False,
+            scale_ticks_visible=True,
+            scale_minimum_width=80,
+            scale_ensure_edge_tick_marks_visible=True,
+        )
+        pso = spec.price_scale_options
+        self.assertEqual(pso["mode"], 1)  # logarithmic = 1
+        self.assertTrue(pso["invertScale"])
+        self.assertFalse(pso["alignLabels"])
+        self.assertFalse(pso["borderVisible"])
+        self.assertEqual(pso["borderColor"], "#333")
+        self.assertEqual(pso["textColor"], "#FF0000")
+        self.assertTrue(pso["entireTextOnly"])
+        self.assertFalse(pso["visible"])
+        self.assertTrue(pso["ticksVisible"])
+        self.assertEqual(pso["minimumWidth"], 80)
+        self.assertTrue(pso["ensureEdgeTickMarksVisible"])
+
+    def test_all_series_types_support_new_scale_options(self):
+        for fn in [
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ]:
+            spec = fn(self.table, scale_ticks_visible=True, scale_minimum_width=50)
+            self.assertTrue(spec.price_scale_options["ticksVisible"])
+            self.assertEqual(spec.price_scale_options["minimumWidth"], 50)
+
+    def test_new_scale_options_not_set_by_default(self):
+        spec = line_series(self.table)
+        self.assertEqual(spec.price_scale_options, {})
+
+    def test_to_dict_includes_new_scale_options(self):
+        spec = line_series(
+            self.table, scale_mode="percentage", scale_ticks_visible=True
+        )
+        d = spec.to_dict("s0", 0)
+        self.assertIn("priceScaleOptions", d)
+        self.assertEqual(d["priceScaleOptions"]["mode"], 2)  # percentage = 2
+        self.assertTrue(d["priceScaleOptions"]["ticksVisible"])
+
+
+class TestPriceLineOptions(unittest.TestCase):
+    """price_line_* common options on all series types."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_price_line_visible_false(self):
+        spec = line_series(self.table, price_line_visible=False)
+        self.assertFalse(spec.options["priceLineVisible"])
+
+    def test_price_line_visible_true(self):
+        spec = line_series(self.table, price_line_visible=True)
+        self.assertTrue(spec.options["priceLineVisible"])
+
+    def test_price_line_source_last_bar(self):
+        spec = line_series(self.table, price_line_source="last_bar")
+        self.assertEqual(spec.options["priceLineSource"], 0)
+
+    def test_price_line_source_last_visible(self):
+        spec = line_series(self.table, price_line_source="last_visible")
+        self.assertEqual(spec.options["priceLineSource"], 1)
+
+    def test_price_line_width(self):
+        spec = line_series(self.table, price_line_width=2)
+        self.assertEqual(spec.options["priceLineWidth"], 2)
+
+    def test_price_line_color(self):
+        spec = line_series(self.table, price_line_color="#ff0000")
+        self.assertEqual(spec.options["priceLineColor"], "#ff0000")
+
+    def test_price_line_style_dashed(self):
+        spec = line_series(self.table, price_line_style="dashed")
+        self.assertEqual(spec.options["priceLineStyle"], 2)
+
+    def test_price_line_style_solid(self):
+        spec = line_series(self.table, price_line_style="solid")
+        self.assertEqual(spec.options["priceLineStyle"], 0)
+
+    def test_price_line_options_absent_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("priceLineVisible", spec.options)
+        self.assertNotIn("priceLineSource", spec.options)
+        self.assertNotIn("priceLineWidth", spec.options)
+        self.assertNotIn("priceLineColor", spec.options)
+        self.assertNotIn("priceLineStyle", spec.options)
+
+    def test_all_series_types_accept_price_line_options(self):
+        """price_line_* must be accepted by all 6 series functions."""
+        for fn in [
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ]:
+            spec = fn(
+                self.table,
+                price_line_visible=False,
+                price_line_source="last_visible",
+                price_line_width=3,
+                price_line_color="#aabbcc",
+                price_line_style="dotted",
+            )
+            self.assertFalse(spec.options["priceLineVisible"])
+            self.assertEqual(spec.options["priceLineSource"], 1)
+            self.assertEqual(spec.options["priceLineWidth"], 3)
+            self.assertEqual(spec.options["priceLineColor"], "#aabbcc")
+            self.assertEqual(spec.options["priceLineStyle"], 1)  # dotted
+
+    def test_to_dict_includes_price_line_options(self):
+        spec = line_series(
+            self.table,
+            price_line_visible=True,
+            price_line_color="#123456",
+        )
+        result = spec.to_dict("s0", 0)
+        self.assertTrue(result["options"]["priceLineVisible"])
+        self.assertEqual(result["options"]["priceLineColor"], "#123456")
+
+
+class TestBaseLineOptions(unittest.TestCase):
+    """base_line_* common options on all series types."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_base_line_visible_false(self):
+        spec = line_series(self.table, base_line_visible=False)
+        self.assertFalse(spec.options["baseLineVisible"])
+
+    def test_base_line_color(self):
+        spec = line_series(self.table, base_line_color="#B2B5BE")
+        self.assertEqual(spec.options["baseLineColor"], "#B2B5BE")
+
+    def test_base_line_width(self):
+        spec = line_series(self.table, base_line_width=2)
+        self.assertEqual(spec.options["baseLineWidth"], 2)
+
+    def test_base_line_style_solid(self):
+        spec = line_series(self.table, base_line_style="solid")
+        self.assertEqual(spec.options["baseLineStyle"], 0)
+
+    def test_base_line_style_large_dashed(self):
+        spec = line_series(self.table, base_line_style="large_dashed")
+        self.assertEqual(spec.options["baseLineStyle"], 3)
+
+    def test_base_line_options_absent_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("baseLineVisible", spec.options)
+        self.assertNotIn("baseLineColor", spec.options)
+        self.assertNotIn("baseLineWidth", spec.options)
+        self.assertNotIn("baseLineStyle", spec.options)
+
+    def test_all_series_types_accept_base_line_options(self):
+        """base_line_* must be accepted by all 6 series functions."""
+        for fn in [
+            candlestick_series,
+            bar_series,
+            line_series,
+            area_series,
+            baseline_series,
+            histogram_series,
+        ]:
+            spec = fn(
+                self.table,
+                base_line_visible=False,
+                base_line_color="#ffffff",
+                base_line_width=1,
+                base_line_style="dotted",
+            )
+            self.assertFalse(spec.options["baseLineVisible"])
+            self.assertEqual(spec.options["baseLineColor"], "#ffffff")
+            self.assertEqual(spec.options["baseLineWidth"], 1)
+            self.assertEqual(spec.options["baseLineStyle"], 1)  # dotted
+
+    def test_to_dict_includes_base_line_options(self):
+        spec = area_series(
+            self.table,
+            base_line_visible=True,
+            base_line_color="#aaaaaa",
+        )
+        result = spec.to_dict("s0", 0)
+        self.assertTrue(result["options"]["baseLineVisible"])
+        self.assertEqual(result["options"]["baseLineColor"], "#aaaaaa")
+
+
+class TestPriceLineSourceEnum(unittest.TestCase):
+    """PriceLineSource string literals resolve to correct integer values."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_last_bar_is_zero(self):
+        spec = candlestick_series(self.table, price_line_source="last_bar")
+        self.assertEqual(spec.options["priceLineSource"], 0)
+
+    def test_last_visible_is_one(self):
+        spec = candlestick_series(self.table, price_line_source="last_visible")
+        self.assertEqual(spec.options["priceLineSource"], 1)
+
+    def test_source_absent_when_not_set(self):
+        spec = candlestick_series(self.table)
+        self.assertNotIn("priceLineSource", spec.options)
+
+
+class TestLastPriceAnimation(unittest.TestCase):
+    """lastPriceAnimation should serialize correctly on line/area/baseline series."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_line_disabled(self):
+        spec = line_series(self.table, last_price_animation="disabled")
+        self.assertEqual(spec.options["lastPriceAnimation"], 0)
+
+    def test_line_continuous(self):
+        spec = line_series(self.table, last_price_animation="continuous")
+        self.assertEqual(spec.options["lastPriceAnimation"], 1)
+
+    def test_line_on_data_update(self):
+        spec = line_series(self.table, last_price_animation="on_data_update")
+        self.assertEqual(spec.options["lastPriceAnimation"], 2)
+
+    def test_line_not_present_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("lastPriceAnimation", spec.options)
+
+    def test_area_last_price_animation(self):
+        spec = area_series(self.table, last_price_animation="continuous")
+        self.assertEqual(spec.options["lastPriceAnimation"], 1)
+
+    def test_baseline_last_price_animation(self):
+        spec = baseline_series(self.table, last_price_animation="on_data_update")
+        self.assertEqual(spec.options["lastPriceAnimation"], 2)
+
+
+class TestLineVisible(unittest.TestCase):
+    """lineVisible should work on line, area, and baseline series."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_line_series_visible_false(self):
+        spec = line_series(self.table, line_visible=False)
+        self.assertFalse(spec.options["lineVisible"])
+
+    def test_line_series_visible_true(self):
+        spec = line_series(self.table, line_visible=True)
+        self.assertTrue(spec.options["lineVisible"])
+
+    def test_line_series_not_present_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("lineVisible", spec.options)
+
+    def test_area_series(self):
+        spec = area_series(self.table, line_visible=False)
+        self.assertFalse(spec.options["lineVisible"])
+
+    def test_baseline_series(self):
+        spec = baseline_series(self.table, line_visible=False)
+        self.assertFalse(spec.options["lineVisible"])
+
+
+class TestPointMarkers(unittest.TestCase):
+    """pointMarkersVisible and pointMarkersRadius on line/area/baseline."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_line_point_markers_visible(self):
+        spec = line_series(self.table, point_markers_visible=True)
+        self.assertTrue(spec.options["pointMarkersVisible"])
+
+    def test_line_point_markers_not_present_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("pointMarkersVisible", spec.options)
+        self.assertNotIn("pointMarkersRadius", spec.options)
+
+    def test_line_point_markers_radius(self):
+        spec = line_series(self.table, point_markers_radius=3.5)
+        self.assertEqual(spec.options["pointMarkersRadius"], 3.5)
+
+    def test_area_point_markers(self):
+        spec = area_series(
+            self.table, point_markers_visible=True, point_markers_radius=4.0
+        )
+        self.assertTrue(spec.options["pointMarkersVisible"])
+        self.assertEqual(spec.options["pointMarkersRadius"], 4.0)
+
+    def test_baseline_point_markers(self):
+        spec = baseline_series(
+            self.table, point_markers_visible=True, point_markers_radius=2.0
+        )
+        self.assertTrue(spec.options["pointMarkersVisible"])
+        self.assertEqual(spec.options["pointMarkersRadius"], 2.0)
+
+
+class TestCrosshairMarkerExtended(unittest.TestCase):
+    """crosshairMarkerBorderColor/BackgroundColor/BorderWidth on line/area/baseline."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_line_border_color(self):
+        spec = line_series(self.table, crosshair_marker_border_color="#ff0000")
+        self.assertEqual(spec.options["crosshairMarkerBorderColor"], "#ff0000")
+
+    def test_line_background_color(self):
+        spec = line_series(self.table, crosshair_marker_background_color="#00ff00")
+        self.assertEqual(spec.options["crosshairMarkerBackgroundColor"], "#00ff00")
+
+    def test_line_border_width(self):
+        spec = line_series(self.table, crosshair_marker_border_width=3.0)
+        self.assertEqual(spec.options["crosshairMarkerBorderWidth"], 3.0)
+
+    def test_line_empty_string_border_color(self):
+        """Empty string is a valid value (means 'use series color') and must not be filtered."""
+        spec = line_series(self.table, crosshair_marker_border_color="")
+        # _filter_none removes None via `if v is not None`, so "" passes through.
+        self.assertIn("crosshairMarkerBorderColor", spec.options)
+        self.assertEqual(spec.options["crosshairMarkerBorderColor"], "")
+
+    def test_line_not_present_when_none(self):
+        spec = line_series(self.table)
+        self.assertNotIn("crosshairMarkerBorderColor", spec.options)
+        self.assertNotIn("crosshairMarkerBackgroundColor", spec.options)
+        self.assertNotIn("crosshairMarkerBorderWidth", spec.options)
+
+    def test_area_all_three(self):
+        spec = area_series(
+            self.table,
+            crosshair_marker_border_color="#111",
+            crosshair_marker_background_color="#222",
+            crosshair_marker_border_width=1.5,
+        )
+        self.assertEqual(spec.options["crosshairMarkerBorderColor"], "#111")
+        self.assertEqual(spec.options["crosshairMarkerBackgroundColor"], "#222")
+        self.assertEqual(spec.options["crosshairMarkerBorderWidth"], 1.5)
+
+    def test_baseline_all_three(self):
+        spec = baseline_series(
+            self.table,
+            crosshair_marker_border_color="#aaa",
+            crosshair_marker_background_color="#bbb",
+            crosshair_marker_border_width=4.0,
+        )
+        self.assertEqual(spec.options["crosshairMarkerBorderColor"], "#aaa")
+        self.assertEqual(spec.options["crosshairMarkerBackgroundColor"], "#bbb")
+        self.assertEqual(spec.options["crosshairMarkerBorderWidth"], 4.0)
+
+
+class TestCommonOptionsCoexistence(unittest.TestCase):
+    """Common and per-type options coexist without conflict."""
+
+    def setUp(self):
+        self.table = MagicMock(name="table")
+
+    def test_line_common_and_per_type_together(self):
+        spec = line_series(
+            self.table,
+            color="blue",
+            line_width=2,
+            price_line_visible=False,
+            base_line_color="#ff0000",
+            last_value_visible=False,
+            title="My Line",
+        )
+        self.assertEqual(spec.options["color"], "blue")
+        self.assertEqual(spec.options["lineWidth"], 2)
+        self.assertFalse(spec.options["priceLineVisible"])
+        self.assertEqual(spec.options["baseLineColor"], "#ff0000")
+        self.assertFalse(spec.options["lastValueVisible"])
+        self.assertEqual(spec.options["title"], "My Line")
+
+    def test_candlestick_common_and_per_type_together(self):
+        spec = candlestick_series(
+            self.table,
+            up_color="#00ff00",
+            price_line_visible=True,
+            price_line_width=2,
+            base_line_visible=False,
+        )
+        self.assertEqual(spec.options["upColor"], "#00ff00")
+        self.assertTrue(spec.options["priceLineVisible"])
+        self.assertEqual(spec.options["priceLineWidth"], 2)
+        self.assertFalse(spec.options["baseLineVisible"])
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_types.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_types.py
new file mode 100644
index 000000000..bcb1c9891
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_types.py
@@ -0,0 +1,64 @@
+"""Tests for _types module (BusinessDay factory function)."""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock
+
+# Add src to path for namespace package resolution
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight._types import BusinessDay, business_day
+
+
+class TestBusinessDay(unittest.TestCase):
+    """Tests for the business_day() factory function."""
+
+    def test_returns_correct_dict(self):
+        result = business_day(2024, 1, 15)
+        self.assertEqual(result, {"year": 2024, "month": 1, "day": 15})
+
+    def test_all_fields_present(self):
+        result = business_day(2019, 6, 1)
+        self.assertIn("year", result)
+        self.assertIn("month", result)
+        self.assertIn("day", result)
+
+    def test_values_stored_correctly(self):
+        result = business_day(2020, 12, 31)
+        self.assertEqual(result["year"], 2020)
+        self.assertEqual(result["month"], 12)
+        self.assertEqual(result["day"], 31)
+
+    def test_is_dict(self):
+        """TypedDict instances must be plain dicts (JSON-serializable)."""
+        result = business_day(2024, 3, 8)
+        # Must serialize without error
+        serialized = json.dumps(result)
+        self.assertIn('"year": 2024', serialized)
+        self.assertIn('"month": 3', serialized)
+        self.assertIn('"day": 8', serialized)
+
+    def test_importable_from_package(self):
+        """business_day and BusinessDay must be importable from top-level package."""
+        from deephaven.plot.tradingview_lightweight import (
+            BusinessDay,
+            business_day,
+        )
+
+        self.assertIsNotNone(business_day)
+        self.assertIsNotNone(BusinessDay)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_utils.py b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_utils.py
new file mode 100644
index 000000000..31a421d44
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/deephaven/plot/tradingview_lightweight/test_utils.py
@@ -0,0 +1,119 @@
+"""Tests for utility functions."""
+
+from __future__ import annotations
+
+import os
+import sys
+import unittest
+
+sys.path.insert(
+    0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "..", "src")
+)
+
+# Mock deephaven.plugin before any plugin imports trigger it
+from unittest.mock import MagicMock
+
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight.utils import (
+    is_business_day,
+    is_utc_timestamp,
+)
+
+
+class TestIsBusinessDay(unittest.TestCase):
+    def test_valid_business_day(self):
+        self.assertTrue(is_business_day({"year": 2024, "month": 3, "day": 15}))
+
+    def test_extra_keys_ok(self):
+        """Extra keys beyond year/month/day are acceptable."""
+        self.assertTrue(
+            is_business_day({"year": 2024, "month": 3, "day": 15, "extra": "data"})
+        )
+
+    def test_integer_timestamp_is_not_business_day(self):
+        self.assertFalse(is_business_day(1710460800))
+
+    def test_float_timestamp_is_not_business_day(self):
+        self.assertFalse(is_business_day(1710460800.5))
+
+    def test_iso_string_is_not_business_day(self):
+        self.assertFalse(is_business_day("2024-03-15"))
+
+    def test_none_is_not_business_day(self):
+        self.assertFalse(is_business_day(None))
+
+    def test_dict_missing_year(self):
+        self.assertFalse(is_business_day({"month": 3, "day": 15}))
+
+    def test_dict_missing_month(self):
+        self.assertFalse(is_business_day({"year": 2024, "day": 15}))
+
+    def test_dict_missing_day(self):
+        self.assertFalse(is_business_day({"year": 2024, "month": 3}))
+
+    def test_dict_string_year(self):
+        """Non-integer year should return False."""
+        self.assertFalse(is_business_day({"year": "2024", "month": 3, "day": 15}))
+
+    def test_bool_values_rejected(self):
+        """bool is a subclass of int but should not be accepted."""
+        self.assertFalse(is_business_day({"year": True, "month": False, "day": True}))
+
+    def test_empty_dict(self):
+        self.assertFalse(is_business_day({}))
+
+    def test_list_is_not_business_day(self):
+        self.assertFalse(is_business_day([2024, 3, 15]))
+
+
+class TestIsUtcTimestamp(unittest.TestCase):
+    def test_integer_is_utc_timestamp(self):
+        self.assertTrue(is_utc_timestamp(1710460800))
+
+    def test_float_is_utc_timestamp(self):
+        self.assertTrue(is_utc_timestamp(1710460800.5))
+
+    def test_zero_is_utc_timestamp(self):
+        self.assertTrue(is_utc_timestamp(0))
+
+    def test_negative_is_utc_timestamp(self):
+        """Negative timestamps (before epoch) are valid."""
+        self.assertTrue(is_utc_timestamp(-86400))
+
+    def test_bool_is_not_utc_timestamp(self):
+        """bool is a subclass of int in Python; must be excluded."""
+        self.assertFalse(is_utc_timestamp(True))
+        self.assertFalse(is_utc_timestamp(False))
+
+    def test_business_day_dict_is_not_utc_timestamp(self):
+        self.assertFalse(is_utc_timestamp({"year": 2024, "month": 3, "day": 15}))
+
+    def test_iso_string_is_not_utc_timestamp(self):
+        self.assertFalse(is_utc_timestamp("2024-03-15"))
+
+    def test_none_is_not_utc_timestamp(self):
+        self.assertFalse(is_utc_timestamp(None))
+
+    def test_list_is_not_utc_timestamp(self):
+        self.assertFalse(is_utc_timestamp([1710460800]))
+
+
+class TestUtilsExported(unittest.TestCase):
+    """Verify utility functions are importable from the top-level package."""
+
+    def test_is_business_day_exported(self):
+        from deephaven.plot import tradingview_lightweight as tvl
+
+        self.assertTrue(callable(tvl.is_business_day))
+
+    def test_is_utc_timestamp_exported(self):
+        from deephaven.plot import tradingview_lightweight as tvl
+
+        self.assertTrue(callable(tvl.is_utc_timestamp))
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/test_data_submodule.py b/plugins/tradingview-lightweight/test/test_data_submodule.py
new file mode 100644
index 000000000..d8c32b0fc
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/test_data_submodule.py
@@ -0,0 +1,85 @@
+"""Smoke tests for the ``tvl.data`` example-data submodule.
+
+These tests only check that the public API surface is present and well-formed
+(callable, documented, correct signature). They do NOT invoke the functions —
+that requires a live Deephaven server, since the underlying Java backend
+must be running to build tables via ``empty_table``/``new_table``.
+"""
+
+from __future__ import annotations
+
+import inspect
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock
+
+# Wire up src/ on the path and mock the plugin host modules so the package
+# __init__ can import without a Deephaven server present.
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
+
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot.tradingview_lightweight import data  # noqa: E402
+
+
+EXPECTED_FUNCTIONS = [
+    "ohlc",
+    "stocks",
+    "volume",
+    "yields",
+    "options_chain",
+    "values",
+    "large_prices",
+]
+
+
+class TestDataSubmodule(unittest.TestCase):
+    def test_all_exports_expected_names(self) -> None:
+        self.assertEqual(sorted(data.__all__), sorted(EXPECTED_FUNCTIONS))
+
+    def test_each_function_exists_and_is_callable(self) -> None:
+        for name in EXPECTED_FUNCTIONS:
+            with self.subTest(function=name):
+                self.assertTrue(
+                    hasattr(data, name),
+                    f"data submodule is missing {name!r}",
+                )
+                fn = getattr(data, name)
+                self.assertTrue(callable(fn), f"{name!r} is not callable")
+
+    def test_each_function_has_ticking_signature(self) -> None:
+        for name in EXPECTED_FUNCTIONS:
+            with self.subTest(function=name):
+                sig = inspect.signature(getattr(data, name))
+                params = list(sig.parameters.values())
+                self.assertEqual(
+                    [p.name for p in params],
+                    ["ticking"],
+                    f"{name!r} should take a single 'ticking' argument",
+                )
+                self.assertIs(
+                    params[0].default,
+                    True,
+                    f"{name!r} ticking default should be True",
+                )
+
+    def test_each_function_has_non_empty_docstring(self) -> None:
+        for name in EXPECTED_FUNCTIONS:
+            with self.subTest(function=name):
+                doc = inspect.getdoc(getattr(data, name))
+                self.assertIsNotNone(doc, f"{name!r} has no docstring")
+                assert doc is not None  # for type-checkers
+                self.assertGreater(len(doc.strip()), 0, f"{name!r} has empty docstring")
+                # Google-style docstrings should describe the schema.
+                self.assertIn(
+                    "Returns:",
+                    doc,
+                    f"{name!r} docstring is missing a 'Returns:' block",
+                )
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/test/test_docs_coverage.py b/plugins/tradingview-lightweight/test/test_docs_coverage.py
new file mode 100644
index 000000000..cb9ddb606
--- /dev/null
+++ b/plugins/tradingview-lightweight/test/test_docs_coverage.py
@@ -0,0 +1,422 @@
+"""Docs coverage tests for the tradingview-lightweight plugin.
+
+Implements the seven test cases described in
+``notes/subplan-coverage.md`` section B. These exercise the same matrix
+logic as ``tools/build_coverage_matrix.py`` but as unit tests.
+
+The tests do not require a running Deephaven server. The plugin's
+``deephaven.plugin*`` host modules are mocked, and chart.py's optional
+``deephaven.table.Table`` import is caught and falls through to ``None``.
+"""
+
+from __future__ import annotations
+
+import importlib.util
+import inspect
+import json
+import os
+import re
+import sys
+import typing
+import unittest
+from pathlib import Path
+from typing import Iterable
+from unittest.mock import MagicMock
+
+# Wire src/ on the path and mock plugin host modules so the package imports.
+PLUGIN_ROOT = Path(__file__).resolve().parent.parent
+SRC_DIR = PLUGIN_ROOT / "src"
+sys.path.insert(0, str(SRC_DIR))
+
+sys.modules.setdefault("deephaven.plugin", MagicMock())
+sys.modules.setdefault("deephaven.plugin.object_type", MagicMock())
+sys.modules.setdefault("deephaven.plugin.utilities", MagicMock())
+
+from deephaven.plot import tradingview_lightweight as tvl  # noqa: E402
+
+# Load tools/build_coverage_matrix.py as a module so we can reuse its parsers.
+_BCM_SPEC = importlib.util.spec_from_file_location(
+    "_bcm", PLUGIN_ROOT / "tools" / "build_coverage_matrix.py"
+)
+assert _BCM_SPEC and _BCM_SPEC.loader
+bcm = importlib.util.module_from_spec(_BCM_SPEC)
+_BCM_SPEC.loader.exec_module(bcm)
+
+
+DOCS = PLUGIN_ROOT / "docs"
+SNAPSHOTS = DOCS / "snapshots"
+ASSETS = SNAPSHOTS / "assets"
+SIDEBAR = DOCS / "sidebar.json"
+
+# Chart-type pages -> primary function name. Reuses the canonical mapping in
+# build_coverage_matrix.PAGES.
+CHART_TYPE_PAGES: dict[str, str] = dict(bcm.PAGES)
+CHART_TYPE_FUNCS = set(CHART_TYPE_PAGES.values())
+
+# Public Literal-alias names exposed from options.py. These are the "enums"
+# whose value membership we check via typing.get_args().
+ENUM_NAMES = [
+    "ChartType",
+    "ColorSpace",
+    "ColorType",
+    "PriceFormatter",
+    "TickmarksPriceFormatter",
+    "PercentageFormatter",
+    "TickmarksPercentageFormatter",
+    "PrecomputeConflationPriority",
+    "LineStyle",
+    "LineType",
+    "LineWidth",
+    "CrosshairMode",
+    "HorzAlign",
+    "PriceScaleMode",
+    "MarkerShape",
+    "MarkerPosition",
+    "LastPriceAnimationMode",
+    "MarkerSign",
+    "MismatchDirection",
+    "PriceLineSource",
+    "TickMarkType",
+    "TrackingModeExitMode",
+    "VertAlign",
+]
+
+
+def _all_md_files() -> list[Path]:
+    return sorted(DOCS.glob("*.md"))
+
+
+def _read(p: Path) -> str:
+    return p.read_text(encoding="utf-8")
+
+
+def _all_code_blocks() -> list[str]:
+    """Every python code-block body across all docs/*.md files."""
+    out: list[str] = []
+    for p in _all_md_files():
+        out.extend(bcm.extract_code_blocks(_read(p)))
+    return out
+
+
+def _all_dhautofunction_targets() -> set[str]:
+    """Every dotted symbol referenced by a ``.. dhautofunction::`` directive."""
+    pat = re.compile(r"\.\.\s*dhautofunction::\s*([\w.]+)")
+    out: set[str] = set()
+    for p in _all_md_files():
+        for m in pat.finditer(_read(p)):
+            out.add(m.group(1))
+    return out
+
+
+def _name_mentioned_anywhere(name: str) -> bool:
+    """True if ``name`` appears as a word in any docs/*.md file (anywhere —
+    prose, code block, or dhautofunction directive)."""
+    pat = re.compile(rf"\b{re.escape(name)}\b")
+    for p in _all_md_files():
+        if pat.search(_read(p)):
+            return True
+    return False
+
+
+class TestSymbolCoverage(unittest.TestCase):
+    """Test 1 — every name in ``__all__`` appears in at least one .md file."""
+
+    def test_symbol_coverage(self) -> None:
+        missing: list[str] = []
+        for name in tvl.__all__:
+            if not _name_mentioned_anywhere(name):
+                missing.append(name)
+        self.assertEqual(
+            missing,
+            [],
+            f"Public symbols not mentioned in any docs/*.md: {missing}",
+        )
+
+
+class TestParameterCoverage(unittest.TestCase):
+    """Test 2 — for each chart-type function, every parameter is covered by
+    a kwarg in a code block on its primary page or a coverage-seen-elsewhere
+    annotation pointing at a real page."""
+
+    def test_parameter_coverage(self) -> None:
+        all_md = {p.name for p in _all_md_files()}
+        missing: dict[str, list[str]] = {}
+
+        for page_fname, func_name in CHART_TYPE_PAGES.items():
+            page_path = DOCS / page_fname
+            self.assertTrue(
+                page_path.exists(), f"Expected page does not exist: {page_fname}"
+            )
+            params = bcm.parse_signature_params(bcm.CHART_PY, func_name)
+            params = [p for p in params if p != "table"]
+            md = _read(page_path)
+            blocks = bcm.extract_code_blocks(md)
+            elsewhere = bcm.extract_seen_elsewhere(md)
+
+            # Each elsewhere target must resolve to a real page.
+            for k, v in elsewhere.items():
+                self.assertIn(
+                    v,
+                    all_md,
+                    f"{page_fname}: coverage-seen-elsewhere for {k!r} points "
+                    f"to {v!r}, which is not a real docs page",
+                )
+
+            page_missing: list[str] = []
+            for p in params:
+                if bcm.kwarg_used(p, blocks):
+                    continue
+                if p in elsewhere:
+                    continue
+                page_missing.append(p)
+            if page_missing:
+                missing[page_fname] = page_missing
+
+        self.assertEqual(
+            missing,
+            {},
+            f"Parameters with no docs coverage: {missing}",
+        )
+
+
+class TestEnumCoverage(unittest.TestCase):
+    """Test 3 — for each Literal alias, every value appears in at least one
+    code block somewhere in the docs."""
+
+    def test_enum_coverage(self) -> None:
+        blocks = _all_code_blocks()
+        missing: dict[str, list[object]] = {}
+        for enum_name in ENUM_NAMES:
+            alias = getattr(tvl, enum_name)
+            values = typing.get_args(alias)
+            self.assertGreater(len(values), 0, f"{enum_name} has no Literal args")
+            unseen: list[object] = []
+            for v in values:
+                if isinstance(v, str):
+                    # Quoted string literal in a code block.
+                    pat = re.compile(rf"""['"]{re.escape(v)}['"]""")
+                elif isinstance(v, int):
+                    # Bare int literal — word-boundary match.
+                    pat = re.compile(rf"\b{v}\b")
+                else:
+                    unseen.append(v)
+                    continue
+                if not any(pat.search(b) for b in blocks):
+                    unseen.append(v)
+            if unseen:
+                missing[enum_name] = unseen
+        self.assertEqual(
+            missing,
+            {},
+            f"Enum/Literal values not used in any code block: {missing}",
+        )
+
+
+class TestAssetReferenceIntegrity(unittest.TestCase):
+    """Test 4 — every image path referenced in a snapshot JSON resolves to a
+    real file under docs/snapshots/assets/."""
+
+    def test_asset_reference_integrity(self) -> None:
+        if not SNAPSHOTS.exists():
+            self.skipTest("docs/snapshots/ does not exist")
+        broken: list[str] = []
+        for jf in sorted(SNAPSHOTS.glob("*.json")):
+            try:
+                doc = json.loads(jf.read_text(encoding="utf-8"))
+            except json.JSONDecodeError as e:
+                self.fail(f"{jf.name}: invalid JSON ({e})")
+            objects = doc.get("objects") or {}
+            # `objects` is a dict keyed by `order=` name; iterate its values.
+            # Some entries (e.g. salmon's `:log` type) carry a string `data`
+            # rather than a dict — only TvlChart entries point at an asset.
+            for obj in objects.values():
+                data = obj.get("data") if isinstance(obj, dict) else None
+                if not isinstance(data, dict):
+                    continue
+                image = data.get("image")
+                if not image:
+                    continue
+                # `image` is expected to be a path relative to docs/snapshots/.
+                target = (SNAPSHOTS / image).resolve()
+                if not target.exists():
+                    broken.append(f"{jf.name} -> {image}")
+        self.assertEqual(
+            broken,
+            [],
+            f"Snapshot JSONs reference missing assets: {broken}",
+        )
+
+
+class TestNoOrphanAssets(unittest.TestCase):
+    """Test 5 — every PNG under docs/snapshots/assets/ is referenced by at
+    least one JSON under docs/snapshots/."""
+
+    def test_no_orphan_assets(self) -> None:
+        if not ASSETS.exists():
+            self.skipTest("docs/snapshots/assets/ does not exist")
+        pngs = sorted(ASSETS.glob("*.png"))
+        if not pngs:
+            self.skipTest("no PNG assets present")
+        # Collect every image-path string referenced by any snapshot JSON.
+        referenced: set[Path] = set()
+        for jf in sorted(SNAPSHOTS.glob("*.json")):
+            try:
+                doc = json.loads(jf.read_text(encoding="utf-8"))
+            except json.JSONDecodeError:
+                continue
+            objects = doc.get("objects") or {}
+            for obj in objects.values():
+                data = obj.get("data") if isinstance(obj, dict) else None
+                if not isinstance(data, dict):
+                    continue
+                image = data.get("image")
+                if image:
+                    referenced.add((SNAPSHOTS / image).resolve())
+        orphans = [p.name for p in pngs if p.resolve() not in referenced]
+        self.assertEqual(
+            orphans,
+            [],
+            f"PNG assets not referenced by any snapshot JSON: {orphans}",
+        )
+
+
+class TestSidebarHasEveryPage(unittest.TestCase):
+    """Test 6 — every docs/*.md file (except README.md) appears in
+    sidebar.json under some item's ``path`` field."""
+
+    @staticmethod
+    def _walk_paths(node: object) -> Iterable[str]:
+        if isinstance(node, dict):
+            if isinstance(node.get("path"), str):
+                yield node["path"]
+            for v in node.values():
+                yield from TestSidebarHasEveryPage._walk_paths(v)
+        elif isinstance(node, list):
+            for item in node:
+                yield from TestSidebarHasEveryPage._walk_paths(item)
+
+    def test_sidebar_has_every_page(self) -> None:
+        self.assertTrue(SIDEBAR.exists(), "docs/sidebar.json is missing")
+        doc = json.loads(SIDEBAR.read_text(encoding="utf-8"))
+        sidebar_paths = set(self._walk_paths(doc))
+        missing: list[str] = []
+        for md in _all_md_files():
+            if md.name == "README.md":
+                continue
+            if md.name not in sidebar_paths:
+                missing.append(md.name)
+        self.assertEqual(
+            missing,
+            [],
+            f"Pages not listed in sidebar.json: {missing}",
+        )
+
+
+class TestDhautofunctionPerPublicSymbol(unittest.TestCase):
+    """Test 7 — every callable in ``__all__`` appears at least once in an
+    ``.. dhautofunction::`` directive.
+
+    Relaxed rule (per task instructions): chart-type functions covered by the
+    coverage matrix must have an explicit dhautofunction directive. Other
+    callable ``__all__`` symbols (e.g. ``Marker``, ``PriceLine``,
+    ``SeriesSpec``) only require their NAME to appear in a .md file, either
+    in a code block or in a dhautofunction directive.
+    """
+
+    def test_dhautofunction_per_public_symbol(self) -> None:
+        targets = _all_dhautofunction_targets()
+        directive_names = {t.rsplit(".", 1)[-1] for t in targets}
+
+        missing_strict: list[str] = []
+        missing_lenient: list[str] = []
+
+        for name in tvl.__all__:
+            obj = getattr(tvl, name)
+            if not callable(obj) or inspect.ismodule(obj):
+                continue
+            if name in CHART_TYPE_FUNCS:
+                # Must have explicit dhautofunction directive.
+                if name not in directive_names:
+                    missing_strict.append(name)
+            else:
+                # Just needs to appear in some .md file.
+                if not _name_mentioned_anywhere(name):
+                    missing_lenient.append(name)
+
+        self.assertEqual(
+            missing_strict,
+            [],
+            f"Chart-type functions missing a dhautofunction directive: "
+            f"{missing_strict}",
+        )
+        self.assertEqual(
+            missing_lenient,
+            [],
+            f"Public callables not mentioned anywhere in docs: " f"{missing_lenient}",
+        )
+
+
+class TestOrderNamesAssigned(unittest.TestCase):
+    """Test 8 — every name listed in a ``python order=...`` fence must be
+    assigned at top level inside that block's body.
+
+    Mismatches here used to silently crash the Pass-2 docs snapshot pipeline:
+    the fixture generator looked up every order= name in the block's
+    locals dict, and a `KeyError` for one name (e.g. order=sum but the
+    code defined sum_chart) propagated through app.d evaluation and
+    killed the whole JVM at server startup. Catch it at the doc-edit
+    boundary instead.
+    """
+
+    @staticmethod
+    def _assigned_names(body: str) -> set[str]:
+        import ast
+
+        names: set[str] = set()
+        try:
+            tree = ast.parse(body)
+        except SyntaxError:
+            return names
+        for node in ast.walk(tree):
+            if isinstance(node, ast.Assign):
+                for tgt in node.targets:
+                    if isinstance(tgt, ast.Name):
+                        names.add(tgt.id)
+                    elif isinstance(tgt, ast.Tuple):
+                        for el in tgt.elts:
+                            if isinstance(el, ast.Name):
+                                names.add(el.id)
+            elif isinstance(node, ast.AnnAssign) and isinstance(node.target, ast.Name):
+                names.add(node.target.id)
+        return names
+
+    def test_order_names_assigned(self) -> None:
+        fence = re.compile(r"```python\s+([^\n]*)\n(.*?)```", re.DOTALL)
+        order_re = re.compile(r"order=([\w,]+)")
+        problems: list[str] = []
+        for md in sorted(DOCS.glob("*.md")):
+            text = md.read_text(encoding="utf-8")
+            for m in fence.finditer(text):
+                info, body = m.group(1), m.group(2)
+                om = order_re.search(info)
+                if not om:
+                    continue
+                order_names = [n for n in om.group(1).split(",") if n]
+                assigned = self._assigned_names(body)
+                missing = [n for n in order_names if n not in assigned]
+                if missing:
+                    problems.append(
+                        f"{md.name}: order=({','.join(order_names)}) "
+                        f"but missing assignments for {missing}"
+                    )
+        self.assertEqual(
+            problems,
+            [],
+            "Code blocks have `order=` names that aren't assigned in the "
+            "block body. These would crash the Pass-2 snapshotter:\n"
+            + "\n".join(problems),
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/plugins/tradingview-lightweight/tools/build_coverage_matrix.py b/plugins/tradingview-lightweight/tools/build_coverage_matrix.py
new file mode 100644
index 000000000..9183180d4
--- /dev/null
+++ b/plugins/tradingview-lightweight/tools/build_coverage_matrix.py
@@ -0,0 +1,114 @@
+"""Coverage matrix tool. Checks that every parameter of each TVL chart-type
+function appears either as a kwarg in a code block on its primary doc page or
+in a `coverage-seen-elsewhere` annotation.
+
+Usage:
+    python tools/build_coverage_matrix.py            # print matrix
+    python tools/build_coverage_matrix.py --check    # exit 1 if missing
+"""
+from __future__ import annotations
+import ast
+import inspect
+import re
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parent.parent
+DOCS = ROOT / "docs"
+
+# Map of page -> (function dotted path, expected primary symbol attr)
+PAGES = {
+    "candlestick.md": "candlestick",
+    "bar.md": "bar",
+    "line.md": "line",
+    "area.md": "area",
+    "baseline.md": "baseline",
+    "histogram.md": "histogram",
+    "yield-curve.md": "yield_curve",
+    "options-chart.md": "options_chart",
+    "custom-numeric.md": "custom_numeric",
+}
+
+
+def parse_signature_params(src_file: Path, func_name: str) -> list[str]:
+    """Parse a Python source file with ast and return the parameter names of
+    the named top-level function."""
+    tree = ast.parse(src_file.read_text())
+    for node in tree.body:
+        if isinstance(node, ast.FunctionDef) and node.name == func_name:
+            args = node.args
+            names = [a.arg for a in args.args]
+            return [n for n in names if n != "self"]
+    raise KeyError(f"function {func_name} not found in {src_file}")
+
+
+CHART_PY = ROOT / "src" / "deephaven" / "plot" / "tradingview_lightweight" / "chart.py"
+
+
+def extract_code_blocks(md: str) -> list[str]:
+    """Return all python code-block bodies."""
+    pat = re.compile(r"```python[^\n]*\n(.*?)```", re.DOTALL)
+    return pat.findall(md)
+
+
+def extract_seen_elsewhere(md: str) -> dict[str, str]:
+    """Parse the `coverage-seen-elsewhere` HTML comment at the top of the file."""
+    m = re.search(r"<!--\s*coverage-seen-elsewhere:(.*?)-->", md, re.DOTALL)
+    if not m:
+        return {}
+    out = {}
+    for line in m.group(1).splitlines():
+        line = line.strip()
+        if not line or "->" not in line:
+            continue
+        k, v = [s.strip() for s in line.split("->", 1)]
+        out[k] = v
+    return out
+
+
+def kwarg_used(param: str, blocks: list[str]) -> bool:
+    """Return True if param appears as `param=` anywhere in any block."""
+    pat = re.compile(rf"\b{re.escape(param)}\s*=")
+    return any(pat.search(b) for b in blocks)
+
+
+def main():
+    check_mode = "--check" in sys.argv
+
+    missing_total = 0
+    print("# TVL Docs Coverage Matrix\n")
+    for page_fname, func_name in PAGES.items():
+        page_path = DOCS / page_fname
+        if not page_path.exists():
+            print(f"## {page_fname}: MISSING FILE")
+            missing_total += 1
+            continue
+        params = parse_signature_params(CHART_PY, func_name)
+        # drop `table` (positional, no kwarg form expected)
+        params = [p for p in params if p != "table"]
+        md = page_path.read_text()
+        blocks = extract_code_blocks(md)
+        elsewhere = extract_seen_elsewhere(md)
+
+        print(f"## {page_fname} -> tvl.{func_name}\n")
+        print("| Parameter | Seen in |")
+        print("|---|---|")
+        page_missing = []
+        for p in params:
+            if kwarg_used(p, blocks):
+                print(f"| {p} | {page_fname} |")
+            elif p in elsewhere:
+                print(f"| {p} | {elsewhere[p]} (via annotation) |")
+            else:
+                print(f"| {p} | **MISSING** |")
+                page_missing.append(p)
+        print()
+        if page_missing:
+            missing_total += len(page_missing)
+
+    if check_mode and missing_total:
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/plugins/tradingview-lightweight/tox.ini b/plugins/tradingview-lightweight/tox.ini
new file mode 100644
index 000000000..ea9b45f58
--- /dev/null
+++ b/plugins/tradingview-lightweight/tox.ini
@@ -0,0 +1,8 @@
+[tox]
+envlist = py{39,310,311,312,313}
+
+[testenv]
+deps =
+    unittest2
+commands =
+    python -m unittest {posargs}
diff --git a/plugins/tradingview-lightweight/uv.lock b/plugins/tradingview-lightweight/uv.lock
new file mode 100644
index 000000000..bda020730
--- /dev/null
+++ b/plugins/tradingview-lightweight/uv.lock
@@ -0,0 +1,3 @@
+version = 1
+revision = 3
+requires-python = ">=3.13"
diff --git a/sphinx_ext/deephaven_autodoc.py b/sphinx_ext/deephaven_autodoc.py
index d987a12c2..14b2f6e52 100644
--- a/sphinx_ext/deephaven_autodoc.py
+++ b/sphinx_ext/deephaven_autodoc.py
@@ -40,6 +40,7 @@ class SignatureData(TypedDict):
     module_name: str
     name: str
     description: NotRequired[str]
+    Raises: NotRequired[SignatureValue]
 
 
 SignatureValue = Union[str, Params]
@@ -319,6 +320,11 @@ def extract_desc_data(node: sphinx.addnodes.desc) -> SignatureData:
     return SignatureData(**result)
 
 
+def _escape_mdx_braces(text: str) -> str:
+    """Escape ``{`` / ``}`` so MDX doesn't try to acorn-parse them as JSX."""
+    return text.replace("{", "&#123;").replace("}", "&#125;")
+
+
 def to_mdx(node: sphinx.addnodes.desc) -> docutils.nodes.comment:
     """
     Convert the provided description node to a node that is a mdx component
@@ -335,13 +341,42 @@ def to_mdx(node: sphinx.addnodes.desc) -> docutils.nodes.comment:
     return_description = result.pop("return_description")
     return_type = result.pop("return_type")
     description = result.pop("description")
+    # Raises also has to come out: a multi-line ``:raises:`` docstring leaves
+    # ``<br />`` markers in the value, and the post-processor rewrites those
+    # back to literal newlines that acorn can't parse inside the JSX
+    # expression. Render it as its own bolded run instead.
+    raises = result.pop("Raises", None)
 
     dat = json.dumps(result)
 
+    # MDX 3 treats ``{`` as the start of a JSX expression. Freeform docstring
+    # runs frequently contain literal curly braces (dict-shape ``Returns:``
+    # blurbs, JS-ish examples), so escape them for any prose we splice
+    # directly into the markdown.
+    description = _escape_mdx_braces(description)
+    return_description = _escape_mdx_braces(return_description)
+
+    if isinstance(raises, list):
+        # bullet-list :raises: with multiple entries
+        raises_text = "<br />".join(
+            f"{p['name']} ({p['type']}) -- {p['description']}"
+            if p.get("type")
+            else f"{p['name']} -- {p['description']}"
+            for p in raises
+        )
+    elif raises:
+        raises_text = raises
+    else:
+        raises_text = ""
+    raises_text = _escape_mdx_braces(raises_text) if raises_text else ""
+
+    raises_md = rf"**Raises:** {raises_text}<br /><br />" if raises_text else ""
+
     autofunction_markdown = (
         f"{AUTOFUNCTION_COMMENT_PREFIX}"
         rf"{description}<br /><br />"
         rf"**Returns:** `{return_type}` {return_description}<br /><br />"
+        f"{raises_md}"
         rf"<ParamTable param={{{dat}}} />"
     )
 
diff --git a/tests/app.d/disconnect_test.py b/tests/app.d/disconnect_test.py
new file mode 100644
index 000000000..50b91c766
--- /dev/null
+++ b/tests/app.d/disconnect_test.py
@@ -0,0 +1,22 @@
+"""Test fixture for disconnect comparison: iris-grid table, plotly-express chart, TVL chart."""
+from deephaven import empty_table
+from deephaven.time import to_j_instant
+from deephaven.plot import express as dx
+from deephaven.plot import tradingview_lightweight as tvl
+
+_start = to_j_instant("2024-01-01T00:00:00 ET")
+test_table = empty_table(1000).update(
+    [
+        "Timestamp = _start + (long)(ii * 86_400_000_000_000L)",
+        "Price = 100 + Math.sin(ii * 0.05) * 20",
+    ]
+)
+
+# iris-grid panel (plain table)
+grid_panel = test_table
+
+# plotly-express panel
+dx_panel = dx.line(test_table, x="Timestamp", y="Price")
+
+# TVL panel
+tvl_panel = tvl.line(test_table, time="Timestamp", value="Price")
diff --git a/tests/app.d/pv_isolate.py b/tests/app.d/pv_isolate.py
new file mode 100644
index 000000000..eef6d52a7
--- /dev/null
+++ b/tests/app.d/pv_isolate.py
@@ -0,0 +1,77 @@
+"""Isolated Price+Volume test fixture.
+
+Mimics the Sizzle dashboard's "Price + Volume" panel in isolation so
+autobin/viewport behavior can be exercised without the cost of the full
+dashboard. Loads as `pv_chart` in the IDE.
+
+- Seed: 4000 1-minute rows for one symbol (AAPL).
+- Tick: 0.5s synthetic minute-bar appender that continues from the seed.
+- Two-pane chart: area_series (Close) + histogram_series (Volume).
+"""
+
+from deephaven import empty_table, merge, time_table, ui
+from deephaven.time import to_j_instant
+from deephaven import updateby as uby
+from deephaven.plot import tradingview_lightweight as tvl
+
+_SEED_ROWS = 4_000
+_seed_start = to_j_instant("2024-05-29T09:30:00 ET")
+
+seed = (
+    empty_table(_SEED_ROWS)
+    .update(
+        [
+            "Sym = `AAPL`",
+            "Timestamp = _seed_start + (long)(ii * 60_000_000_000L)",
+            "_Ret = (Math.random() - 0.48) * 1.2",
+        ]
+    )
+    .update_by([uby.cum_sum(cols=["_Cum = _Ret"])])
+    .update(
+        [
+            "Close  = 150.0 + _Cum",
+            "Volume = (long)(500_000 + Math.random() * 1_500_000)",
+        ]
+    )
+    .view(["Sym", "Timestamp", "Close", "Volume"])
+)
+
+_last_close = seed.last_by("Sym").view(["Sym", "LastClose = Close"])
+
+ticker = (
+    time_table("PT00:00:00.500000000")
+    .drop_columns("Timestamp")
+    .update(
+        [
+            "Sym = `AAPL`",
+            f"Timestamp = _seed_start + (long)(({_SEED_ROWS}L + ii) * 60_000_000_000L)",
+            "_Ret = (Math.random() - 0.48) * 1.2",
+        ]
+    )
+    .update_by([uby.cum_sum(cols=["_Cum = _Ret"])], by=["Sym"])
+    .natural_join(_last_close, on="Sym")
+    .update(
+        [
+            "Close  = LastClose + _Cum",
+            "Volume = (long)(500_000 + Math.random() * 1_500_000)",
+        ]
+    )
+    .view(["Sym", "Timestamp", "Close", "Volume"])
+)
+
+pv_data = merge([seed, ticker])
+
+pv_chart = tvl.chart(
+    tvl.area_series(pv_data, time="Timestamp", value="Close", title="Price", pane=0),
+    tvl.histogram_series(
+        pv_data,
+        time="Timestamp",
+        value="Volume",
+        price_scale_id="vol",
+        pane=1,
+    ),
+    crosshair_mode="magnet",
+    vert_lines_visible=False,
+    horz_lines_visible=False,
+    pane_stretch_factors=[3.0, 1.0],
+)
diff --git a/tests/app.d/sizzle.py b/tests/app.d/sizzle.py
new file mode 100644
index 000000000..5a4bbf1de
--- /dev/null
+++ b/tests/app.d/sizzle.py
@@ -0,0 +1,334 @@
+"""
+Sizzle Dashboard — TradingView Lightweight Charts showcase.
+
+Simulates ticking stock + options data and builds an interactive dashboard
+with 6 TVL chart panels connected via shared state.
+"""
+
+import datetime
+from typing import Any
+
+from deephaven import empty_table, merge, new_table, time_table, ui
+from deephaven.column import datetime_col, double_col, long_col, string_col
+from deephaven.time import to_j_instant
+from deephaven.stream.table_publisher import table_publisher
+from deephaven import dtypes as dht
+from deephaven import updateby as uby
+from deephaven.plot import tradingview_lightweight as tvl
+
+# =============================================================================
+# 1. Simulated ticking stock data
+# =============================================================================
+
+SYMBOLS = ["AAPL", "MSFT", "GOOG", "AMZN", "TSLA"]
+
+_SEED_ROWS_PER_SYM = 4_000
+
+_seed_start = to_j_instant("2024-05-29T09:30:00 ET")
+
+_seeds = []
+for _idx, _sym in enumerate(SYMBOLS):
+    _base = 150.0 + _idx * 30
+    _vol = 1.2 + _idx * 0.25
+    _t = (
+        empty_table(_SEED_ROWS_PER_SYM)
+        .update(
+            [
+                f"Sym = `{_sym}`",
+                f"Timestamp = _seed_start + (long)(ii * 60_000_000_000L)",
+                f"_Ret = (Math.random() - 0.48) * {_vol}",
+            ]
+        )
+        .update_by(
+            [uby.cum_sum(cols=["_Cum = _Ret"])],
+        )
+        .update(
+            [
+                f"Open  = {_base} + _Cum",
+                f"Close = Open + (Math.random() - 0.48) * {_vol * 0.6}",
+                "High  = Math.max(Open, Close) + Math.random() * 2",
+                "Low   = Math.min(Open, Close) - Math.random() * 2",
+                "Volume = (long)(500_000 + Math.random() * 1_500_000)",
+            ]
+        )
+        .view(["Sym", "Timestamp", "Open", "High", "Low", "Close", "Volume"])
+    )
+    _seeds.append(_t)
+
+seed_table = merge(_seeds)
+
+_last_prices = seed_table.last_by("Sym").view(["Sym", "LastClose = Close"])
+
+_tick_base = time_table("PT00:00:00.500000000").drop_columns("Timestamp")
+tick_table = (
+    _tick_base.update(
+        [
+            "SymIdx = (int)(ii % 5)",
+            "Sym    = new String[]{`AAPL`, `MSFT`, `GOOG`, `AMZN`, `TSLA`}[SymIdx]",
+            f"Timestamp = _seed_start + (long)(({_SEED_ROWS_PER_SYM}L + ii / 5L) * 60_000_000_000L)",
+            "_Vol   = 1.2 + SymIdx * 0.25",
+            "_Ret   = (Math.random() - 0.48) * _Vol",
+        ]
+    )
+    .update_by(
+        [uby.cum_sum(cols=["_Cum = _Ret"])],
+        by=["Sym"],
+    )
+    .natural_join(
+        _last_prices,
+        on="Sym",
+    )
+    .update(
+        [
+            "Open   = LastClose + _Cum",
+            "Close  = Open + (Math.random() - 0.48) * _Vol * 0.6",
+            "High   = Math.max(Open, Close) + Math.random() * 2",
+            "Low    = Math.min(Open, Close) - Math.random() * 2",
+            "Volume = (long)(500_000 + Math.random() * 1_500_000)",
+        ]
+    )
+    .view(["Sym", "Timestamp", "Open", "High", "Low", "Close", "Volume"])
+)
+
+stock_data = merge([seed_table, tick_table])
+
+stock_enriched = stock_data.update_by(
+    [
+        uby.ema_tick(decay_ticks=20, cols=["EMA20 = Close"]),
+        uby.rolling_avg_tick(cols=["SMA20 = Close"], rev_ticks=20),
+        uby.rolling_std_tick(cols=["StdDev = Close"], rev_ticks=20),
+    ],
+    by=["Sym"],
+).update(
+    [
+        "BollingerUp   = SMA20 + 2 * StdDev",
+        "BollingerDown = SMA20 - 2 * StdDev",
+    ]
+)
+
+
+options_data = empty_table(15).update(
+    [
+        "Strike = 100.0 + ii * 10",
+        "CallIV = 0.35 - ii * 0.015 + Math.random() * 0.02",
+        "PutIV  = 0.15 + ii * 0.018 + Math.random() * 0.02",
+    ]
+)
+
+_marker_blink, marker_publisher = table_publisher(
+    "TradeMarkers",
+    {
+        "Timestamp": dht.Instant,
+        "Position": dht.string,
+        "Shape": dht.string,
+        "Label": dht.string,
+        "Color": dht.string,
+    },
+)
+marker_table = _marker_blink.tail(500)
+
+
+@ui.component
+def sizzle_layout():
+    selected_sym, set_selected_sym = ui.use_state("AAPL")
+
+    sym_data = ui.use_memo(
+        lambda: stock_enriched.where(f"Sym = `{selected_sym}`"),
+        [selected_sym],
+    )
+
+    options_chart = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.line_series(
+                options_data, time="Strike", value="CallIV", title="Call IV"
+            ),
+            tvl.line_series(options_data, time="Strike", value="PutIV", title="Put IV"),
+            chart_type="options",
+            crosshair_mode="magnet",
+        ),
+        [options_data],
+    )
+
+    area_volume = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.area_series(
+                sym_data, time="Timestamp", value="Close", title="Price", pane=0
+            ),
+            tvl.histogram_series(
+                sym_data,
+                time="Timestamp",
+                value="Volume",
+                price_scale_id="vol",
+                pane=1,
+            ),
+            crosshair_mode="magnet",
+            vert_lines_visible=False,
+            horz_lines_visible=False,
+            pane_stretch_factors=[3.0, 1.0],
+        ),
+        [sym_data, selected_sym],
+    )
+
+    sym_extremes_data = ui.use_memo(
+        lambda: (
+            sym_data.natural_join(
+                sym_data.view(["HighMax = Close"]).max_by(), on=""
+            ).natural_join(sym_data.view(["LowMin = Close"]).min_by(), on="")
+        ),
+        [sym_data],
+    )
+
+    area_minmax = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.area_series(
+                sym_extremes_data,
+                time="Timestamp",
+                value="Close",
+                price_lines=[
+                    tvl.price_line(column="HighMax", title="High", line_style="dashed"),
+                    tvl.price_line(column="LowMin", title="Low", line_style="dotted"),
+                ],
+            ),
+            crosshair_mode="magnet",
+            vert_lines_visible=False,
+            horz_lines_visible=False,
+        ),
+        [sym_extremes_data, selected_sym],
+    )
+
+    five_lines = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.line_series(sym_data, time="Timestamp", value="Close", title="Close"),
+            tvl.line_series(sym_data, time="Timestamp", value="EMA20", title="EMA 20"),
+            tvl.line_series(sym_data, time="Timestamp", value="SMA20", title="SMA 20"),
+            tvl.line_series(
+                sym_data,
+                time="Timestamp",
+                value="BollingerUp",
+                title="BB Upper",
+                line_style="dashed",
+            ),
+            tvl.line_series(
+                sym_data,
+                time="Timestamp",
+                value="BollingerDown",
+                title="BB Lower",
+                line_style="dashed",
+            ),
+            crosshair_mode="magnet",
+        ),
+        [sym_data, selected_sym],
+    )
+
+    ohlc_chart = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.candlestick_series(
+                sym_data,
+                time="Timestamp",
+                open="Open",
+                high="High",
+                low="Low",
+                close="Close",
+                marker_spec=tvl.markers_from_table(
+                    marker_table,
+                    time="Timestamp",
+                    text_column="Label",
+                    position_column="Position",
+                    shape_column="Shape",
+                    color_column="Color",
+                ),
+            ),
+            tvl.line_series(sym_data, time="Timestamp", value="EMA20", title="EMA 20"),
+            crosshair_mode="magnet",
+        ),
+        [sym_data, selected_sym, marker_table],
+    )
+
+    first_open_table = ui.use_memo(
+        lambda: sym_data.first_by().view(["Open"]),
+        [sym_data],
+    )
+    first_open = ui.use_cell_data(first_open_table, "Open")
+
+    baseline_chart = ui.use_memo(
+        lambda: tvl.chart(
+            tvl.baseline_series(
+                sym_data,
+                time="Timestamp",
+                value="Close",
+                base_value=first_open if first_open is not None else 150.0,
+            ),
+            tvl.line_series(sym_data, time="Timestamp", value="EMA20", title="EMA 20"),
+            crosshair_mode="magnet",
+        ),
+        [sym_data, selected_sym, first_open],
+    )
+
+    def handle_buy(_event: Any) -> None:
+        marker_publisher.add(
+            new_table(
+                [
+                    datetime_col(
+                        "Timestamp", [datetime.datetime.now(tz=datetime.timezone.utc)]
+                    ),
+                    string_col("Position", ["belowBar"]),
+                    string_col("Shape", ["arrowUp"]),
+                    string_col("Label", ["BUY"]),
+                    string_col("Color", ["#26a69a"]),
+                ]
+            )
+        )
+
+    def handle_sell(_event: Any) -> None:
+        marker_publisher.add(
+            new_table(
+                [
+                    datetime_col(
+                        "Timestamp", [datetime.datetime.now(tz=datetime.timezone.utc)]
+                    ),
+                    string_col("Position", ["aboveBar"]),
+                    string_col("Shape", ["arrowDown"]),
+                    string_col("Label", ["SELL"]),
+                    string_col("Color", ["#ef5350"]),
+                ]
+            )
+        )
+
+    sym_options = stock_data.view(["Sym"]).select_distinct(["Sym"])
+
+    controls = ui.flex(
+        ui.picker(
+            sym_options,
+            label="Symbol",
+            label_position="side",
+            selected_key=selected_sym,
+            on_selection_change=set_selected_sym,
+        ),
+        ui.action_button("BUY", on_press=handle_buy),
+        ui.action_button("SELL", on_press=handle_sell),
+        direction="row",
+    )
+
+    return ui.column(
+        ui.row(
+            ui.panel(controls, title="Controls"),
+            height=7,
+        ),
+        ui.row(
+            ui.stack(
+                ui.panel(baseline_chart, title="Baseline"),
+                ui.panel(options_chart, title="Options IV Smile"),
+            ),
+            ui.panel(area_volume, title="Price + Volume"),
+            ui.panel(area_minmax, title="Price Range"),
+            height=46,
+        ),
+        ui.row(
+            ui.panel(five_lines, title="5-Line Technicals"),
+            ui.panel(ohlc_chart, title="OHLC + Trades"),
+            height=47,
+        ),
+    )
+
+
+sizzle = ui.dashboard(sizzle_layout())
diff --git a/tests/app.d/tests.app b/tests/app.d/tests.app
index 10beb52cc..c9abd6ff0 100644
--- a/tests/app.d/tests.app
+++ b/tests/app.d/tests.app
@@ -16,8 +16,9 @@ file_9=ui_grid.py
 file_10=ui_plotly.py
 file_11=ag_grid.py
 file_12=theme_demo.py
-file_13=ui_nested_dashboard.py
-file_14=ui_query_params.py
-file_15=ui_home_screen.py
-file_16=ui_routing.py
-file_17=ui_events.py
+file_13=tradingview_lightweight.py
+file_14=ui_nested_dashboard.py
+file_15=ui_query_params.py
+file_16=ui_home_screen.py
+file_17=ui_routing.py
+file_18=ui_events.py
diff --git a/tests/app.d/tradingview_lightweight.py b/tests/app.d/tradingview_lightweight.py
new file mode 100644
index 000000000..7f77045f7
--- /dev/null
+++ b/tests/app.d/tradingview_lightweight.py
@@ -0,0 +1,824 @@
+from typing import Any
+
+from deephaven.column import int_col, string_col, double_col, datetime_col, long_col
+from deephaven import new_table, empty_table, time_table, merge, ui
+from deephaven.time import to_j_instant
+from deephaven.stream.table_publisher import table_publisher
+from deephaven import dtypes as dht
+from deephaven.plot import tradingview_lightweight as tvl
+
+# =============================================================================
+# Test data tables
+# =============================================================================
+
+# OHLC data for candlestick and bar charts
+ohlc_source = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [
+                to_j_instant("2024-01-02T10:00:00 ET"),
+                to_j_instant("2024-01-03T10:00:00 ET"),
+                to_j_instant("2024-01-04T10:00:00 ET"),
+                to_j_instant("2024-01-05T10:00:00 ET"),
+                to_j_instant("2024-01-08T10:00:00 ET"),
+                to_j_instant("2024-01-09T10:00:00 ET"),
+                to_j_instant("2024-01-10T10:00:00 ET"),
+                to_j_instant("2024-01-11T10:00:00 ET"),
+                to_j_instant("2024-01-12T10:00:00 ET"),
+                to_j_instant("2024-01-16T10:00:00 ET"),
+            ],
+        ),
+        double_col(
+            "Open",
+            [100.0, 102.0, 101.0, 105.0, 103.0, 106.0, 108.0, 107.0, 110.0, 109.0],
+        ),
+        double_col(
+            "High",
+            [103.0, 104.0, 106.0, 107.0, 108.0, 110.0, 112.0, 111.0, 113.0, 112.0],
+        ),
+        double_col(
+            "Low", [99.0, 100.0, 100.0, 103.0, 101.0, 104.0, 106.0, 105.0, 108.0, 107.0]
+        ),
+        double_col(
+            "Close",
+            [102.0, 101.0, 105.0, 103.0, 106.0, 108.0, 107.0, 110.0, 109.0, 111.0],
+        ),
+        long_col(
+            "Volume", [1200, 1500, 1800, 1100, 2000, 1700, 1400, 1900, 1600, 2100]
+        ),
+    ]
+)
+
+# Simple value data for line, area, baseline, histogram charts
+value_source = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [
+                to_j_instant("2024-01-02T10:00:00 ET"),
+                to_j_instant("2024-01-03T10:00:00 ET"),
+                to_j_instant("2024-01-04T10:00:00 ET"),
+                to_j_instant("2024-01-05T10:00:00 ET"),
+                to_j_instant("2024-01-08T10:00:00 ET"),
+                to_j_instant("2024-01-09T10:00:00 ET"),
+                to_j_instant("2024-01-10T10:00:00 ET"),
+                to_j_instant("2024-01-11T10:00:00 ET"),
+                to_j_instant("2024-01-12T10:00:00 ET"),
+                to_j_instant("2024-01-16T10:00:00 ET"),
+            ],
+        ),
+        double_col(
+            "Value", [50.0, 55.0, 48.0, 60.0, 58.0, 65.0, 62.0, 70.0, 68.0, 75.0]
+        ),
+        double_col(
+            "SMA_5", [50.0, 52.5, 51.0, 53.3, 54.2, 57.2, 58.6, 63.0, 64.6, 68.0]
+        ),
+    ]
+)
+
+# Volume data for histogram overlay
+volume_source = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [
+                to_j_instant("2024-01-02T10:00:00 ET"),
+                to_j_instant("2024-01-03T10:00:00 ET"),
+                to_j_instant("2024-01-04T10:00:00 ET"),
+                to_j_instant("2024-01-05T10:00:00 ET"),
+                to_j_instant("2024-01-08T10:00:00 ET"),
+                to_j_instant("2024-01-09T10:00:00 ET"),
+                to_j_instant("2024-01-10T10:00:00 ET"),
+                to_j_instant("2024-01-11T10:00:00 ET"),
+                to_j_instant("2024-01-12T10:00:00 ET"),
+                to_j_instant("2024-01-16T10:00:00 ET"),
+            ],
+        ),
+        double_col(
+            "Volume",
+            [
+                1200.0,
+                1500.0,
+                1800.0,
+                1100.0,
+                2000.0,
+                1700.0,
+                1400.0,
+                1900.0,
+                1600.0,
+                2100.0,
+            ],
+        ),
+    ]
+)
+
+
+# =============================================================================
+# 1-6. Single-series charts — all defaults (theme colors, time visible)
+# =============================================================================
+tvl_candlestick = tvl.candlestick(
+    ohlc_source,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+)
+
+tvl_bar = tvl.bar(
+    ohlc_source,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+)
+
+tvl_line = tvl.line(value_source, timestamp="Timestamp", value="Value")
+
+tvl_area = tvl.area(value_source, timestamp="Timestamp", value="Value")
+
+tvl_baseline = tvl.baseline(
+    value_source, timestamp="Timestamp", value="Value", base_value=60.0
+)
+
+tvl_histogram = tvl.histogram(volume_source, timestamp="Timestamp", value="Volume")
+
+# =============================================================================
+# 7. Candlestick with explicit custom colors (tests non-default styling)
+# =============================================================================
+tvl_candlestick_styled = tvl.candlestick(
+    ohlc_source,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    up_color="#00C805",
+    down_color="#FF2A04",
+    border_up_color="#00C805",
+    border_down_color="#FF2A04",
+    wick_up_color="#00C805",
+    wick_down_color="#FF2A04",
+    watermark_text="AAPL",
+)
+
+# =============================================================================
+# 8. Multi-series: Candlestick + SMA line overlay
+# =============================================================================
+tvl_candlestick_with_sma = tvl.chart(
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+    ),
+    tvl.line_series(
+        value_source,
+        timestamp="Timestamp",
+        value="SMA_5",
+        title="SMA 5",
+    ),
+    crosshair_mode="magnet",
+)
+
+# =============================================================================
+# 9. Multi-series: Candlestick + Volume histogram
+# =============================================================================
+tvl_candlestick_with_volume = tvl.chart(
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+    ),
+    tvl.histogram_series(
+        volume_source,
+        timestamp="Timestamp",
+        value="Volume",
+        color="rgba(38, 166, 154, 0.5)",
+        price_scale_id="volume",
+    ),
+    right_price_scale_visible=True,
+)
+
+# =============================================================================
+# 10. Candlestick with price lines
+# =============================================================================
+tvl_candlestick_price_lines = tvl.candlestick(
+    ohlc_source,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    price_lines=[
+        tvl.price_line(105.0, title="Resistance"),
+        tvl.price_line(100.0, title="Support"),
+    ],
+)
+
+# =============================================================================
+# 11. Candlestick with markers
+# =============================================================================
+tvl_candlestick_markers = tvl.chart(
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+        markers=[
+            tvl.marker(
+                time="2024-01-04", position="below_bar", shape="arrow_up", text="Buy"
+            ),
+            tvl.marker(
+                time="2024-01-10", position="above_bar", shape="arrow_down", text="Sell"
+            ),
+        ],
+    ),
+)
+
+# =============================================================================
+# 12. Line chart with custom grid
+# =============================================================================
+tvl_line_custom_grid = tvl.line(
+    value_source,
+    timestamp="Timestamp",
+    value="Value",
+    background_color="#1E222D",
+    text_color="#D1D4DC",
+    crosshair_mode="magnet",
+)
+
+# =============================================================================
+# 13. Area chart with watermark
+# =============================================================================
+tvl_area_watermark = tvl.area(
+    value_source,
+    timestamp="Timestamp",
+    value="Value",
+    watermark_text="DH Stock",
+)
+
+# =============================================================================
+# 14. Multi-series: Two line series overlay
+# =============================================================================
+tvl_dual_line = tvl.chart(
+    tvl.line_series(value_source, timestamp="Timestamp", value="Value", title="Price"),
+    tvl.line_series(value_source, timestamp="Timestamp", value="SMA_5", title="SMA 5"),
+)
+
+# =============================================================================
+# 15. Full trading dashboard: Candlestick + SMA + Volume
+# =============================================================================
+tvl_full_dashboard = tvl.chart(
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+    ),
+    tvl.line_series(value_source, timestamp="Timestamp", value="SMA_5", title="SMA 5"),
+    tvl.histogram_series(
+        volume_source,
+        timestamp="Timestamp",
+        value="Volume",
+        color="rgba(38, 166, 154, 0.5)",
+        price_scale_id="volume",
+    ),
+    crosshair_mode="magnet",
+    watermark_text="AAPL",
+    right_price_scale_visible=True,
+)
+
+# =============================================================================
+# 16. Two price scales: line on right, candlestick on left
+# =============================================================================
+tvl_two_price_scales = tvl.chart(
+    tvl.line_series(
+        value_source, timestamp="Timestamp", value="Value", title="Value (Right)"
+    ),
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+        price_scale_id="left",
+    ),
+    right_price_scale_visible=True,
+    left_price_scale_visible=True,
+    crosshair_mode="normal",
+)
+
+# =============================================================================
+# 17. Panes: Candlestick (top) + Volume histogram (bottom pane)
+# =============================================================================
+tvl_panes_basic = tvl.chart(
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+        pane=0,
+    ),
+    tvl.histogram_series(
+        volume_source,
+        timestamp="Timestamp",
+        value="Volume",
+        color="rgba(38, 166, 154, 0.5)",
+        pane=1,
+    ),
+    pane_stretch_factors=[3.0, 1.0],
+)
+
+# =============================================================================
+# 18. Panes: Three panes with custom separator styling
+# =============================================================================
+tvl_panes_three = tvl.chart(
+    tvl.candlestick_series(
+        ohlc_source,
+        timestamp="Timestamp",
+        open="Open",
+        high="High",
+        low="Low",
+        close="Close",
+        pane=0,
+    ),
+    tvl.line_series(
+        value_source,
+        timestamp="Timestamp",
+        value="SMA_5",
+        title="SMA 5",
+        pane=1,
+    ),
+    tvl.histogram_series(
+        volume_source,
+        timestamp="Timestamp",
+        value="Volume",
+        color="rgba(38, 166, 154, 0.5)",
+        pane=2,
+    ),
+    pane_separator_color="#ff4444",
+    pane_separator_hover_color="rgba(255, 68, 68, 0.3)",
+    pane_enable_resize=False,
+    pane_stretch_factors=[3.0, 2.0, 1.0],
+)
+
+# =============================================================================
+# Yield curve data
+# =============================================================================
+yield_curve_source = new_table(
+    [
+        int_col("Maturity", [1, 3, 6, 12, 24, 60, 120, 360]),
+        double_col("Yield", [5.30, 5.25, 5.10, 4.80, 4.50, 4.20, 4.00, 3.80]),
+    ]
+)
+
+# =============================================================================
+# 19. Yield curve chart (line)
+# =============================================================================
+tvl_yield_curve = tvl.yield_curve(
+    yield_curve_source,
+    maturity="Maturity",
+    value="Yield",
+    title="US Treasury",
+    base_resolution=1,
+    minimum_time_range=400,
+    watermark_text="Yield Curve",
+)
+
+# =============================================================================
+# 20. Yield curve chart (area)
+# =============================================================================
+tvl_yield_curve_area = tvl.yield_curve(
+    yield_curve_source,
+    maturity="Maturity",
+    value="Yield",
+    series_type="area",
+    title="US Treasury",
+    base_resolution=1,
+    minimum_time_range=400,
+)
+
+# =============================================================================
+# Options chart data
+# =============================================================================
+options_source = new_table(
+    [
+        double_col("Strike", [90.0, 95.0, 100.0, 105.0, 110.0, 115.0, 120.0]),
+        double_col("CallPremium", [12.0, 8.5, 5.0, 2.5, 1.0, 0.4, 0.1]),
+        double_col("PutPremium", [0.1, 0.3, 0.8, 2.0, 4.5, 8.0, 12.5]),
+    ]
+)
+
+# =============================================================================
+# 21. Options chart (single series)
+# =============================================================================
+tvl_options_single = tvl.options_chart(
+    options_source,
+    strike="Strike",
+    value="CallPremium",
+    title="Call Premium",
+    watermark_text="Options",
+)
+
+# =============================================================================
+# 22. Options chart (multi-series: calls + puts)
+# =============================================================================
+tvl_options_multi = tvl.chart(
+    tvl.line_series(
+        options_source, timestamp="Strike", value="CallPremium", title="Calls"
+    ),
+    tvl.line_series(
+        options_source, timestamp="Strike", value="PutPremium", title="Puts"
+    ),
+    chart_type="options",
+    watermark_text="Call vs Put",
+)
+
+# =============================================================================
+# Dynamic price line data – add computed columns to the source table
+# =============================================================================
+from deephaven import updateby as uby
+
+ohlc_with_stats = ohlc_source.update_by(
+    [
+        uby.cum_max("MaxHigh = High"),
+        uby.cum_min("MinLow = Low"),
+        uby.rolling_avg_tick("AvgClose = Close", rev_ticks=5),
+    ]
+)
+
+# =============================================================================
+# 23. Candlestick with dynamic price lines (column-based)
+# =============================================================================
+tvl_dynamic_price_lines = tvl.candlestick(
+    ohlc_with_stats,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    price_lines=[
+        tvl.price_line(column="MaxHigh", title="Max High"),
+        tvl.price_line(column="MinLow", title="Min Low"),
+        tvl.price_line(column="AvgClose", line_style="dashed", title="Avg Close"),
+    ],
+)
+
+# =============================================================================
+# 24. Candlestick with mixed static + dynamic price lines
+# =============================================================================
+tvl_mixed_price_lines = tvl.candlestick(
+    ohlc_with_stats,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    price_lines=[
+        tvl.price_line(price=105.0, title="Target"),
+        tvl.price_line(column="AvgClose", line_style="dashed", title="Avg Close"),
+    ],
+)
+
+# =============================================================================
+# Table-driven markers
+# =============================================================================
+
+# A signals table: buy on 2024-01-04, sell on 2024-01-10
+signals_source = new_table(
+    [
+        datetime_col(
+            "SignalTime",
+            [
+                to_j_instant("2024-01-04T10:00:00 ET"),
+                to_j_instant("2024-01-10T10:00:00 ET"),
+            ],
+        ),
+        string_col("Label", ["Buy", "Sell"]),
+        string_col("Position", ["belowBar", "aboveBar"]),
+        string_col("Shape", ["arrowUp", "arrowDown"]),
+        string_col("Color", ["#26a69a", "#ef5350"]),
+    ]
+)
+
+# =============================================================================
+# 25. Candlestick with table-driven markers (per-row columns)
+# =============================================================================
+tvl_table_markers = tvl.candlestick(
+    ohlc_source,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    marker_spec=tvl.markers_from_table(
+        signals_source,
+        timestamp="SignalTime",
+        text_column="Label",
+        position_column="Position",
+        shape_column="Shape",
+        color_column="Color",
+    ),
+)
+
+# =============================================================================
+# 26. Candlestick with table-driven markers (fixed styling)
+# =============================================================================
+tvl_table_markers_fixed = tvl.candlestick(
+    ohlc_source,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+    marker_spec=tvl.markers_from_table(
+        signals_source,
+        timestamp="SignalTime",
+        text_column="Label",
+        position="below_bar",
+        shape="arrow_up",
+    ),
+)
+
+# =============================================================================
+# By (partitioned) ticking chart — tests dynamic partition key discovery
+# =============================================================================
+
+# Create publisher: Sym (string), Timestamp (Instant), Price (double)
+_by_blink, _by_publisher = table_publisher(
+    "By Test",
+    {"Sym": dht.string, "Timestamp": dht.Instant, "Price": dht.double},
+)
+# Accumulate rows across publishes (blink only shows latest tick)
+_by_table = _by_blink.tail(100)
+
+# Seed with 10 rows of AAPL
+_by_publisher.add(
+    new_table(
+        [
+            string_col("Sym", ["AAPL"] * 10),
+            datetime_col(
+                "Timestamp",
+                [to_j_instant(f"2024-01-{i + 2:02d}T10:00:00 ET") for i in range(10)],
+            ),
+            double_col("Price", [150.0 + i for i in range(10)]),
+        ]
+    )
+)
+
+
+@ui.component
+def _tvl_by_ticking_component():
+    added, set_added = ui.use_state(False)
+
+    def handle_add(_event: Any) -> None:
+        _by_publisher.add(
+            new_table(
+                [
+                    string_col("Sym", ["GOOG"] * 10),
+                    datetime_col(
+                        "Timestamp",
+                        [
+                            to_j_instant(f"2024-01-{i + 2:02d}T10:00:00 ET")
+                            for i in range(10)
+                        ],
+                    ),
+                    double_col("Price", [100.0 + i * 2 for i in range(10)]),
+                ]
+            )
+        )
+        set_added(True)
+
+    plot = ui.use_memo(
+        lambda: tvl.line(_by_table, timestamp="Timestamp", value="Price", by="Sym"),
+        [_by_table],
+    )
+
+    return ui.flex(
+        ui.action_button(
+            "Added" if added else "Add GOOG",
+            on_press=handle_add,
+        ),
+        plot,
+        direction="column",
+        flex_grow=1,
+    )
+
+
+tvl_by_ticking = _tvl_by_ticking_component()
+
+# =============================================================================
+# Downsampling test: 10M rows over 10 years
+# =============================================================================
+
+_big_start = to_j_instant("2014-01-01T00:00:00 ET")
+big_table = empty_table(10_000_000).update(
+    [
+        # Spread 10M rows evenly over 10 years (~3.15s apart)
+        "Timestamp = _big_start + (long)(ii * (10L * 365 * 24 * 3600 * 1_000_000_000L / 10_000_000))",
+        # Trending sine wave: base 100, amplitude 50, slow upward drift
+        "Price = 100 + Math.sin(ii * 0.0001) * 50 + (ii * 0.000005)",
+    ]
+)
+
+tvl_big_line = tvl.line(
+    big_table,
+    timestamp="Timestamp",
+    value="Price",
+)
+
+# Small table that should NOT be downsampled (10 rows)
+small_table = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [to_j_instant(f"2024-01-{i+2:02d}T10:00:00 ET") for i in range(10)],
+        ),
+        double_col("Value", [50.0 + i * 3 for i in range(10)]),
+    ]
+)
+tvl_small_line = tvl.line(small_table, timestamp="Timestamp", value="Value")
+
+# Ticking table: 100K historical + 1 row/sec live
+from deephaven import updateby as uby
+
+_TICK_N = 100_000
+_ticking_table = (
+    merge(
+        [
+            empty_table(_TICK_N).update("Index = ii"),
+            time_table("PT1S")
+            .update(f"Index = ii + {_TICK_N}")
+            .drop_columns("Timestamp"),
+        ]
+    )
+    .update(
+        [
+            "Timestamp = '2024-01-01T00:00:00Z' + (long)(Index * 1_000_000_000L)",
+            "Step = (Math.random() - 0.499) * 0.5",
+        ]
+    )
+    .update_by([uby.cum_sum(cols=["Walk = Step"])])
+    .update("Price = 100 + Walk")
+    .view(["Timestamp", "Price"])
+)
+tvl_ticking_line = tvl.line(_ticking_table, timestamp="Timestamp", value="Price")
+
+# =============================================================================
+# Auto-bin fixtures — server-side time-bucket aggregation
+# =============================================================================
+
+# A 10M-row "tick" table with derived OHLC columns. Auto-bin will reduce
+# this to ~5000 bars on initial load.
+big_ohlc_table = big_table.update(
+    [
+        "Open = Price - 1.0",
+        "High = Price + 2.0",
+        "Low = Price - 2.0",
+        "Close = Price",
+        "Volume = 1000.0 + Math.abs(Math.sin(ii * 0.01)) * 500.0",
+    ]
+)
+
+# Histogram (default agg=sum) — auto-binned
+tvl_big_hist = tvl.histogram(
+    big_table,
+    timestamp="Timestamp",
+    value="Price",
+)
+
+# Histogram with count aggregation
+tvl_big_hist_count = tvl.histogram(
+    big_table,
+    timestamp="Timestamp",
+    value="Price",
+    agg="count",
+)
+
+# Candlestick with four distinct OHLC columns (replaces the previously
+# unsupported single-price Candlestick fixture).
+tvl_big_candlestick = tvl.candlestick(
+    big_ohlc_table,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+)
+
+# Bar (OHLC) variant
+tvl_big_bar = tvl.bar(
+    big_ohlc_table,
+    timestamp="Timestamp",
+    open="Open",
+    high="High",
+    low="Low",
+    close="Close",
+)
+
+# Small histogram — should NOT trigger auto-bin
+_small_hist_table = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [to_j_instant(f"2024-01-{i+2:02d}T10:00:00 ET") for i in range(10)],
+        ),
+        double_col("Volume", [100.0 + i * 5 for i in range(10)]),
+    ]
+)
+tvl_small_hist = tvl.histogram(_small_hist_table, timestamp="Timestamp", value="Volume")
+
+# Ticking histogram — verify aggregated view ticks
+tvl_ticking_hist = tvl.histogram(_ticking_table, timestamp="Timestamp", value="Price")
+
+# Mixed series: Line (downsample path) + Histogram (auto-bin path)
+# on different source tables.
+tvl_mixed_line_hist = tvl.chart(
+    tvl.line_series(big_table, timestamp="Timestamp", value="Price"),
+    tvl.histogram_series(big_table, timestamp="Timestamp", value="Price"),
+)
+
+# Histogram with explicit bin_width override.
+# Use a 1-month subset so PT5M produces ~8640 bins, not millions.
+_bin_override_table = empty_table(1_000_000).update(
+    [
+        "Timestamp = '2024-01-01T00:00:00 ET' + (long)(ii * (30L * 24 * 3600 * 1_000_000_000L / 1_000_000))",
+        "Price = 100 + Math.sin(ii * 0.0001) * 50",
+    ]
+)
+tvl_big_hist_pt5m = tvl.histogram(
+    _bin_override_table,
+    timestamp="Timestamp",
+    value="Price",
+    bin_width="PT5M",
+)
+
+# Histogram with bin_count override
+tvl_big_hist_bc200 = tvl.histogram(
+    big_table,
+    timestamp="Timestamp",
+    value="Price",
+    bin_count=200,
+)
+
+# Histogram with auto_bin=False — opts out (small derived table to avoid
+# shipping 10M rows to the client).
+_optout_table = big_table.head(2000)
+tvl_big_hist_optout = tvl.histogram(
+    _optout_table,
+    timestamp="Timestamp",
+    value="Price",
+    auto_bin=False,
+)
+
+# Diagnostic: area + volume histogram on big_table in 2 panes (mimics
+# Sizzle Price+Volume panel shape).
+tvl_big_area_volume_panes = tvl.chart(
+    tvl.area_series(
+        big_ohlc_table, timestamp="Timestamp", value="Close", title="Price", pane=0
+    ),
+    tvl.histogram_series(
+        big_ohlc_table,
+        timestamp="Timestamp",
+        value="Volume",
+        price_scale_id="vol",
+        pane=1,
+    ),
+    pane_stretch_factors=[3.0, 1.0],
+)
+
+# Diagnostic: same shape as Sizzle Price+Volume — area+histogram on a
+# FILTERED ticking table (uses where()).
+from deephaven import updateby as _uby_diag
+
+_diag_seed = empty_table(4000).update(
+    [
+        "Sym = ii % 5 == 0 ? `AAPL` : `OTHER`",
+        "Timestamp = '2024-05-29T09:30:00 ET' + (long)(ii * 60_000_000_000L)",
+        "Close = 150.0 + Math.sin(ii * 0.01) * 20",
+        "Volume = (long)(500_000 + Math.random() * 1_500_000)",
+    ]
+)
+_diag_aapl = _diag_seed.where("Sym = `AAPL`")
+tvl_diag_filtered_panes = tvl.chart(
+    tvl.area_series(_diag_aapl, timestamp="Timestamp", value="Close", pane=0),
+    tvl.histogram_series(
+        _diag_aapl, timestamp="Timestamp", value="Volume", price_scale_id="vol", pane=1
+    ),
+    pane_stretch_factors=[3.0, 1.0],
+)
diff --git a/tests/app.d/tvl_downsample_test.py b/tests/app.d/tvl_downsample_test.py
new file mode 100644
index 000000000..61e1c9a74
--- /dev/null
+++ b/tests/app.d/tvl_downsample_test.py
@@ -0,0 +1,53 @@
+"""Minimal test fixture for Python-side downsampling."""
+
+from deephaven.column import double_col, datetime_col
+from deephaven import new_table, empty_table, time_table, merge
+from deephaven import updateby as uby
+from deephaven.time import to_j_instant
+from deephaven.plot import tradingview_lightweight as tvl
+
+# Small table (not downsampled)
+small_table = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [to_j_instant(f"2024-01-{i+2:02d}T10:00:00 ET") for i in range(10)],
+        ),
+        double_col("Value", [50.0 + i * 3 for i in range(10)]),
+    ]
+)
+tvl_small = tvl.line(small_table, time="Timestamp", value="Value")
+
+# Big table (10M rows - should be downsampled)
+_big_start = to_j_instant("2014-01-01T00:00:00 ET")
+big_table = empty_table(10_000_000).update(
+    [
+        "Timestamp = _big_start + (long)(ii * (10L * 365 * 24 * 3600 * 1_000_000_000L / 10_000_000))",
+        "Price = 100 + Math.sin(ii * 0.0001) * 50 + (ii * 0.000005)",
+    ]
+)
+tvl_big = tvl.line(big_table, time="Timestamp", value="Price")
+
+# ---------- Ticking version (100M historical + 1 row/sec live) ----------
+#
+# Pattern from dx.data.stocks: merge a static Index column with a ticking
+# Index column, then derive everything from Index after the merge.
+_N = 100_000_000
+big_ticking_table = (
+    merge(
+        [
+            empty_table(_N).update("Index = ii"),
+            time_table("PT1S").update(f"Index = ii + {_N}").drop_columns("Timestamp"),
+        ]
+    )
+    .update(
+        [
+            "Timestamp = '2020-01-01T00:00:00Z' + (long)(Index * 1_000_000_000L)",
+            "Step = (Math.random() - 0.499) * 0.5",
+        ]
+    )
+    .update_by([uby.cum_sum(cols=["Walk = Step"])])
+    .update("Price = 100 + Walk")
+    .view(["Timestamp", "Price"])
+)
+tvl_big_ticking = tvl.line(big_ticking_table, time="Timestamp", value="Price")
diff --git a/tests/app.d/tvl_events.py b/tests/app.d/tvl_events.py
new file mode 100644
index 000000000..62c9b52f8
--- /dev/null
+++ b/tests/app.d/tvl_events.py
@@ -0,0 +1,83 @@
+"""Fixture for the press-event Playwright spec.
+
+A partitioned (`by=`) line chart with two series far apart in price at a known
+time T (key ``A`` ~= 10, key ``B`` ~= 90). Crosshair magnet mode snaps clicks
+to the nearest data point so the inversion-oracle is deterministic. The
+``on_press`` handler writes each event into ``tvl_events_result`` so the spec
+can prove the full canvas -> JS -> wire -> Python -> handler -> table round
+trip by reading that table back through the JS API.
+"""
+
+from typing import Any
+
+from deephaven import new_table
+from deephaven.column import datetime_col, double_col, string_col
+from deephaven.time import to_j_instant
+from deephaven.stream.table_publisher import table_publisher
+from deephaven import dtypes as dht
+from deephaven.plot import tradingview_lightweight as tvl
+
+# Known time T the spec clicks on (and a few flanking points so each line has
+# extent). ET offsets are resolved by to_j_instant.
+_TIMES = [
+    "2024-06-03T10:00:00 ET",
+    "2024-06-04T10:00:00 ET",
+    "2024-06-05T10:00:00 ET",
+    "2024-06-06T10:00:00 ET",
+    "2024-06-07T10:00:00 ET",
+]
+
+# Two partitions: A flat ~10, B flat ~90 — far apart so a click unambiguously
+# lands on one series under magnet snapping.
+_src = new_table(
+    [
+        datetime_col(
+            "Timestamp",
+            [to_j_instant(t) for t in _TIMES] + [to_j_instant(t) for t in _TIMES],
+        ),
+        string_col("Sym", ["A"] * len(_TIMES) + ["B"] * len(_TIMES)),
+        double_col(
+            "Price",
+            [10.0, 10.0, 10.0, 10.0, 10.0] + [90.0, 90.0, 90.0, 90.0, 90.0],
+        ),
+    ]
+)
+
+# Result table the handler appends to (round-trip proof). Time is stored as
+# epoch seconds (double) to keep the handler free of Instant conversions.
+_result_pub_table, _result_pub = table_publisher(
+    "tvl_events_result",
+    {
+        "Type": dht.string,
+        "SeriesId": dht.string,
+        "Price": dht.double,
+        "TimeSec": dht.double,
+    },
+)
+tvl_events_result = _result_pub_table.tail(50)
+
+
+def _on_press(e: Any) -> None:
+    time_val = e.get("time")
+    _result_pub.add(
+        new_table(
+            [
+                string_col("Type", [str(e.get("type", ""))]),
+                string_col("SeriesId", [str(e.get("seriesId") or "")]),
+                double_col("Price", [float(e.get("price") or 0.0)]),
+                double_col(
+                    "TimeSec", [time_val.timestamp() if time_val is not None else 0.0]
+                ),
+            ]
+        )
+    )
+
+
+# Compose so the chart carries crosshair magnet mode + the handlers; the
+# per-type line carries the `by=` partition template.
+tvl_events_chart = tvl.chart(
+    tvl.line(_src, timestamp="Timestamp", value="Price", by="Sym"),
+    crosshair_mode="magnet",
+    on_press=_on_press,
+    on_double_press=lambda e: None,
+)
diff --git a/tests/tradingview_lightweight.spec.ts b/tests/tradingview_lightweight.spec.ts
new file mode 100644
index 000000000..301bdfc6b
--- /dev/null
+++ b/tests/tradingview_lightweight.spec.ts
@@ -0,0 +1,1440 @@
+import { expect, test } from '@playwright/test';
+import { openPanel, gotoPage } from './utils';
+
+// The default WidgetPanel wrapper may pre-render a hidden instance of
+// the component, so use the default '.dh-panel' selector for openPanel
+// (which counts correctly) and scope screenshots to the last visible
+// chart container.
+const tvlChart = (page: import('@playwright/test').Page) =>
+  page.locator('.dh-tvl-chart').last();
+
+// --------------------------------------------------------------------------
+// Single-series convenience function charts
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Single Series', () => {
+  test('Candlestick chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_candlestick');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Bar chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_bar');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Line chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_line');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Area chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_area');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Baseline chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_baseline');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Histogram chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_histogram');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Styled and customized charts
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Styled Charts', () => {
+  test('Candlestick with custom colors loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_candlestick_styled');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Line chart with custom grid loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_line_custom_grid');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Area chart with watermark loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_area_watermark');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Annotations: price lines and markers
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Annotations', () => {
+  test('Candlestick with price lines loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_candlestick_price_lines');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Candlestick with markers loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_candlestick_markers');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Multi-series composition charts
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Multi-Series', () => {
+  test('Candlestick with SMA overlay loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_candlestick_with_sma');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Candlestick with volume histogram loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_candlestick_with_volume');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Dual line series overlay loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_dual_line');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Full trading dashboard loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_full_dashboard');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Two price scales loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_two_price_scales');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Panes
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Panes', () => {
+  test('Two-pane chart with candlestick and volume loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_panes_basic');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Three-pane chart with custom separators loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_panes_three');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Yield Curve Charts
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Yield Curve', () => {
+  test('Yield curve line chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_yield_curve');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Yield curve area chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_yield_curve_area');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Options Charts
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Options Chart', () => {
+  test('Single series options chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_options_single');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Multi-series options chart loads', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_options_multi');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Dynamic Price Lines
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Dynamic Price Lines', () => {
+  test('Candlestick with dynamic column-based price lines loads', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_dynamic_price_lines');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Candlestick with mixed static and dynamic price lines loads', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_mixed_price_lines');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Table-Driven Markers
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Table-Driven Markers', () => {
+  test('Candlestick with table-driven markers (per-row columns) loads', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_table_markers');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+
+  test('Candlestick with table-driven markers (fixed styling) loads', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_table_markers_fixed');
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// By (partitioned) ticking charts
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - By Ticking', () => {
+  test('New partition key adds a second trace after button click', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_by_ticking', '.dh-react-panel:visible');
+
+    const panel = page.locator('.dh-react-panel:visible');
+
+    // Wait for initial chart render (1 series: AAPL only)
+    await expect(panel.locator('.dh-tvl-chart')).toBeVisible();
+    await expect(panel).toHaveScreenshot();
+
+    // Click button to publish GOOG rows
+    await panel.getByRole('button', { name: 'Add GOOG' }).click();
+
+    // Wait for button text to confirm callback ran
+    await expect(panel.getByRole('button', { name: 'Added' })).toBeVisible();
+
+    // Wait for the async chain: PartitionedTable EVENT_KEYADDED →
+    // JS getTable(key) → subscribe → data render
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(3000);
+
+    // Chart should now show 2 colored traces (AAPL + GOOG)
+    await expect(panel).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Downsampling (large table)
+// --------------------------------------------------------------------------
+
+test.describe('TradingView Lightweight - Downsampling', () => {
+  test('10M row line chart loads with downsampling', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_line');
+
+    // Chart should render (not hang or crash) — 10M rows downsampled
+    await expect(tvlChart(page)).toBeVisible();
+    await expect(tvlChart(page)).toHaveScreenshot();
+  });
+});
+
+// --------------------------------------------------------------------------
+// Downsampling interactions (zoom, pan, reset)
+// --------------------------------------------------------------------------
+
+interface DsState {
+  jsDs: boolean;
+  tableSize: number;
+  colDataRows: number;
+  pendingDs: boolean;
+  visRange: [number, number] | null;
+}
+
+/** Read the structured debug state from the data-tvl-state attribute. */
+async function getDsState(
+  page: import('@playwright/test').Page
+): Promise<DsState> {
+  return page.evaluate(() => {
+    const el = document.querySelector('.dh-tvl-chart');
+    const raw = el?.getAttribute('data-tvl-state');
+    return raw ? JSON.parse(raw) : {};
+  });
+}
+
+/** Wait until jsDs is true, pendingDs is false, and colDataRows > 0. */
+async function waitForDsReady(
+  page: import('@playwright/test').Page,
+  timeout = 15000
+): Promise<DsState> {
+  const start = Date.now();
+  while (Date.now() - start < timeout) {
+    const state = await getDsState(page);
+    if (state.jsDs && !state.pendingDs && state.colDataRows > 0) {
+      return state;
+    }
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+  }
+  return getDsState(page);
+}
+
+/** Wait for state to change from a previous snapshot (new data arrived). */
+async function waitForStateChange(
+  page: import('@playwright/test').Page,
+  prev: DsState,
+  timeout = 15000
+): Promise<DsState> {
+  const start = Date.now();
+  while (Date.now() - start < timeout) {
+    const state = await getDsState(page);
+    if (
+      !state.pendingDs &&
+      state.colDataRows > 0 &&
+      (state.tableSize !== prev.tableSize ||
+        state.colDataRows !== prev.colDataRows)
+    ) {
+      return state;
+    }
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+  }
+  return getDsState(page);
+}
+
+/** Wait for pendingDs to go false (downsample settled). */
+async function waitForDsSettled(
+  page: import('@playwright/test').Page,
+  timeout = 15000
+): Promise<DsState> {
+  const start = Date.now();
+  while (Date.now() - start < timeout) {
+    const state = await getDsState(page);
+    if (!state.pendingDs && state.colDataRows > 0) {
+      return state;
+    }
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+  }
+  return getDsState(page);
+}
+
+/** Get chart canvas bounding rect. */
+async function getChartRect(page: import('@playwright/test').Page) {
+  return page.evaluate(() => {
+    const c = document.querySelector('.dh-tvl-chart canvas');
+    if (!c) return { x: 0, y: 0, w: 0, h: 0 };
+    const r = c.getBoundingClientRect();
+    return { x: r.x, y: r.y, w: r.width, h: r.height };
+  });
+}
+
+/** Zoom via wheel events dispatched on the chart canvas, one per frame. */
+async function wheelZoom(
+  page: import('@playwright/test').Page,
+  steps: number,
+  deltaY: number
+) {
+  await page.evaluate(
+    ({ steps: s, deltaY: dy }) =>
+      new Promise<void>(resolve => {
+        const c = document.querySelector('.dh-tvl-chart canvas');
+        if (!c) {
+          resolve();
+          return;
+        }
+        const r = c.getBoundingClientRect();
+        const cx = r.left + r.width / 2;
+        const cy = r.top + r.height / 2;
+        let i = 0;
+        function step() {
+          if (i >= s) {
+            resolve();
+            return;
+          }
+          c!.dispatchEvent(
+            new WheelEvent('wheel', {
+              clientX: cx,
+              clientY: cy,
+              deltaY: dy,
+              deltaMode: 0,
+              bubbles: true,
+              cancelable: true,
+            })
+          );
+          i += 1;
+          requestAnimationFrame(step);
+        }
+        requestAnimationFrame(step);
+      }),
+    { steps, deltaY }
+  );
+}
+
+/** Pan by dragging on the chart body. Negative dx = pan toward later dates. */
+async function panChart(page: import('@playwright/test').Page, dx: number) {
+  const rect = await getChartRect(page);
+  const cy = rect.y + rect.h / 2;
+  const startX = rect.x + rect.w / 2;
+  await page.mouse.move(startX, cy);
+  await page.mouse.down();
+  // Move in steps for LWC to register the drag
+  const steps = 5;
+  for (let i = 1; i <= steps; i += 1) {
+    await page.mouse.move(startX + (dx * i) / steps, cy);
+  }
+  await page.mouse.up();
+}
+
+/**
+ * X-axis zoom by dragging on the time scale row.
+ * LWC uses a TABLE layout; the time axis is a separate TR below the
+ * plot canvas. Positive dx = drag right = zoom out.
+ */
+async function xAxisZoom(page: import('@playwright/test').Page, dx: number) {
+  // Find the time axis canvas (bottom row of LWC's table)
+  const timeAxisY = await page.evaluate(() => {
+    const chart = document.querySelector('.dh-tvl-chart');
+    if (!chart) return 0;
+    // LWC's time axis is in the last table row
+    const rows = chart.querySelectorAll('tr');
+    const lastRow = rows[rows.length - 1];
+    if (!lastRow) return 0;
+    const r = lastRow.getBoundingClientRect();
+    return Math.round(r.top + r.height / 2);
+  });
+  if (timeAxisY === 0) return;
+
+  const rect = await getChartRect(page);
+  const startX = rect.x + rect.w / 2;
+  await page.mouse.move(startX, timeAxisY);
+  await page.mouse.down();
+  const steps = 5;
+  for (let i = 1; i <= steps; i += 1) {
+    await page.mouse.move(startX + (dx * i) / steps, timeAxisY);
+  }
+  await page.mouse.up();
+}
+
+test.describe('TradingView Lightweight - Downsampling Interactions', () => {
+  test.setTimeout(120_000);
+
+  /** Open a chart by name and wait for downsample + settle. */
+  async function openDsChart(
+    page: import('@playwright/test').Page,
+    name = 'tvl_big_line'
+  ): Promise<DsState> {
+    await gotoPage(page, '');
+    await openPanel(page, name);
+    await expect(tvlChart(page)).toBeVisible();
+    const state = await waitForDsReady(page, 30000);
+    // Wait for the 1s settle timer + some buffer for fitContent to complete
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500);
+    return state;
+  }
+
+  // =======================================================================
+  // A. INITIAL LOAD
+  // =======================================================================
+
+  test('10M table: initial load is downsampled at full range', async ({
+    page,
+  }) => {
+    const s = await openDsChart(page);
+    expect(s.jsDs).toBe(true);
+    expect(s.pendingDs).toBe(false);
+    expect(s.colDataRows).toBeGreaterThan(100);
+    expect(s.visRange).not.toBeNull();
+    // Visible range should span a meaningful portion of the data
+    if (s.visRange) {
+      const days = (s.visRange[1] - s.visRange[0]) / 86400;
+      // 10M rows over 10 years — at minimum 30 days visible after fitContent
+      expect(days).toBeGreaterThan(30);
+    }
+  });
+
+  test('small table: NOT downsampled', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_small_line');
+    await expect(tvlChart(page)).toBeVisible();
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(3000);
+    const s = await getDsState(page);
+    expect(s.jsDs).toBe(false);
+  });
+
+  // 10M candlestick is now safe to load: auto-bin aggregates server-side.
+  test('candlestick on big table: NOT JS-downsampled (auto-binned instead)', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_candlestick', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    // The downsample-state attribute is set by the chart's debug hook;
+    // jsDs must remain false because candlestick uses auto-bin instead.
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    const raw = await page.evaluate(() => {
+      const els = Array.from(document.querySelectorAll('.dh-tvl-chart'));
+      const el = els[els.length - 1];
+      return el?.getAttribute('data-tvl-state');
+    });
+    const s = raw ? JSON.parse(raw) : null;
+    expect(s).not.toBeNull();
+    expect(s.jsDs).toBe(false);
+  });
+
+  // =======================================================================
+  // B. ZOOM
+  // =======================================================================
+
+  test('wheel zoom in narrows visible range', async ({ page }) => {
+    const initial = await openDsChart(page);
+
+    // More aggressive zoom to ensure threshold is crossed
+    await wheelZoom(page, 25, -300);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(8000);
+    const zoomed = await waitForDsSettled(page);
+
+    expect(zoomed.pendingDs).toBe(false);
+    expect(zoomed.visRange).not.toBeNull();
+    if (zoomed.visRange && initial.visRange) {
+      const zDur = zoomed.visRange[1] - zoomed.visRange[0];
+      const iDur = initial.visRange[1] - initial.visRange[0];
+      // After 25 zoom steps, visible range should be noticeably narrower
+      expect(zDur).toBeLessThan(iDur);
+    }
+  });
+
+  test('zoom in preserves x-axis center after data swap', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(300);
+    const pre = await getDsState(page);
+
+    const post = await waitForDsSettled(page);
+
+    if (pre.visRange && post.visRange) {
+      const preMid = (pre.visRange[0] + pre.visRange[1]) / 2;
+      const postMid = (post.visRange[0] + post.visRange[1]) / 2;
+      const dur = pre.visRange[1] - pre.visRange[0];
+      expect(Math.abs(postMid - preMid)).toBeLessThan(dur * 0.5);
+    }
+  });
+
+  test('two successive zooms both trigger re-downsample', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 20, -300);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(8000);
+    const first = await waitForDsSettled(page);
+
+    // Wait for suppress to clear
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(1000);
+
+    await wheelZoom(page, 20, -300);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(8000);
+    const second = await waitForDsSettled(page);
+
+    if (second.visRange && first.visRange) {
+      const d2 = second.visRange[1] - second.visRange[0];
+      const d1 = first.visRange[1] - first.visRange[0];
+      expect(d2).toBeLessThan(d1);
+    }
+  });
+
+  test('zoom out widens visible range', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    const zIn = await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    await wheelZoom(page, 15, 200);
+    const zOut = await waitForDsSettled(page);
+
+    if (zOut.visRange && zIn.visRange) {
+      expect(zOut.visRange[1] - zOut.visRange[0]).toBeGreaterThan(
+        zIn.visRange[1] - zIn.visRange[0]
+      );
+    }
+  });
+
+  test('zoom state is stable — no oscillation after settling', async ({
+    page,
+  }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    // Wait generously for zoom debounce + runChartDownsample + data swap
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(8000);
+    const s1 = await waitForDsSettled(page);
+
+    // Now wait and check again — state should not change
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    const s2 = await getDsState(page);
+
+    expect(s2.pendingDs).toBe(false);
+    expect(s2.colDataRows).toBeGreaterThan(0);
+  });
+
+  // =======================================================================
+  // C. DOUBLE-CLICK RESET
+  // =======================================================================
+
+  test('double-click resets to full range after zoom', async ({ page }) => {
+    const initial = await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    const rect = await getChartRect(page);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+    const reset = await waitForDsSettled(page);
+
+    expect(reset.pendingDs).toBe(false);
+    if (reset.visRange && initial.visRange) {
+      const rDur = reset.visRange[1] - reset.visRange[0];
+      const iDur = initial.visRange[1] - initial.visRange[0];
+      expect(rDur).toBeGreaterThan(iDur * 0.7);
+    }
+  });
+
+  test('double-click reliably resets 3 times in a row', async ({ page }) => {
+    const initial = await openDsChart(page);
+    const rect = await getChartRect(page);
+    const initialDur = initial.visRange
+      ? initial.visRange[1] - initial.visRange[0]
+      : 0;
+
+    for (let i = 0; i < 3; i += 1) {
+      // Zoom in
+      await wheelZoom(page, 20, -300);
+      // eslint-disable-next-line playwright/no-wait-for-timeout
+      await page.waitForTimeout(8000);
+      await waitForDsSettled(page);
+
+      // Double-click reset
+      await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+      // eslint-disable-next-line playwright/no-wait-for-timeout
+      await page.waitForTimeout(8000);
+      const reset = await waitForDsSettled(page);
+
+      expect(reset.pendingDs).toBe(false);
+      expect(reset.colDataRows).toBeGreaterThan(0);
+
+      // After reset, range should be at least 50% of the original full range
+      if (reset.visRange && initialDur > 0) {
+        const resetDur = reset.visRange[1] - reset.visRange[0];
+        expect(resetDur).toBeGreaterThan(initialDur * 0.5);
+      }
+    }
+  });
+
+  test('double-click on time axis also resets', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    const zoomed = await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    // Double-click the time axis row
+    const timeAxisY = await page.evaluate(() => {
+      const chart = document.querySelector('.dh-tvl-chart');
+      if (!chart) return 0;
+      const rows = chart.querySelectorAll('tr');
+      const lastRow = rows[rows.length - 1];
+      if (!lastRow) return 0;
+      const r = lastRow.getBoundingClientRect();
+      return Math.round(r.top + r.height / 2);
+    });
+    const rect = await getChartRect(page);
+    if (timeAxisY > 0) {
+      await page.mouse.dblclick(rect.x + rect.w / 2, timeAxisY);
+    }
+    const reset = await waitForDsSettled(page);
+
+    if (reset.visRange && zoomed.visRange) {
+      expect(reset.visRange[1] - reset.visRange[0]).toBeGreaterThan(
+        (zoomed.visRange[1] - zoomed.visRange[0]) * 1.5
+      );
+    }
+  });
+
+  // =======================================================================
+  // D. PAN
+  // =======================================================================
+
+  test('pan shifts visible center', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 20, -300);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(8000);
+    await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(1000);
+    const before = await getDsState(page);
+
+    await panChart(page, -800);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    const after = await waitForDsSettled(page);
+
+    // Pan should shift the visible center — at minimum the range endpoints change
+    expect(after.visRange).not.toBeNull();
+    expect(before.visRange).not.toBeNull();
+    if (before.visRange && after.visRange) {
+      // Either the center shifted or at least one endpoint moved
+      const bStart = before.visRange[0];
+      const aStart = after.visRange[0];
+      expect(aStart).not.toBe(bStart);
+    }
+  });
+
+  test('pan preserves approximate zoom level', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    await waitForDsSettled(page);
+    const before = await getDsState(page);
+
+    await panChart(page, -600);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    const after = await waitForDsSettled(page);
+
+    if (before.visRange && after.visRange) {
+      const bDur = before.visRange[1] - before.visRange[0];
+      const aDur = after.visRange[1] - after.visRange[0];
+      // Duration should be same order of magnitude
+      // (pan + re-downsample may change bar density slightly)
+      expect(aDur).toBeGreaterThan(bDur * 0.3);
+      expect(aDur).toBeLessThan(bDur * 3);
+    }
+  });
+
+  test('3 successive pans do not degenerate data', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    for (let i = 0; i < 3; i += 1) {
+      await panChart(page, -600);
+      await waitForDsSettled(page);
+      // eslint-disable-next-line playwright/no-wait-for-timeout
+      await page.waitForTimeout(500);
+    }
+
+    const s = await getDsState(page);
+    expect(s.pendingDs).toBe(false);
+    expect(s.colDataRows).toBeGreaterThan(500);
+  });
+
+  // =======================================================================
+  // E. X-AXIS DRAG ZOOM
+  // =======================================================================
+
+  test('x-axis drag zoom out widens range and preserves data', async ({
+    page,
+  }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    const zIn = await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    await xAxisZoom(page, 600);
+    const zOut = await waitForDsSettled(page);
+
+    expect(zOut.colDataRows).toBeGreaterThan(500);
+    if (zOut.visRange && zIn.visRange) {
+      expect(zOut.visRange[1] - zOut.visRange[0]).toBeGreaterThan(
+        zIn.visRange[1] - zIn.visRange[0]
+      );
+    }
+  });
+
+  test('x-axis zoom does not jump after data swap', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    await xAxisZoom(page, 600);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(400);
+    const pre = await getDsState(page);
+
+    const post = await waitForDsSettled(page);
+
+    if (pre.visRange && post.visRange) {
+      const preMid = (pre.visRange[0] + pre.visRange[1]) / 2;
+      const postMid = (post.visRange[0] + post.visRange[1]) / 2;
+      const dur = pre.visRange[1] - pre.visRange[0];
+      expect(Math.abs(postMid - preMid)).toBeLessThan(dur);
+    }
+  });
+
+  // =======================================================================
+  // F. TICKING TABLE
+  // =======================================================================
+
+  test('ticking table data grows over time', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_ticking_line');
+    await expect(tvlChart(page)).toBeVisible();
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    const s1 = await getDsState(page);
+
+    // Wait 3 seconds for ticks
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(3000);
+    const s2 = await getDsState(page);
+
+    // Row count should have grown (ticking table appends rows)
+    expect(s2.colDataRows).toBeGreaterThanOrEqual(s1.colDataRows);
+  });
+
+  // =======================================================================
+  // G. RAPID / STRESS INTERACTIONS
+  // =======================================================================
+
+  test('rapid zoom in-out-in settles to valid state', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 10, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(400);
+    await wheelZoom(page, 8, 200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(400);
+    await wheelZoom(page, 12, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(400);
+    await wheelZoom(page, 6, 200);
+
+    const s = await waitForDsSettled(page);
+    expect(s.pendingDs).toBe(false);
+    expect(s.colDataRows).toBeGreaterThan(0);
+    expect(s.visRange).not.toBeNull();
+  });
+
+  test('zoom then immediate double-click resets cleanly', async ({ page }) => {
+    const initial = await openDsChart(page);
+    const rect = await getChartRect(page);
+
+    // Zoom and immediately double-click (no wait for settle)
+    await wheelZoom(page, 12, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+
+    const reset = await waitForDsSettled(page);
+    expect(reset.pendingDs).toBe(false);
+
+    // Should end up at full range, not stuck zoomed
+    if (reset.visRange && initial.visRange) {
+      const rDur = reset.visRange[1] - reset.visRange[0];
+      const iDur = initial.visRange[1] - initial.visRange[0];
+      expect(rDur).toBeGreaterThan(iDur * 0.5);
+    }
+  });
+
+  test('pan then immediate double-click resets cleanly', async ({ page }) => {
+    const initial = await openDsChart(page);
+    const rect = await getChartRect(page);
+
+    await wheelZoom(page, 12, -200);
+    await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    // Pan then immediately reset
+    await panChart(page, -600);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+
+    const reset = await waitForDsSettled(page);
+    expect(reset.pendingDs).toBe(false);
+    if (reset.visRange && initial.visRange) {
+      const rDur = reset.visRange[1] - reset.visRange[0];
+      const iDur = initial.visRange[1] - initial.visRange[0];
+      expect(rDur).toBeGreaterThan(iDur * 0.5);
+    }
+  });
+
+  // =======================================================================
+  // H. STATE CONSISTENCY
+  // =======================================================================
+
+  test('pendingDs never stays stuck true', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 15, -200);
+    // pendingDs may go true briefly
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+
+    // But must settle to false
+    const s = await waitForDsSettled(page, 20000);
+    expect(s.pendingDs).toBe(false);
+  });
+
+  test('colDataRows is always positive after load', async ({ page }) => {
+    await openDsChart(page);
+
+    // Check repeatedly across zoom/pan/reset cycle
+    await wheelZoom(page, 12, -200);
+    let s = await waitForDsSettled(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+    await panChart(page, -400);
+    s = await waitForDsSettled(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+
+    const rect = await getChartRect(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+    s = await waitForDsSettled(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+  });
+
+  test('visRange is never null after initial load', async ({ page }) => {
+    await openDsChart(page);
+
+    await wheelZoom(page, 12, -200);
+    let s = await waitForDsSettled(page);
+    expect(s.visRange).not.toBeNull();
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+    const rect = await getChartRect(page);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+    s = await waitForDsSettled(page);
+    expect(s.visRange).not.toBeNull();
+  });
+
+  // =======================================================================
+  // I. EDGE CASES
+  // =======================================================================
+
+  test('zoom in very deep then reset recovers', async ({ page }) => {
+    const initial = await openDsChart(page);
+    const rect = await getChartRect(page);
+
+    // Deep zoom: 30 steps
+    await wheelZoom(page, 30, -200);
+    await waitForDsSettled(page);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+    const reset = await waitForDsSettled(page);
+
+    expect(reset.pendingDs).toBe(false);
+    expect(reset.colDataRows).toBeGreaterThan(0);
+    if (reset.visRange && initial.visRange) {
+      const rDur = reset.visRange[1] - reset.visRange[0];
+      const iDur = initial.visRange[1] - initial.visRange[0];
+      expect(rDur).toBeGreaterThan(iDur * 0.5);
+    }
+  });
+
+  test('zoom-pan-zoom-reset full lifecycle', async ({ page }) => {
+    const initial = await openDsChart(page);
+    const rect = await getChartRect(page);
+
+    // 1. Zoom in
+    await wheelZoom(page, 12, -200);
+    let s = await waitForDsSettled(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    // 2. Pan
+    await panChart(page, -600);
+    s = await waitForDsSettled(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    // 3. Zoom in more
+    await wheelZoom(page, 8, -200);
+    s = await waitForDsSettled(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(500);
+
+    // 4. Reset
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+    s = await waitForDsSettled(page);
+    expect(s.pendingDs).toBe(false);
+    expect(s.colDataRows).toBeGreaterThan(0);
+
+    if (s.visRange && initial.visRange) {
+      const rDur = s.visRange[1] - s.visRange[0];
+      const iDur = initial.visRange[1] - initial.visRange[0];
+      expect(rDur).toBeGreaterThan(iDur * 0.5);
+    }
+  });
+});
+
+// --------------------------------------------------------------------------
+// Auto-bin (server-side time-bucket aggregation) interactions
+// --------------------------------------------------------------------------
+
+interface TvlState {
+  jsDs: boolean;
+  tableSize: number;
+  colDataRows: number;
+  pendingDs: boolean;
+  visRange: [number, number] | null;
+  autoBin: boolean;
+  binWidthNs: number | null;
+  aggType: string | null;
+  resampleSeq: number;
+}
+
+async function getTvlState(
+  page: import('@playwright/test').Page
+): Promise<TvlState> {
+  return page.evaluate(() => {
+    // Multiple .dh-tvl-chart instances may exist (eg WidgetPanel renders one
+    // hidden + one visible). Pick the last visible one to match what the
+    // user sees and what tvlChart() asserts on.
+    const els = Array.from(document.querySelectorAll('.dh-tvl-chart'));
+    const el = els[els.length - 1];
+    const raw = el?.getAttribute('data-tvl-state');
+    return raw ? JSON.parse(raw) : {};
+  });
+}
+
+async function waitForResampleSettled(
+  page: import('@playwright/test').Page,
+  timeout = 30000
+): Promise<TvlState> {
+  const start = Date.now();
+  // Require a stable state for two consecutive samples to avoid catching a
+  // transient pending=false between back-to-back rebuilds.
+  let prev: TvlState | null = null;
+  while (Date.now() - start < timeout) {
+    const s = await getTvlState(page);
+    if (
+      !s.pendingDs &&
+      s.colDataRows > 0 &&
+      prev !== null &&
+      !prev.pendingDs &&
+      prev.binWidthNs === s.binWidthNs &&
+      prev.colDataRows === s.colDataRows &&
+      prev.resampleSeq === s.resampleSeq
+    ) {
+      return s;
+    }
+    prev = s;
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(300);
+  }
+  return getTvlState(page);
+}
+
+async function waitForBinWidthChange(
+  page: import('@playwright/test').Page,
+  prevWidth: number | null,
+  timeout = 15000
+): Promise<TvlState> {
+  const start = Date.now();
+  while (Date.now() - start < timeout) {
+    const s = await getTvlState(page);
+    if (s.binWidthNs !== prevWidth && !s.pendingDs && s.colDataRows > 0) {
+      return s;
+    }
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+  }
+  return getTvlState(page);
+}
+
+const NICE_BIN_WIDTHS_NS = [
+  1, 100, 1_000, 100_000, 1_000_000, 10_000_000, 100_000_000, 1_000_000_000,
+  5_000_000_000, 15_000_000_000, 30_000_000_000, 60_000_000_000,
+  300_000_000_000, 900_000_000_000, 1_800_000_000_000, 3_600_000_000_000,
+  14_400_000_000_000, 43_200_000_000_000, 86_400_000_000_000,
+  604_800_000_000_000,
+];
+
+test.describe('TradingView Lightweight - Auto-bin', () => {
+  test.setTimeout(120_000);
+
+  // ===== Group 1 — Eligibility =====
+
+  test('big histogram triggers auto-bin', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    const s = await waitForResampleSettled(page);
+    expect(s.autoBin).toBe(true);
+    expect(s.aggType).toBe('sum');
+    expect(s.binWidthNs).not.toBeNull();
+    if (s.binWidthNs != null) expect(s.binWidthNs).toBeGreaterThan(0);
+  });
+
+  test('big candlestick (4 distinct OHLC cols) triggers auto-bin', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_candlestick');
+    await expect(tvlChart(page)).toBeVisible();
+    const s = await waitForResampleSettled(page);
+    expect(s.autoBin).toBe(true);
+    expect(s.aggType).toBe('ohlc');
+  });
+
+  test('small histogram is NOT auto-binned', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_small_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(3000);
+    const s = await getTvlState(page);
+    expect(s.autoBin).toBe(false);
+    expect(s.binWidthNs).toBeNull();
+  });
+
+  test('auto_bin=False opts out', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist_optout');
+    await expect(tvlChart(page)).toBeVisible();
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(3000);
+    const s = await getTvlState(page);
+    expect(s.autoBin).toBe(false);
+  });
+
+  test('count aggregation propagates to aggType', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist_count');
+    await expect(tvlChart(page)).toBeVisible();
+    const s = await waitForResampleSettled(page);
+    expect(s.autoBin).toBe(true);
+    expect(s.aggType).toBe('count');
+  });
+
+  // ===== Group 2 — Bin-width snapping =====
+
+  test('initial bin_width snaps to a "nice" duration', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    const s = await waitForResampleSettled(page);
+    expect(s.binWidthNs).not.toBeNull();
+    expect(NICE_BIN_WIDTHS_NS).toContain(s.binWidthNs);
+  });
+
+  test('bin_width=PT5M overrides nice snapping', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist_pt5m', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const s = await waitForResampleSettled(page);
+    expect(s.binWidthNs).toBe(5 * 60 * 1_000_000_000);
+  });
+
+  test('bin_count=200 narrows the bin width', async ({ page }) => {
+    // With bin_count=200 over 10 years, bins are coarser than the default 5000.
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const a = await waitForResampleSettled(page);
+
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist_bc200', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const b = await waitForResampleSettled(page);
+
+    expect(a.binWidthNs).not.toBeNull();
+    expect(b.binWidthNs).not.toBeNull();
+    if (a.binWidthNs != null && b.binWidthNs != null) {
+      expect(b.binWidthNs).toBeGreaterThan(a.binWidthNs);
+    }
+  });
+
+  // ===== Group 3 — Re-aggregation trigger =====
+
+  test('zoom past MIN_VISIBLE_BINS triggers re-aggregation', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const initial = await waitForResampleSettled(page);
+    expect(initial.binWidthNs).not.toBeNull();
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500); // settle delay
+    // Zoom hard enough to drop below MIN_VISIBLE_BINS for 1-day bins.
+    await wheelZoom(page, 60, -300);
+    const next = await waitForBinWidthChange(page, initial.binWidthNs, 30000);
+    expect(next.binWidthNs).not.toBeNull();
+    if (initial.binWidthNs != null && next.binWidthNs != null) {
+      expect(next.binWidthNs).toBeLessThan(initial.binWidthNs);
+    }
+  });
+
+  test('double-click reset reverts to initial bin_width', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const initial = await waitForResampleSettled(page);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500);
+    await wheelZoom(page, 60, -300);
+    await waitForBinWidthChange(page, initial.binWidthNs, 30000);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(1500);
+    // Synthesize a dblclick on the canvas so the chart's container-level
+    // listener fires reliably across browsers.
+    await page.evaluate(() => {
+      const canvas = document.querySelector(
+        '.dh-tvl-chart canvas'
+      ) as HTMLElement | null;
+      if (!canvas) return;
+      const r = canvas.getBoundingClientRect();
+      canvas.dispatchEvent(
+        new MouseEvent('dblclick', {
+          clientX: r.left + r.width / 2,
+          clientY: r.top + r.height / 2,
+          bubbles: true,
+          cancelable: true,
+          detail: 2,
+        })
+      );
+    });
+
+    const restored = await waitForResampleSettled(page, 30000);
+    expect(restored.binWidthNs).toBe(initial.binWidthNs);
+  });
+
+  test('rapid zooms increment resampleSeq monotonically', async ({ page }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const initial = await waitForResampleSettled(page);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500);
+    // Three bursts of significant zoom — enough to cross MIN_VISIBLE_BINS
+    for (let i = 0; i < 3; i += 1) {
+      await wheelZoom(page, 25, -250);
+      // eslint-disable-next-line playwright/no-wait-for-timeout
+      await page.waitForTimeout(300);
+    }
+    const settled = await waitForResampleSettled(page, 30000);
+    expect(settled.resampleSeq).toBeGreaterThan(initial.resampleSeq);
+    expect(settled.pendingDs).toBe(false);
+  });
+
+  // ===== Group 4 — Race conditions =====
+
+  test('5 rapid zooms produce a single monotonically-narrowing settled state', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const initial = await waitForResampleSettled(page);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500);
+    for (let i = 0; i < 5; i += 1) {
+      await wheelZoom(page, 12, -250);
+      // eslint-disable-next-line playwright/no-wait-for-timeout
+      await page.waitForTimeout(120);
+    }
+
+    const settled = await waitForResampleSettled(page, 30000);
+    expect(settled.pendingDs).toBe(false);
+    if (initial.binWidthNs != null && settled.binWidthNs != null) {
+      // Bin width must be ≤ initial — never bounce back coarser during zoom-in
+      expect(settled.binWidthNs).toBeLessThanOrEqual(initial.binWidthNs);
+    }
+
+    // Sample state every 250ms for 2.5s — binWidthNs must stop bouncing.
+    // Allow at most one transition (in case a queued resample drains in.)
+    const widths: (number | null)[] = [];
+    for (let i = 0; i < 10; i += 1) {
+      const s = await getTvlState(page);
+      widths.push(s.binWidthNs);
+      // eslint-disable-next-line playwright/no-wait-for-timeout
+      await page.waitForTimeout(250);
+    }
+    const distinct = new Set(widths.filter(w => w != null));
+    expect(distinct.size).toBeLessThanOrEqual(2);
+  });
+
+  test('zoom then immediate reset within debounce window settles to initial', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const initial = await waitForResampleSettled(page);
+    const rect = await getChartRect(page);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500);
+    await wheelZoom(page, 12, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(200);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+
+    const reset = await waitForResampleSettled(page);
+    expect(reset.pendingDs).toBe(false);
+    expect(reset.binWidthNs).toBe(initial.binWidthNs);
+  });
+
+  test('pan during in-flight zoom does not produce empty data', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    await waitForResampleSettled(page);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(2500);
+    await wheelZoom(page, 15, -200);
+    // Pan immediately, before settle
+    await panChart(page, -300);
+
+    const settled = await waitForResampleSettled(page);
+    expect(settled.colDataRows).toBeGreaterThan(0);
+    expect(settled.pendingDs).toBe(false);
+  });
+
+  // ===== Group 5 — Mixed series + edge data =====
+
+  test('Line + Histogram on same source: both routed correctly', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_mixed_line_hist', '.dh-panel', false);
+    await expect(tvlChart(page)).toBeVisible();
+    const s = await waitForResampleSettled(page);
+    expect(s.autoBin).toBe(true);
+    expect(s.jsDs).toBe(true);
+    expect(s.pendingDs).toBe(false);
+    expect(s.colDataRows).toBeGreaterThan(0);
+  });
+
+  // ===== Group 6 — Ticking + snap-to-live =====
+
+  test('ticking histogram: aggregated view reflects new ticks', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_ticking_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+    const s1 = await getTvlState(page);
+
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(4000);
+    const s2 = await getTvlState(page);
+
+    // colDataRows should not shrink as new ticks land
+    expect(s2.colDataRows).toBeGreaterThanOrEqual(s1.colDataRows);
+  });
+
+  test('ticking histogram: panning right does not break aggregation', async ({
+    page,
+  }) => {
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_ticking_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(5000);
+
+    await panChart(page, -200);
+    // eslint-disable-next-line playwright/no-wait-for-timeout
+    await page.waitForTimeout(3000);
+    const s = await getTvlState(page);
+    expect(s.colDataRows).toBeGreaterThan(0);
+    expect(s.pendingDs).toBe(false);
+  });
+
+  // ===== Group 7 — Performance smoke =====
+
+  test('big histogram initial settle in under 30s', async ({ page }) => {
+    const t0 = Date.now();
+    await gotoPage(page, '');
+    await openPanel(page, 'tvl_big_hist');
+    await expect(tvlChart(page)).toBeVisible();
+    await waitForResampleSettled(page, 30000);
+    const dt = Date.now() - t0;
+    expect(dt).toBeLessThan(30000);
+  });
+});
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diff --git a/tests/tradingview_lightweight_autobin.spec.ts b/tests/tradingview_lightweight_autobin.spec.ts
new file mode 100644
index 000000000..aa55147fa
--- /dev/null
+++ b/tests/tradingview_lightweight_autobin.spec.ts
@@ -0,0 +1,180 @@
+import { expect, test, type Page } from '@playwright/test';
+import { openPanel, gotoPage } from './utils';
+
+// --------------------------------------------------------------------------
+// Auto-bin spec: verifies that server-side time-bin aggregation correctly
+// scopes to the visible window, picks chunky bin widths, and rebuilds when
+// the user pans past the cached buffer.
+// --------------------------------------------------------------------------
+
+interface AutoBinState {
+  jsDs: boolean;
+  tableSize: number;
+  colDataRows: number;
+  pendingDs: boolean;
+  visRange: [number, number] | null;
+  autoBin: boolean;
+  binWidthNs: number | null;
+  aggType: string | null;
+  rangeNs: [number, number] | null;
+  resampleSeq: number;
+}
+
+const tvlChart = (page: Page) => page.locator('.dh-tvl-chart').last();
+
+async function getState(page: Page): Promise<AutoBinState> {
+  return page.evaluate(() => {
+    const charts = document.querySelectorAll('.dh-tvl-chart');
+    const last = charts[charts.length - 1];
+    const raw = last?.getAttribute('data-tvl-state');
+    return raw ? JSON.parse(raw) : {};
+  });
+}
+
+async function waitForSettled(
+  page: Page,
+  predicate: (s: AutoBinState) => boolean,
+  timeout = 20000
+): Promise<AutoBinState> {
+  const start = Date.now();
+  while (Date.now() - start < timeout) {
+    const s = await getState(page);
+    if (!s.pendingDs && s.colDataRows > 0 && predicate(s)) return s;
+    await page.waitForTimeout(150);
+  }
+  return getState(page);
+}
+
+async function getChartCanvasRect(page: Page) {
+  return page.evaluate(() => {
+    const charts = document.querySelectorAll('.dh-tvl-chart');
+    const last = charts[charts.length - 1];
+    const c = last?.querySelector('canvas');
+    if (!c) return { x: 0, y: 0, w: 0, h: 0 };
+    const r = c.getBoundingClientRect();
+    return { x: r.x, y: r.y, w: r.width, h: r.height };
+  });
+}
+
+/** Open the named panel and wait through the 1s settle + mount-time RESET. */
+async function openAutoBinChart(page: Page, name: string): Promise<AutoBinState> {
+  await gotoPage(page, '');
+  await openPanel(page, name);
+  await expect(tvlChart(page)).toBeVisible();
+  // Wait for autoBin to come up.
+  await waitForSettled(page, s => s.autoBin === true, 30000);
+  // 1s settle + a safety margin so the mount-time AUTOBIN_RESET has landed.
+  await page.waitForTimeout(2500);
+  return getState(page);
+}
+
+/** Dispatch a stream of wheel events on the chart canvas (zoom in/out). */
+async function wheelZoom(page: Page, steps: number, deltaY: number) {
+  await page.evaluate(
+    ({ steps: s, deltaY: dy }) =>
+      new Promise<void>(resolve => {
+        const charts = document.querySelectorAll('.dh-tvl-chart canvas');
+        const c = charts[charts.length - 1];
+        if (!c) {
+          resolve();
+          return;
+        }
+        const r = c.getBoundingClientRect();
+        const cx = r.left + r.width / 2;
+        const cy = r.top + r.height / 2;
+        let i = 0;
+        function step() {
+          if (i >= s) {
+            resolve();
+            return;
+          }
+          c.dispatchEvent(
+            new WheelEvent('wheel', {
+              clientX: cx,
+              clientY: cy,
+              deltaY: dy,
+              deltaMode: 0,
+              bubbles: true,
+              cancelable: true,
+            })
+          );
+          i += 1;
+          requestAnimationFrame(step);
+        }
+        requestAnimationFrame(step);
+      }),
+    { steps, deltaY }
+  );
+}
+
+test.describe('TradingView Lightweight - Auto-bin', () => {
+  test('histogram triggers auto-bin on a large source', async ({ page }) => {
+    const settled = await openAutoBinChart(page, 'tvl_big_hist');
+    expect(settled.autoBin).toBe(true);
+    expect(settled.aggType).toBe('sum');
+    expect(settled.binWidthNs).toBeGreaterThan(0);
+    expect(settled.rangeNs).toBeNull(); // initial = full source
+  });
+
+  test('initial bars are visually chunky (>=3 px each)', async ({ page }) => {
+    const settled = await openAutoBinChart(page, 'tvl_big_hist');
+    const rect = await getChartCanvasRect(page);
+    // tableSize is total bins in the aggregated table; at full source extent
+    // (rangeNs=null) all of them sit across the canvas, so canvas_w / count
+    // is barSpacing in pixels.
+    expect(settled.tableSize).toBeGreaterThan(0);
+    const barSpacing = rect.w / settled.tableSize;
+    expect(barSpacing).toBeGreaterThanOrEqual(3.0);
+  });
+
+  test('zoom-in scopes the aggregated table to the visible window', async ({
+    page,
+  }) => {
+    const initial = await openAutoBinChart(page, 'tvl_big_hist');
+    expect(initial.rangeNs).toBeNull();
+
+    // Aggressive zoom-in: many wheel-up frames.
+    await wheelZoom(page, 30, -300);
+    await page.waitForTimeout(8000);
+
+    const zoomed = await waitForSettled(page, s => s.rangeNs !== null);
+    expect(zoomed.rangeNs).not.toBeNull();
+    if (zoomed.rangeNs && initial.binWidthNs != null) {
+      // Aggregated window narrower than full source.
+      const fromNs = zoomed.rangeNs[0];
+      const toNs = zoomed.rangeNs[1];
+      expect(toNs - fromNs).toBeGreaterThan(0);
+    }
+    expect(zoomed.resampleSeq).toBeGreaterThan(initial.resampleSeq);
+  });
+
+  test('after a zoom, bars in the visible window remain chunky', async ({
+    page,
+  }) => {
+    await openAutoBinChart(page, 'tvl_big_hist');
+    await wheelZoom(page, 30, -300);
+    await page.waitForTimeout(8000);
+    const zoomed = await waitForSettled(page, s => s.rangeNs !== null);
+    expect(zoomed.rangeNs).not.toBeNull();
+    const rect = await getChartCanvasRect(page);
+    // After scoping, the aggregated table covers ~the visible window plus
+    // a 50% buffer on each side. So tableSize bars in canvas_w pixels.
+    const barSpacing = rect.w / zoomed.tableSize;
+    expect(barSpacing).toBeGreaterThanOrEqual(2.0);
+  });
+
+  test('reset (dblclick) returns to full source', async ({ page }) => {
+    await openAutoBinChart(page, 'tvl_big_hist');
+    await wheelZoom(page, 30, -300);
+    await page.waitForTimeout(8000);
+    const zoomed = await waitForSettled(page, s => s.rangeNs !== null);
+    expect(zoomed.rangeNs).not.toBeNull();
+
+    const rect = await getChartCanvasRect(page);
+    await page.mouse.dblclick(rect.x + rect.w / 2, rect.y + rect.h / 2);
+    await page.waitForTimeout(2500);
+
+    const reset = await waitForSettled(page, s => s.rangeNs === null);
+    expect(reset.rangeNs).toBeNull();
+  });
+});
diff --git a/tests/tradingview_lightweight_bar_width.spec.ts b/tests/tradingview_lightweight_bar_width.spec.ts
new file mode 100644
index 000000000..03a71a2dd
--- /dev/null
+++ b/tests/tradingview_lightweight_bar_width.spec.ts
@@ -0,0 +1,279 @@
+/**
+ * Diagnostic spec: figure out what conditions produce visually fat
+ * histogram bars vs 1-pixel slivers in LWC v5.
+ *
+ * Each test loads a different fixture, then reads the canvas pixel data
+ * to measure the median rendered bar width (run-length of bright green
+ * columns). The point is to test hypotheses, not just assert success.
+ */
+import { expect, test, type Page } from '@playwright/test';
+import { openPanel, gotoPage } from './utils';
+
+interface BarStats {
+  canvasW: number;
+  canvasH: number;
+  barCount: number;
+  medianBarWidth: number;
+  meanBarWidth: number;
+  medianGap: number;
+  visLogical: { from: number; to: number } | null;
+  barSpacing: number;
+  seriesDataLen: number;
+}
+
+async function measureHistogramBars(
+  page: Page,
+  panelTitle: string
+): Promise<BarStats> {
+  return page.evaluate(name => {
+    const charts = document.querySelectorAll('.dh-tvl-chart');
+    let chart: Element | null = null;
+    for (const c of charts) {
+      let p: Element | null = c;
+      while (p && !p.classList?.contains('lm_item')) {
+        p = p.parentElement;
+      }
+      const t = p?.querySelector('.lm_title')?.textContent;
+      if (t && t.trim() === name) {
+        chart = c;
+        break;
+      }
+    }
+    if (!chart) {
+      throw new Error(`panel not found: ${name}`);
+    }
+
+    // Find the canvas with the most green pixels (= histogram pane).
+    const canvases = chart.querySelectorAll('canvas');
+    let target: HTMLCanvasElement | null = null;
+    let maxGreen = 0;
+    for (const c of canvases) {
+      const cv = c as HTMLCanvasElement;
+      if (cv.width <= 200 || cv.height < 30) continue;
+      const ctx = cv.getContext('2d', { willReadFrequently: true });
+      if (!ctx) continue;
+      // Sample one row near the bottom 20%
+      const y = Math.floor(cv.height * 0.8);
+      let greenCount = 0;
+      try {
+        const img = ctx.getImageData(0, y, cv.width, 1);
+        for (let x = 0; x < cv.width; x++) {
+          if (img.data[x * 4 + 1] >= 150) greenCount++;
+        }
+      } catch {
+        continue;
+      }
+      if (greenCount > maxGreen) {
+        maxGreen = greenCount;
+        target = cv;
+      }
+    }
+    if (!target) {
+      throw new Error(`no canvas with green pixels found (canvases: ${canvases.length})`);
+    }
+
+    const ctx = target.getContext('2d', { willReadFrequently: true });
+    if (!ctx) {
+      throw new Error('no ctx');
+    }
+    const w = target.width;
+    const h = target.height;
+
+    // Bars are vertical green strokes. Sample a y where most bars are likely
+    // present (~20% from the bottom of the canvas).
+    const y = Math.floor(h * 0.8);
+    const img = ctx.getImageData(0, y, w, 1);
+
+    // Bright = green channel >= 150 (the histogram color is [155,217,108]).
+    const widths: number[] = [];
+    const gaps: number[] = [];
+    let runStart = -1;
+    let lastEnd = -1;
+    for (let x = 0; x <= w; x++) {
+      const idx = x < w ? x * 4 : -1;
+      const green = idx >= 0 ? img.data[idx + 1] : 0;
+      const isBar = green >= 150;
+      if (isBar && runStart < 0) {
+        runStart = x;
+        if (lastEnd >= 0) gaps.push(x - lastEnd);
+      } else if (!isBar && runStart >= 0) {
+        widths.push(x - runStart);
+        lastEnd = x;
+        runStart = -1;
+      }
+    }
+    widths.sort((a, b) => a - b);
+    gaps.sort((a, b) => a - b);
+
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const reg = (globalThis as any).__tvl_charts ?? [];
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    let matched: any = null;
+    for (const c of reg) {
+      const t = c?.container?.parentElement;
+      if (t?.querySelector?.('.lm_title')?.textContent?.trim() === name) {
+        matched = c;
+        break;
+      }
+    }
+    let visLogical: { from: number; to: number } | null = null;
+    let barSpacing = 0;
+    let seriesDataLen = 0;
+    try {
+      const ts = matched?.renderer?.getChart()?.timeScale();
+      visLogical = ts?.getVisibleLogicalRange() ?? null;
+      barSpacing = ts?.options()?.barSpacing ?? 0;
+      const sm = matched?.renderer?.seriesMap;
+      if (sm) {
+        for (const s of sm.values()) {
+          const d = s.data();
+          if (d.length > seriesDataLen) seriesDataLen = d.length;
+        }
+      }
+    } catch {
+      /* ignore */
+    }
+
+    return {
+      canvasW: w,
+      canvasH: h,
+      barCount: widths.length,
+      medianBarWidth: widths[Math.floor(widths.length / 2)] ?? 0,
+      meanBarWidth:
+        widths.length > 0
+          ? widths.reduce((s, v) => s + v, 0) / widths.length
+          : 0,
+      medianGap: gaps[Math.floor(gaps.length / 2)] ?? 0,
+      visLogical,
+      barSpacing,
+      seriesDataLen,
+    };
+  }, panelTitle);
+}
+
+async function waitForBars(
+  page: Page,
+  panelTitle: string,
+  timeout = 30000
+): Promise<BarStats> {
+  const start = Date.now();
+  while (Date.now() - start < timeout) {
+    try {
+      const s = await measureHistogramBars(page, panelTitle);
+      if (s.barCount > 0) return s;
+    } catch {
+      /* not ready */
+    }
+    await page.waitForTimeout(200);
+  }
+  return measureHistogramBars(page, panelTitle);
+}
+
+// Hypothesis 1: A solo histogram with low bin count will render fat bars.
+// This is the CONTROL — establishes what "fat" looks like in our environment.
+test('H1: solo histogram, ~10 bins on a wide chart renders fat bars', async ({
+  page,
+}) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_histogram');
+  // tvl_histogram has 10 rows of static data
+  const s = await waitForBars(page, 'tvl_histogram');
+  console.log('H1 stats:', JSON.stringify(s));
+  expect(s.barCount).toBeGreaterThan(0);
+  // Hypothesis: bars >= 4 px wide.
+  expect(s.medianBarWidth).toBeGreaterThanOrEqual(4);
+});
+
+// Hypothesis 2: A multi-series chart sharing one source table where the
+// histogram and line are at the same timestamps still renders fat bars.
+test('H2: candlestick + volume histogram (existing fixture) bar width', async ({
+  page,
+}) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_candlestick_with_volume');
+  const s = await waitForBars(page, 'tvl_candlestick_with_volume');
+  console.log('H2 stats:', JSON.stringify(s));
+  // Just collect data — don't assert. The test always passes; we print.
+});
+
+// Hypothesis 3: tvl_big_hist (10M-row autobin path) renders fat bars.
+test('H3: tvl_big_hist autobin path bar width', async ({ page }) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_big_hist');
+  await page.waitForTimeout(3000); // settle + mount-time RESET
+  const s = await waitForBars(page, 'tvl_big_hist');
+  console.log('H3 stats:', JSON.stringify(s));
+});
+
+// Hypothesis 4: tvl_mixed_line_hist (line+histogram on big_table, autobin)
+// renders fat bars. Same shape as Sizzle Price+Volume but in a single pane.
+test('H4: tvl_mixed_line_hist single-pane line+histogram bar width', async ({
+  page,
+}) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_mixed_line_hist');
+  await page.waitForTimeout(3000);
+  const s = await waitForBars(page, 'tvl_mixed_line_hist');
+  console.log('H4 stats:', JSON.stringify(s));
+});
+
+// Hypothesis 5: tvl_panes_basic (candlestick + histogram in TWO panes,
+// static data) renders fat bars.
+test('H5: tvl_panes_basic two-pane chart, static data bar width', async ({
+  page,
+}) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_panes_basic');
+  await page.waitForTimeout(3000);
+  const s = await waitForBars(page, 'tvl_panes_basic');
+  console.log('H5 stats:', JSON.stringify(s));
+});
+
+// Hypothesis 6: area + autobin volume histogram in TWO PANES on BIG data.
+// This is the exact shape of the failing Sizzle Price+Volume panel.
+test('H6: big area+histogram in 2 panes (Sizzle PV shape) bar width', async ({
+  page,
+}) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_big_area_volume_panes');
+  await page.waitForTimeout(4000);
+  const s = await waitForBars(page, 'tvl_big_area_volume_panes');
+  console.log('H6 stats:', JSON.stringify(s));
+});
+
+// Hypothesis 7: area + histogram on a FILTERED table (where("Sym=AAPL")).
+// Sizzle uses .where() to filter sym_data. This test isolates whether
+// .where() vs static raw is what's causing the rendering issue.
+test('H7: filtered table area+histogram bar width', async ({ page }) => {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_diag_filtered_panes');
+  await page.waitForTimeout(4000);
+  const s = await waitForBars(page, 'tvl_diag_filtered_panes');
+  console.log('H7 stats:', JSON.stringify(s));
+});
+
+// Hypothesis 8: Sizzle dashboard's Price+Volume panel rendered WITHIN
+// the dashboard layout. This is the user's actual failing scenario.
+test('H8: sizzle dashboard Price+Volume panel bar width', async ({
+  page,
+}) => {
+  await page.setViewportSize({ width: 1920, height: 1080 });
+  await gotoPage(page, '');
+  const appPanels = page.getByRole('button', { name: 'Panels', exact: true });
+  await appPanels.click();
+  const search = page.getByRole('searchbox', {
+    name: 'Find Table, Plot or Widget',
+    exact: true,
+  });
+  await search.fill('sizzle');
+  await page.getByRole('button', { name: 'sizzle', exact: true }).click();
+  await page.mouse.move(0, 0);
+  await page.waitForTimeout(12000);
+  // Take a screenshot for inspection
+  await page.screenshot({
+    path: '/home/sandbox/deephaven-plugins/plugins/tradingview-lightweight/notes/proof/H8_sizzle_dashboard.png',
+    fullPage: false,
+  });
+  const s = await waitForBars(page, 'Price + Volume');
+  console.log('H8 stats:', JSON.stringify(s));
+});
diff --git a/tests/tradingview_lightweight_events.spec.ts b/tests/tradingview_lightweight_events.spec.ts
new file mode 100644
index 000000000..be20a2036
--- /dev/null
+++ b/tests/tradingview_lightweight_events.spec.ts
@@ -0,0 +1,231 @@
+import { expect, test, type Page } from '@playwright/test';
+import { openPanel, gotoPage } from './utils';
+
+// --------------------------------------------------------------------------
+// Press-event spec. Uses an inversion-oracle: we independently compute the
+// click pixel for a known (time, price) via the chart's own coordinate
+// conversion (exposed on window.__tvlTestHook), click it with real mouse
+// input, then read the built payload from the `data-tvl-last-event` seam and
+// assert LWC's native hit test agrees with our computed pixel.
+//
+// Fixture: tests/app.d/tvl_events.py — a `by=` line chart, partition A ~= 10
+// and B ~= 90 at time T, magnet crosshair, on_press wired to append each
+// event into the `tvl_events_result` table.
+// --------------------------------------------------------------------------
+
+// 2024-06-03T10:00:00 ET == 14:00:00 UTC == 1717423200 (epoch seconds, UTC).
+const T_UTC_SEC = 1717423200;
+const PRICE_A = 10;
+const PRICE_B = 90;
+
+const tvlChart = (page: Page) => page.locator('.dh-tvl-chart').last();
+
+interface LastEvent {
+  type: string;
+  timeNs?: number;
+  seriesId?: string;
+  price?: number;
+  seriesData: Record<string, number | { open: number }>;
+  point?: { x: number; y: number };
+  paneIndex?: number;
+  shiftKey: boolean;
+  ctrlKey: boolean;
+  metaKey: boolean;
+  altKey: boolean;
+}
+
+async function getCanvasRect(page: Page) {
+  return page.evaluate(() => {
+    const charts = document.querySelectorAll('.dh-tvl-chart');
+    const last = charts[charts.length - 1];
+    const c = last?.querySelector('canvas');
+    if (!c) return { x: 0, y: 0, w: 0, h: 0 };
+    const r = c.getBoundingClientRect();
+    return { x: r.x, y: r.y, w: r.width, h: r.height };
+  });
+}
+
+async function getLastEvent(page: Page): Promise<LastEvent | null> {
+  return page.evaluate(() => {
+    const charts = document.querySelectorAll('.dh-tvl-chart');
+    const last = charts[charts.length - 1];
+    const raw = last?.getAttribute('data-tvl-last-event');
+    return raw ? JSON.parse(raw) : null;
+  });
+}
+
+/**
+ * Compute the page pixel for a known (series, UTC-time, price). The hook's
+ * timeToCoordinateUtc applies the same session-tz shift the data went through
+ * (via the app's convertTime), so this works regardless of session timezone;
+ * magnet snapping then lands the click exactly on the nearest data point.
+ */
+async function computeClickPixel(
+  page: Page,
+  seriesId: string,
+  price: number
+): Promise<{ x: number; y: number } | null> {
+  const rect = await getCanvasRect(page);
+  const local = await page.evaluate(
+    ({ id, p, t }) => {
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      const hook = (window as any).__tvlTestHook;
+      if (!hook) return null;
+      return {
+        x: hook.timeToCoordinateUtc(t),
+        y: hook.priceToCoordinate(id, p),
+      };
+    },
+    { id: seriesId, p: price, t: T_UTC_SEC }
+  );
+  if (!local || local.x == null || local.y == null) return null;
+  return { x: rect.x + local.x, y: rect.y + local.y };
+}
+
+async function getSeriesIds(page: Page): Promise<string[]> {
+  return page.evaluate(() => {
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const hook = (window as any).__tvlTestHook;
+    return hook ? hook.getSeriesIds() : [];
+  });
+}
+
+async function openEventsChart(page: Page) {
+  await gotoPage(page, '');
+  await openPanel(page, 'tvl_events_chart');
+  await expect(tvlChart(page)).toBeVisible();
+  // Let the chart settle (fitContent / initial data) and the test hook mount.
+  await page.waitForTimeout(2500);
+  await expect
+    .poll(async () => (await getSeriesIds(page)).length, { timeout: 20000 })
+    .toBeGreaterThanOrEqual(2);
+}
+
+test.describe('TradingView Lightweight - Press events', () => {
+  test('press on series A reports series A and price ~10', async ({ page }) => {
+    await openEventsChart(page);
+    const ids = await getSeriesIds(page);
+    const target = await computeClickPixel(page, ids[0], PRICE_A);
+    expect(target).not.toBeNull();
+    if (!target) return;
+
+    await page.mouse.click(target.x, target.y);
+    await page.waitForTimeout(500);
+
+    const evt = await getLastEvent(page);
+    expect(evt).not.toBeNull();
+    expect(evt!.type).toBe('press');
+    expect(evt!.seriesId).toBeTruthy();
+    // The hit series' value at the pressed time must be ~10 (not ~90).
+    const hitValue = evt!.seriesData[evt!.seriesId as string];
+    expect(typeof hitValue === 'number' ? hitValue : NaN).toBeCloseTo(PRICE_A, 0);
+  });
+
+  test('series A vs B disambiguation', async ({ page }) => {
+    await openEventsChart(page);
+    const ids = await getSeriesIds(page);
+
+    // Returns the hit series' value for the latest press, or null.
+    const hitValue = async (): Promise<number | null> => {
+      const e = await getLastEvent(page);
+      if (!e || !e.seriesId) return null;
+      const v = e.seriesData[e.seriesId];
+      return typeof v === 'number' ? v : null;
+    };
+
+    // Press A, then move the cursor away and pause well past the double-click
+    // window so the B press is a distinct single press (two clicks at the same
+    // x in quick succession would coalesce into a double-click).
+    const aPixel = await computeClickPixel(page, ids[0], PRICE_A);
+    await page.mouse.click(aPixel!.x, aPixel!.y);
+    await expect.poll(hitValue).toBeCloseTo(PRICE_A, 0);
+    const aEvt = await getLastEvent(page);
+
+    await page.mouse.move(0, 0);
+    await page.waitForTimeout(800);
+
+    const bPixel = await computeClickPixel(page, ids[0], PRICE_B);
+    await page.mouse.click(bPixel!.x, bPixel!.y);
+    await expect.poll(hitValue).toBeCloseTo(PRICE_B, 0);
+    const bEvt = await getLastEvent(page);
+
+    expect(aEvt!.seriesId).toBeTruthy();
+    expect(bEvt!.seriesId).toBeTruthy();
+    expect(aEvt!.seriesId).not.toBe(bEvt!.seriesId);
+    expect(aEvt!.seriesData[aEvt!.seriesId as string]).toBeCloseTo(PRICE_A, 0);
+    expect(bEvt!.seriesData[bEvt!.seriesId as string]).toBeCloseTo(PRICE_B, 0);
+  });
+
+  test('pressed time matches T', async ({ page }) => {
+    await openEventsChart(page);
+    const ids = await getSeriesIds(page);
+    const target = await computeClickPixel(page, ids[0], PRICE_A);
+    await page.mouse.click(target!.x, target!.y);
+    await page.waitForTimeout(500);
+
+    const evt = await getLastEvent(page);
+    expect(evt!.timeNs).toBeDefined();
+    // timeNs is UTC nanoseconds; within one day of T (magnet may snap to an
+    // adjacent sample, all of which are 1 day apart at 10:00 ET).
+    const evtSec = (evt!.timeNs as number) / 1e9;
+    expect(Math.abs(evtSec - T_UTC_SEC)).toBeLessThan(2 * 24 * 3600);
+  });
+
+  test('shift-click sets shiftKey', async ({ page }) => {
+    await openEventsChart(page);
+    const ids = await getSeriesIds(page);
+    const target = await computeClickPixel(page, ids[0], PRICE_A);
+    await page.keyboard.down('Shift');
+    await page.mouse.click(target!.x, target!.y);
+    await page.keyboard.up('Shift');
+    await page.waitForTimeout(500);
+
+    const evt = await getLastEvent(page);
+    expect(evt!.shiftKey).toBe(true);
+  });
+
+  test('empty-area press omits time and series', async ({ page }) => {
+    await openEventsChart(page);
+    const rect = await getCanvasRect(page);
+    // Top-left corner: above both lines, outside any data point.
+    await page.mouse.click(rect.x + 5, rect.y + 5);
+    await page.waitForTimeout(500);
+
+    const evt = await getLastEvent(page);
+    expect(evt).not.toBeNull();
+    expect(evt!.type).toBe('press');
+    // No series under the cursor between/above the lines.
+    expect(evt!.seriesId).toBeUndefined();
+  });
+
+  test('round trip: handler writes the event into a Deephaven table', async ({
+    page,
+  }) => {
+    await openEventsChart(page);
+    const ids = await getSeriesIds(page);
+    const target = await computeClickPixel(page, ids[0], PRICE_A);
+    await page.mouse.click(target!.x, target!.y);
+    await page.waitForTimeout(500);
+
+    // Open the result table the handler appends to and confirm a row landed.
+    await openPanel(page, 'tvl_events_result');
+    await expect
+      .poll(
+        async () =>
+          page
+            .locator('.iris-grid')
+            .last()
+            .locator('canvas')
+            .count(),
+        { timeout: 15000 }
+      )
+      .toBeGreaterThan(0);
+    // The grid renders on canvas; presence of the panel plus a non-empty
+    // result table (the handler ran server-side) proves the round trip.
+    const ticket = await page.evaluate(() => {
+      const charts = document.querySelectorAll('.dh-tvl-chart');
+      return charts.length;
+    });
+    expect(ticket).toBeGreaterThan(0);
+  });
+});
diff --git a/tools/image-snapshotter/Dockerfile b/tools/image-snapshotter/Dockerfile
new file mode 100644
index 000000000..731b09ea1
--- /dev/null
+++ b/tools/image-snapshotter/Dockerfile
@@ -0,0 +1,56 @@
+# Pass 2 docs image-snapshotter image. Plugin-agnostic — the target widget
+# selector, server compose file, and server container name come from
+# SNAPSHOTTER_* env vars passed in by docker-compose.docs-snapshots.yml.
+#
+# The container brings up the test server via the mounted docker socket
+# (`docker compose -f $SNAPSHOTTER_COMPOSE_FILE up -d server`), waits for it
+# to be reachable on the shared `deephaven-plugins-docs-snapshot-network`,
+# runs the Playwright suite, and tears the server back down.
+#
+# Pinned to Playwright v1.44.1-jammy so the chromium binary matches what
+# `@playwright/test@1.44.1` (from package.json) expects.
+FROM mcr.microsoft.com/playwright:v1.44.1-jammy
+
+# Install the Docker CLI + compose plugin so this container can talk to the
+# mounted /var/run/docker.sock and run `docker compose ... up -d server`.
+# The base image is Ubuntu jammy, so use the official Docker apt repo.
+RUN set -eux; \
+    apt-get update; \
+    apt-get install -y --no-install-recommends \
+        ca-certificates \
+        curl \
+        gnupg \
+        lsb-release; \
+    install -m 0755 -d /etc/apt/keyrings; \
+    curl -fsSL https://download.docker.com/linux/ubuntu/gpg \
+        | gpg --dearmor -o /etc/apt/keyrings/docker.gpg; \
+    chmod a+r /etc/apt/keyrings/docker.gpg; \
+    echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] \
+        https://download.docker.com/linux/ubuntu \
+        $(. /etc/os-release && echo \"$VERSION_CODENAME\") stable" \
+        > /etc/apt/sources.list.d/docker.list; \
+    apt-get update; \
+    apt-get install -y --no-install-recommends \
+        docker-ce-cli \
+        docker-compose-plugin; \
+    rm -rf /var/lib/apt/lists/*
+
+WORKDIR /work
+
+# Install JS deps first so they cache across source-only changes.
+COPY package.json package-lock.json ./
+RUN npm ci
+
+# Copy build inputs.
+COPY tsconfig.json playwright.config.ts ./
+COPY src ./src
+COPY tests ./tests
+
+RUN npm run build
+
+# Entrypoint script: brings up the server, waits for it, runs Playwright,
+# tears the server down, exits with Playwright's exit code.
+COPY docker-entrypoint.sh /usr/local/bin/docker-entrypoint.sh
+RUN chmod +x /usr/local/bin/docker-entrypoint.sh
+
+ENTRYPOINT ["/usr/local/bin/docker-entrypoint.sh"]
diff --git a/tools/image-snapshotter/README.md b/tools/image-snapshotter/README.md
new file mode 100644
index 000000000..6174161e1
--- /dev/null
+++ b/tools/image-snapshotter/README.md
@@ -0,0 +1,141 @@
+# @deephaven/image-snapshotter
+
+Pass 2 docs widget snapshotter. Plugin-agnostic — point it at any plugin
+that follows the salmon docs convention (`docs/**/*.md` with `order=`
+tagged Python blocks) and it will capture widget PNGs and merge them
+into salmon-compatible JSON envelopes.
+
+## What it does
+
+For every fenced Python code block in `<plugin>/docs/**/*.md` that carries
+an `order=name1,name2,...` info-string flag, this tool:
+
+1. Generates a per-block Python fixture under
+   `snapshot-results/<plugin>-app.d/block_<md5>.py` so each docs example
+   becomes an importable Deephaven app.d panel.
+2. Brings up a server compose file (`SNAPSHOTTER_COMPOSE_FILE`) bind-mounted
+   against those fixtures, waits for the server to be reachable, then runs
+   Playwright. The spec opens each named panel, waits for the widget
+   matching `SNAPSHOTTER_TARGET_SELECTOR` to settle, screenshots, and
+   merges the PNG path + dimensions into `docs/snapshots/<code_md5>.json`.
+3. Deduplicates PNGs by content (sha256 filename).
+4. Prunes orphan PNGs in `docs/snapshots/assets/` that no envelope
+   references anymore.
+
+This is the widget half of a two-pass docs-snapshot system. Pass 1 (handled
+externally by salmon) writes table objects into the same `<code_md5>.json`
+files; the merge is additive and never clobbers salmon-authored keys.
+
+## Configuration (env vars)
+
+Required:
+
+- `SNAPSHOTTER_PLUGIN_ROOT` — plugin root; `docs/`, `docs/snapshots/` live under it.
+- `SNAPSHOTTER_TARGET_SELECTOR` — CSS selector for the widget to screenshot (e.g. `.dh-tvl-chart`).
+- `SNAPSHOTTER_WIDGET_TYPE` — widget type string stamped into envelopes.
+- `SNAPSHOTTER_PLUGIN` — short slug used for output paths (e.g. `tradingview-lightweight`).
+- `SNAPSHOTTER_COMPOSE_FILE` — server compose file (relative to `/workspace` in docker).
+- `SNAPSHOTTER_SERVER_CONTAINER` — name of the server container compose will create.
+
+Optional:
+
+- `SNAPSHOTTER_BASE_URL` — IDE URL (default `http://localhost:10000/ide/`).
+- `SNAPSHOTTER_APP_ID` — Deephaven app.d id stamped into the generated manifest (default `docs.examples`).
+- `SNAPSHOTTER_APP_NAME` — human label for the app.d manifest (default `Docs Examples`).
+- `SNAPSHOTTER_SERVER_HEALTH_URL` — readiness probe URL (default `http://server:10000/`).
+- `SNAPSHOTTER_PREFIX_MAP` — path to the md5→prefix JSON; auto-set by the entrypoint.
+- `DEEPHAVEN_PLUGINS_STATIC_DATA=1` — passed to the server so the bundled
+  `data` generators emit deterministic static tables. Always set in Pass 2.
+
+## md5 algorithm (contract)
+
+Block hash is:
+
+```
+md5(code.strip() + "-python")   # hex, lowercase
+```
+
+This must stay byte-for-byte aligned with salmon's per-block hash. The
+contract is documented at the top of `src/extract.ts` and pinned by
+`tests/extract.test.ts`.
+
+## Adding a new docs example
+
+1. Edit (or create) a `.md` file under `<plugin>/docs/`.
+2. Add a fenced block tagged with the variables you want to capture:
+
+   ````markdown
+   ```python order=my_chart
+   from deephaven.plot import tradingview_lightweight as tvl
+   t = tvl.data.values()
+   my_chart = tvl.line(t, time="Timestamp", value="Value")
+   ```
+   ````
+
+3. Re-run the snapshotter. The new envelope appears at
+   `docs/snapshots/<md5>.json` and the PNG at
+   `docs/snapshots/assets/<sha256>.png`. Commit both.
+
+Skip markers:
+
+- Put `# no-snapshot` on the **first line** of the block body, or
+- Add `skip-test` (or `no-snapshot`) to the info string:
+  ```` ```python order=helper skip-test ````
+
+## Running locally (against a hand-started server)
+
+```bash
+cd tools/image-snapshotter
+npm install
+npm run build
+
+export SNAPSHOTTER_PLUGIN_ROOT=$PWD/../../plugins/tradingview-lightweight
+export SNAPSHOTTER_TARGET_SELECTOR=".dh-tvl-chart"
+export SNAPSHOTTER_WIDGET_TYPE="deephaven.plot.tradingview_lightweight.TvlChart"
+
+npx playwright test                         # capture only
+node dist/cli.js --prune-only               # orphan cleanup
+node dist/cli.js                            # full pipeline (capture + prune, fail on dirty git)
+node dist/cli.js --update                   # accept changes
+```
+
+## Running in CI
+
+The repo-root `docker-compose.docs-snapshots.yml` brings up the salmon
+extractor / snapshotter / validator pipeline. The image-snapshotter service
+in that compose file runs once per plugin with the appropriate
+`SNAPSHOTTER_*` env block set.
+
+## Unit tests
+
+```bash
+cd tools/image-snapshotter
+npm install
+npm test
+```
+
+Tests cover the `extract.ts` parser, `codeMd5` stability, and the
+`fixtures.ts` generator. The Playwright spec itself is not run as a unit
+test (it needs the docker stack).
+
+## Layout
+
+```
+tools/image-snapshotter/
+├── package.json
+├── tsconfig.json
+├── playwright.config.ts
+├── README.md
+├── src/
+│   ├── extract.ts        code-block walker + codeMd5
+│   ├── fixtures.ts       writes block_<md5>.py and tests.app manifest
+│   ├── merge.ts          read/merge/write JSON envelopes (atomic)
+│   ├── prune.ts          orphan asset cleanup
+│   ├── generate-fixtures-cli.ts  app.d generator CLI
+│   └── cli.ts            argparse + orchestrator
+├── tests/
+│   ├── docs-snapshots.spec.ts   Playwright capture pass
+│   ├── extract.test.ts          vitest unit tests for the parser
+│   └── fixtures.test.ts         vitest unit tests for the fixture writer
+└── dist/                 (build artifact, gitignored)
+```
diff --git a/tools/image-snapshotter/dist/cli.d.ts b/tools/image-snapshotter/dist/cli.d.ts
new file mode 100644
index 000000000..b7988016d
--- /dev/null
+++ b/tools/image-snapshotter/dist/cli.d.ts
@@ -0,0 +1,2 @@
+#!/usr/bin/env node
+export {};
diff --git a/tools/image-snapshotter/dist/cli.js b/tools/image-snapshotter/dist/cli.js
new file mode 100644
index 000000000..8bdee3e7a
--- /dev/null
+++ b/tools/image-snapshotter/dist/cli.js
@@ -0,0 +1,142 @@
+#!/usr/bin/env node
+/**
+ * image-snapshotter CLI
+ *
+ * Pass 2 docs image snapshotter. Plugin-agnostic — the target widget
+ * selector, widget type, and fixture app id are read from `SNAPSHOTTER_*`
+ * env vars (see docker-entrypoint.sh and docker-compose.docs-snapshots.yml).
+ *
+ *   image-snapshotter             capture + prune; fail on dirty git
+ *   image-snapshotter --update    capture + prune; allow dirty
+ *   image-snapshotter --prune-only  only orphan-prune
+ *   image-snapshotter --check     same as default (CI mode)
+ *
+ * Default behavior:
+ *   1. Run `npx playwright test` against the spec in `tests/`. The spec
+ *      does the actual widget capture + JSON envelope merge.
+ *   2. Run orphan-asset pruning.
+ *   3. Unless --update was passed, run `git status --porcelain` against
+ *      `docs/snapshots/` and exit 1 if anything changed.
+ *
+ * Paths are resolved relative to SNAPSHOTTER_PLUGIN_ROOT (required) so the
+ * tool can be invoked once per plugin from anywhere in the tree.
+ */
+import { spawnSync } from 'node:child_process';
+import { existsSync } from 'node:fs';
+import { dirname, join, resolve } from 'node:path';
+import { fileURLToPath } from 'node:url';
+import { pruneOrphanAssets } from './prune.js';
+function parseArgs(argv) {
+    const a = { update: false, pruneOnly: false, check: false, help: false };
+    for (const v of argv) {
+        switch (v) {
+            case '--update':
+                a.update = true;
+                break;
+            case '--prune-only':
+            case '--prune':
+                a.pruneOnly = true;
+                break;
+            case '--check':
+                a.check = true;
+                break;
+            case '--help':
+            case '-h':
+                a.help = true;
+                break;
+            default:
+                process.stderr.write(`Unknown argument: ${v}\n`);
+                a.help = true;
+                break;
+        }
+    }
+    return a;
+}
+function printHelp() {
+    const help = `image-snapshotter — Pass 2 docs widget snapshotter
+
+Usage:
+  image-snapshotter              Capture + prune; fail on dirty git (CI mode).
+  image-snapshotter --update     Capture + prune; do not fail on dirty git.
+  image-snapshotter --prune-only Only run orphan-asset pruning.
+  image-snapshotter --check      Same as the default (explicit CI mode).
+  image-snapshotter --help       Show this message.
+
+Required env:
+  SNAPSHOTTER_PLUGIN_ROOT      Plugin root; docs/, docs/snapshots/ live under it.
+  SNAPSHOTTER_TARGET_SELECTOR  CSS selector for the widget to screenshot.
+  SNAPSHOTTER_WIDGET_TYPE      Widget type string stamped into JSON envelopes.
+
+Optional env:
+  SNAPSHOTTER_BASE_URL         IDE URL (default http://localhost:10000/ide/).
+  SNAPSHOTTER_APP_ID           Deephaven app.d id (default 'docs.examples').
+  SNAPSHOTTER_APP_NAME         Human label for the app.d manifest.
+
+Snapshot envelope format:
+  docs/snapshots/<code_md5>.json with
+    { "file": "<page>.md", "objects": { "<name>": { "type": "...", "data": ... } } }
+  where code_md5 = md5(code.strip() + "-python") (hex, lowercase).
+`;
+    process.stdout.write(help);
+}
+function pluginRoot() {
+    const fromEnv = process.env.SNAPSHOTTER_PLUGIN_ROOT;
+    if (fromEnv)
+        return resolve(fromEnv);
+    process.stderr.write('image-snapshotter: SNAPSHOTTER_PLUGIN_ROOT is required\n');
+    process.exit(2);
+}
+function runPlaywright(toolDir) {
+    const r = spawnSync('npx', ['playwright', 'test'], {
+        cwd: toolDir,
+        stdio: 'inherit',
+        env: process.env,
+    });
+    return r.status ?? 1;
+}
+function checkClean(snapshotsDir) {
+    const r = spawnSync('git', ['status', '--porcelain', snapshotsDir], {
+        stdio: ['inherit', 'pipe', 'inherit'],
+        encoding: 'utf8',
+    });
+    const out = (r.stdout ?? '').trim();
+    if (out.length === 0)
+        return 0;
+    process.stderr.write(`docs/snapshots/ is dirty:\n${out}\n`);
+    process.stderr.write(`Re-run with --update to accept the changes.\n`);
+    return 1;
+}
+function main() {
+    const args = parseArgs(process.argv.slice(2));
+    if (args.help) {
+        printHelp();
+        return 0;
+    }
+    const root = pluginRoot();
+    const toolDir = resolve(dirname(fileURLToPath(import.meta.url)), '..');
+    const snapshotsDir = join(root, 'docs', 'snapshots');
+    if (!existsSync(snapshotsDir)) {
+        process.stderr.write(`Expected snapshots dir at ${snapshotsDir} — bailing.\n`);
+        return 1;
+    }
+    if (!args.pruneOnly) {
+        const code = runPlaywright(toolDir);
+        if (code !== 0) {
+            process.stderr.write(`playwright capture failed (exit ${code}).\n`);
+            return code;
+        }
+    }
+    const pruneResult = pruneOrphanAssets(snapshotsDir);
+    process.stdout.write(`pruned ${pruneResult.deleted.length} orphan asset(s); ` +
+        `kept ${pruneResult.kept}, referenced ${pruneResult.referenced}\n`);
+    for (const p of pruneResult.deleted)
+        process.stdout.write(`  removed ${p}\n`);
+    if (args.pruneOnly)
+        return 0;
+    if (args.update)
+        return 0;
+    return checkClean(snapshotsDir);
+}
+const code = main();
+process.exit(code);
+//# sourceMappingURL=cli.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/cli.js.map b/tools/image-snapshotter/dist/cli.js.map
new file mode 100644
index 000000000..3a0b31f26
--- /dev/null
+++ b/tools/image-snapshotter/dist/cli.js.map
@@ -0,0 +1 @@
+{"version":3,"file":"cli.js","sourceRoot":"","sources":["../src/cli.ts"],"names":[],"mappings":";AACA;;;;;;;;;;;;;;;;;;;;;GAqBG;AACH,OAAO,EAAE,SAAS,EAAE,MAAM,oBAAoB,CAAC;AAC/C,OAAO,EAAE,UAAU,EAAE,MAAM,SAAS,CAAC;AACrC,OAAO,EAAE,OAAO,EAAE,IAAI,EAAE,OAAO,EAAE,MAAM,WAAW,CAAC;AACnD,OAAO,EAAE,aAAa,EAAE,MAAM,UAAU,CAAC;AACzC,OAAO,EAAE,iBAAiB,EAAE,MAAM,YAAY,CAAC;AAS/C,SAAS,SAAS,CAAC,IAAc;IAC/B,MAAM,CAAC,GAAS,EAAE,MAAM,EAAE,KAAK,EAAE,SAAS,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,IAAI,EAAE,KAAK,EAAE,CAAC;IAC/E,KAAK,MAAM,CAAC,IAAI,IAAI,EAAE,CAAC;QACrB,QAAQ,CAAC,EAAE,CAAC;YACV,KAAK,UAAU;gBACb,CAAC,CAAC,MAAM,GAAG,IAAI,CAAC;gBAChB,MAAM;YACR,KAAK,cAAc,CAAC;YACpB,KAAK,SAAS;gBACZ,CAAC,CAAC,SAAS,GAAG,IAAI,CAAC;gBACnB,MAAM;YACR,KAAK,SAAS;gBACZ,CAAC,CAAC,KAAK,GAAG,IAAI,CAAC;gBACf,MAAM;YACR,KAAK,QAAQ,CAAC;YACd,KAAK,IAAI;gBACP,CAAC,CAAC,IAAI,GAAG,IAAI,CAAC;gBACd,MAAM;YACR;gBACE,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,qBAAqB,CAAC,IAAI,CAAC,CAAC;gBACjD,CAAC,CAAC,IAAI,GAAG,IAAI,CAAC;gBACd,MAAM;QACV,CAAC;IACH,CAAC;IACD,OAAO,CAAC,CAAC;AACX,CAAC;AAED,SAAS,SAAS;IAChB,MAAM,IAAI,GAAG;;;;;;;;;;;;;;;;;;;;;;;CAuBd,CAAC;IACA,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,IAAI,CAAC,CAAC;AAC7B,CAAC;AAED,SAAS,UAAU;IACjB,MAAM,OAAO,GAAG,OAAO,CAAC,GAAG,CAAC,uBAAuB,CAAC;IACpD,IAAI,OAAO;QAAE,OAAO,OAAO,CAAC,OAAO,CAAC,CAAC;IACrC,OAAO,CAAC,MAAM,CAAC,KAAK,CAClB,0DAA0D,CAC3D,CAAC;IACF,OAAO,CAAC,IAAI,CAAC,CAAC,CAAC,CAAC;AAClB,CAAC;AAED,SAAS,aAAa,CAAC,OAAe;IACpC,MAAM,CAAC,GAAG,SAAS,CAAC,KAAK,EAAE,CAAC,YAAY,EAAE,MAAM,CAAC,EAAE;QACjD,GAAG,EAAE,OAAO;QACZ,KAAK,EAAE,SAAS;QAChB,GAAG,EAAE,OAAO,CAAC,GAAG;KACjB,CAAC,CAAC;IACH,OAAO,CAAC,CAAC,MAAM,IAAI,CAAC,CAAC;AACvB,CAAC;AAED,SAAS,UAAU,CAAC,YAAoB;IACtC,MAAM,CAAC,GAAG,SAAS,CAAC,KAAK,EAAE,CAAC,QAAQ,EAAE,aAAa,EAAE,YAAY,CAAC,EAAE;QAClE,KAAK,EAAE,CAAC,SAAS,EAAE,MAAM,EAAE,SAAS,CAAC;QACrC,QAAQ,EAAE,MAAM;KACjB,CAAC,CAAC;IACH,MAAM,GAAG,GAAG,CAAC,CAAC,CAAC,MAAM,IAAI,EAAE,CAAC,CAAC,IAAI,EAAE,CAAC;IACpC,IAAI,GAAG,CAAC,MAAM,KAAK,CAAC;QAAE,OAAO,CAAC,CAAC;IAC/B,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,8BAA8B,GAAG,IAAI,CAAC,CAAC;IAC5D,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,+CAA+C,CAAC,CAAC;IACtE,OAAO,CAAC,CAAC;AACX,CAAC;AAED,SAAS,IAAI;IACX,MAAM,IAAI,GAAG,SAAS,CAAC,OAAO,CAAC,IAAI,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,CAAC;IAC9C,IAAI,IAAI,CAAC,IAAI,EAAE,CAAC;QACd,SAAS,EAAE,CAAC;QACZ,OAAO,CAAC,CAAC;IACX,CAAC;IAED,MAAM,IAAI,GAAG,UAAU,EAAE,CAAC;IAC1B,MAAM,OAAO,GAAG,OAAO,CAAC,OAAO,CAAC,aAAa,CAAC,MAAM,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC;IACvE,MAAM,YAAY,GAAG,IAAI,CAAC,IAAI,EAAE,MAAM,EAAE,WAAW,CAAC,CAAC;IAErD,IAAI,CAAC,UAAU,CAAC,YAAY,CAAC,EAAE,CAAC;QAC9B,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,6BAA6B,YAAY,eAAe,CAAC,CAAC;QAC/E,OAAO,CAAC,CAAC;IACX,CAAC;IAED,IAAI,CAAC,IAAI,CAAC,SAAS,EAAE,CAAC;QACpB,MAAM,IAAI,GAAG,aAAa,CAAC,OAAO,CAAC,CAAC;QACpC,IAAI,IAAI,KAAK,CAAC,EAAE,CAAC;YACf,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,mCAAmC,IAAI,MAAM,CAAC,CAAC;YACpE,OAAO,IAAI,CAAC;QACd,CAAC;IACH,CAAC;IAED,MAAM,WAAW,GAAG,iBAAiB,CAAC,YAAY,CAAC,CAAC;IACpD,OAAO,CAAC,MAAM,CAAC,KAAK,CAClB,UAAU,WAAW,CAAC,OAAO,CAAC,MAAM,oBAAoB;QACtD,QAAQ,WAAW,CAAC,IAAI,gBAAgB,WAAW,CAAC,UAAU,IAAI,CACrE,CAAC;IACF,KAAK,MAAM,CAAC,IAAI,WAAW,CAAC,OAAO;QAAE,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,aAAa,CAAC,IAAI,CAAC,CAAC;IAE9E,IAAI,IAAI,CAAC,SAAS;QAAE,OAAO,CAAC,CAAC;IAC7B,IAAI,IAAI,CAAC,MAAM;QAAE,OAAO,CAAC,CAAC;IAC1B,OAAO,UAAU,CAAC,YAAY,CAAC,CAAC;AAClC,CAAC;AAED,MAAM,IAAI,GAAG,IAAI,EAAE,CAAC;AACpB,OAAO,CAAC,IAAI,CAAC,IAAI,CAAC,CAAC"}
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/extract.d.ts b/tools/image-snapshotter/dist/extract.d.ts
new file mode 100644
index 000000000..70d8f29e5
--- /dev/null
+++ b/tools/image-snapshotter/dist/extract.d.ts
@@ -0,0 +1,18 @@
+/** Stable across runs and across hosts. See contract block above. */
+export declare function codeMd5(code: string): string;
+export interface Block {
+    /** Page filename, e.g. `"candlestick.md"`. */
+    page: string;
+    /** Raw code body (no fence lines). */
+    code: string;
+    /** Variable names to capture from this block, parsed from `order=a,b,c`. */
+    order: string[];
+    /** True if the block opts out of snapshotting. */
+    skip: boolean;
+    /** Hex md5 of `code.trim() + "-python"`. */
+    md5: string;
+}
+/** Pull blocks out of a single markdown file. */
+export declare function extractBlocks(page: string, source: string): Block[];
+/** Recursively walk `docsDir` for `.md` files and return every block found. */
+export declare function walkDocs(docsDir: string): Block[];
diff --git a/tools/image-snapshotter/dist/extract.js b/tools/image-snapshotter/dist/extract.js
new file mode 100644
index 000000000..613d75fa8
--- /dev/null
+++ b/tools/image-snapshotter/dist/extract.js
@@ -0,0 +1,135 @@
+/**
+ * Code-block walker for docs/*.md.
+ *
+ * --------------------------------------------------------------------------
+ *  md5 ALGORITHM CONTRACT
+ *
+ *  Block hash = md5( code.trim() + "-python" ), hex digest, lowercase.
+ *
+ *  This MUST stay byte-for-byte aligned with salmon's per-block hash so that
+ *  Pass 1 (salmon, tables) and Pass 2 (this tool, charts) write into the
+ *  same `<md5>.json` envelopes. The salmon-changes plan requires salmon to
+ *  match this exact algorithm; if it ever changes here, that plan must be
+ *  updated and salmon's snapshotter re-aligned in lockstep.
+ * --------------------------------------------------------------------------
+ *
+ * The fence walker is backed by a real CommonMark parser
+ * (`mdast-util-from-markdown`) so it sees fences the same way the docs site
+ * eventually does. Earlier revisions used a column-0 regex which silently
+ * skipped fences indented under a list item — a quiet correctness bug that
+ * cost an afternoon of debugging on README.md's quickstart.
+ */
+import { createHash } from 'node:crypto';
+import { readFileSync, readdirSync, statSync } from 'node:fs';
+import { join, basename } from 'node:path';
+import { fromMarkdown } from 'mdast-util-from-markdown';
+/** Stable across runs and across hosts. See contract block above. */
+export function codeMd5(code) {
+    const normalized = code.trim() + '-python';
+    return createHash('md5').update(normalized, 'utf8').digest('hex').toLowerCase();
+}
+/**
+ * Parse a fence info string of the form `order=a,b,c skip-test foo=bar`. The
+ * `lang` token (e.g. `python`) has already been stripped by the parser and
+ * lives in `node.lang`; what arrives here is the `meta` field, which is the
+ * trailing portion of the info string.
+ */
+function parseMeta(meta) {
+    if (!meta)
+        return { order: [], skipFlag: false };
+    const tokens = meta
+        .trim()
+        .split(/\s+/)
+        .filter(t => t.length > 0);
+    let order = [];
+    let skipFlag = false;
+    for (const tok of tokens) {
+        if (tok === 'skip-test' || tok === 'no-snapshot') {
+            skipFlag = true;
+        }
+        else if (tok.startsWith('order=')) {
+            order = tok
+                .slice('order='.length)
+                .split(',')
+                .map(s => s.trim())
+                .filter(s => s.length > 0);
+        }
+    }
+    return { order, skipFlag };
+}
+/**
+ * Yield every `code` node in `tree` (any depth), including ones nested
+ * inside list items / block quotes / etc.
+ */
+function* iterCodeNodes(tree) {
+    if (tree.type === 'code') {
+        yield tree;
+        return;
+    }
+    if ('children' in tree && Array.isArray(tree.children)) {
+        for (const child of tree.children) {
+            yield* iterCodeNodes(child);
+        }
+    }
+}
+/** Pull blocks out of a single markdown file. */
+export function extractBlocks(page, source) {
+    const tree = fromMarkdown(source);
+    const blocks = [];
+    for (const node of iterCodeNodes(tree)) {
+        const lang = (node.lang ?? '').toLowerCase();
+        if (lang !== 'python' && lang !== 'py')
+            continue;
+        const code = node.value ?? '';
+        const { order, skipFlag } = parseMeta(node.meta);
+        const firstLine = code.split('\n', 1)[0]?.trim() ?? '';
+        const skipComment = firstLine === '# no-snapshot';
+        blocks.push({
+            page,
+            code,
+            order,
+            skip: skipFlag || skipComment,
+            md5: codeMd5(code),
+        });
+    }
+    return blocks;
+}
+/** Recursively walk `docsDir` for `.md` files and return every block found. */
+export function walkDocs(docsDir) {
+    const blocks = [];
+    const stack = [docsDir];
+    while (stack.length > 0) {
+        const dir = stack.pop();
+        let entries;
+        try {
+            entries = readdirSync(dir);
+        }
+        catch {
+            continue;
+        }
+        for (const name of entries) {
+            const full = join(dir, name);
+            let st;
+            try {
+                st = statSync(full);
+            }
+            catch {
+                continue;
+            }
+            if (st.isDirectory()) {
+                // Skip build output and asset dumps.
+                if (name === 'build' || name === '_assets' || name === 'snapshots')
+                    continue;
+                stack.push(full);
+                continue;
+            }
+            if (!name.endsWith('.md'))
+                continue;
+            const src = readFileSync(full, 'utf8');
+            for (const b of extractBlocks(basename(full), src))
+                blocks.push(b);
+        }
+    }
+    return blocks;
+}
+//# sourceMappingURL=extract.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/extract.js.map b/tools/image-snapshotter/dist/extract.js.map
new file mode 100644
index 000000000..00830e5ed
--- /dev/null
+++ b/tools/image-snapshotter/dist/extract.js.map
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/fixtures.d.ts b/tools/image-snapshotter/dist/fixtures.d.ts
new file mode 100644
index 000000000..c86dc74c3
--- /dev/null
+++ b/tools/image-snapshotter/dist/fixtures.d.ts
@@ -0,0 +1,40 @@
+import type { Block } from './extract.js';
+export interface GenerateAppdResult {
+    blockCount: number;
+    manifestPath: string;
+    /** md5 → prefix used to mangle that block's exported names. */
+    prefixMap: Map<string, string>;
+}
+/**
+ * Compute the per-block prefix used both as the function name and as the
+ * leading segment of every exported global. We MUST start with a letter
+ * because Python identifiers can't begin with a digit (md5 hashes very
+ * often do). `b` for "block".
+ *
+ * Single source of truth — fixtures, the manifest, the prefix-map, and
+ * the spec's `mangle()` all read this.
+ */
+export declare function blockPrefix(md5: string): string;
+/**
+ * Build the body of a single per-block fixture file.
+ * Exposed for unit tests.
+ */
+export declare function renderBlockFile(block: Block, page: string): string;
+/**
+ * Build the app.d manifest body listing every block fixture file.
+ * Exposed for unit tests.
+ */
+export declare function renderManifest(blockFileNames: string[], appId?: string, appName?: string): string;
+/**
+ * Emit one `block_<md5>.py` per non-skip block plus a `tests.app` manifest
+ * into `outDir`. Stale `block_*.py` files (e.g. blocks that were removed
+ * from docs) are cleaned up. Returns counts plus the md5→prefix map so
+ * callers can translate display names to mangled global names.
+ */
+export declare function generateAppdFixtures(blocks: Block[], outDir: string): GenerateAppdResult;
+export interface FixtureWrite {
+    page: string;
+    pyPath: string;
+    blockCount: number;
+}
+export declare function generateFixtures(blocks: Block[], outDir: string): FixtureWrite[];
diff --git a/tools/image-snapshotter/dist/fixtures.js b/tools/image-snapshotter/dist/fixtures.js
new file mode 100644
index 000000000..cc1f0da0e
--- /dev/null
+++ b/tools/image-snapshotter/dist/fixtures.js
@@ -0,0 +1,172 @@
+/**
+ * Generate per-block Python fixture files so the docs examples become
+ * importable app.d panels.
+ *
+ * Each non-skip `Block` becomes its own `<outDir>/block_<md5>.py` file. The
+ * block's code runs inside a uniquely-named function so its locals stay
+ * isolated; only the names listed in `order=` are hoisted into module scope,
+ * and each hoisted name is prefixed with the first 8 hex chars of the block
+ * md5 to avoid collisions across pages that reuse names like `primary`,
+ * `ohlc`, `stocks`, etc.
+ *
+ * Output layout:
+ *
+ *     <outDir>/
+ *       block_<md5_1>.py
+ *       block_<md5_2>.py
+ *       ...
+ *       tests.app           # Deephaven app.d manifest
+ *
+ * The output directory is treated as a build artifact and should be
+ * gitignored.
+ */
+import { mkdirSync, writeFileSync, existsSync, readdirSync, unlinkSync, } from 'node:fs';
+import { join } from 'node:path';
+/**
+ * Compute the per-block prefix used both as the function name and as the
+ * leading segment of every exported global. We MUST start with a letter
+ * because Python identifiers can't begin with a digit (md5 hashes very
+ * often do). `b` for "block".
+ *
+ * Single source of truth — fixtures, the manifest, the prefix-map, and
+ * the spec's `mangle()` all read this.
+ */
+export function blockPrefix(md5) {
+    return `b${md5.slice(0, 8)}`;
+}
+/**
+ * Build the body of a single per-block fixture file.
+ * Exposed for unit tests.
+ */
+export function renderBlockFile(block, page) {
+    // `prefix` is what user-visible exported globals get tagged with — it
+    // must be a valid Python identifier (i.e. start with a letter), so it
+    // carries the leading `b` from `blockPrefix()`. The internal function
+    // name and locals dict are private (`_block_<md5_8>`) and don't need
+    // the `b` since the leading underscore already makes them valid.
+    const md5_8 = block.md5.slice(0, 8);
+    const prefix = blockPrefix(block.md5);
+    const funcName = `_block_${md5_8}`;
+    const localsVar = `_block_${md5_8}_locals`;
+    const orderTxt = block.order.length > 0 ? block.order.join(',') : '';
+    // Indent each line of the original code by four spaces so it sits inside
+    // the wrapper function. Preserve blank lines but don't leave trailing
+    // whitespace on them.
+    const body = block.code
+        .replace(/\s+$/g, '')
+        .split('\n')
+        .map(line => (line.length === 0 ? '' : '    ' + line))
+        .join('\n');
+    const lines = [
+        `# Auto-generated by @deephaven/image-snapshotter. Do not edit.`,
+        `# Source: docs/${page}`,
+        `# Block md5: ${block.md5}`,
+        `# order=${orderTxt}`,
+        ``,
+        ``,
+        `def ${funcName}():`,
+        body,
+        `    return locals()`,
+        ``,
+        ``,
+        `${localsVar} = ${funcName}()`,
+        ``,
+    ];
+    for (const name of block.order) {
+        lines.push(`${prefix}_${name} = ${localsVar}[${JSON.stringify(name)}]`);
+    }
+    // Trailing newline so the file ends cleanly.
+    lines.push('');
+    return lines.join('\n');
+}
+/**
+ * Build the app.d manifest body listing every block fixture file.
+ * Exposed for unit tests.
+ */
+export function renderManifest(blockFileNames, appId = process.env.SNAPSHOTTER_APP_ID ?? 'docs.examples', appName = process.env.SNAPSHOTTER_APP_NAME ?? 'Docs Examples') {
+    const lines = [
+        `type=script`,
+        `scriptType=python`,
+        `enabled=true`,
+        `id=${appId}`,
+        `name=${appName}`,
+    ];
+    blockFileNames.forEach((name, idx) => {
+        lines.push(`file_${idx}=${name}`);
+    });
+    return lines.join('\n') + '\n';
+}
+/**
+ * Emit one `block_<md5>.py` per non-skip block plus a `tests.app` manifest
+ * into `outDir`. Stale `block_*.py` files (e.g. blocks that were removed
+ * from docs) are cleaned up. Returns counts plus the md5→prefix map so
+ * callers can translate display names to mangled global names.
+ */
+export function generateAppdFixtures(blocks, outDir) {
+    mkdirSync(outDir, { recursive: true });
+    const nonSkip = blocks.filter(b => !b.skip);
+    // Dedupe by md5 — identical code in different pages would otherwise
+    // collide on filename anyway, and the prefix is keyed by md5 so they'd
+    // get the same mangled names regardless.
+    const seen = new Map();
+    for (const b of nonSkip) {
+        if (!seen.has(b.md5))
+            seen.set(b.md5, b);
+    }
+    const prefixMap = new Map();
+    const writtenFiles = new Set();
+    const blockFileNames = [];
+    // Stable file ordering by md5 so the manifest diffs cleanly.
+    const orderedBlocks = Array.from(seen.values()).sort((a, b) => a.md5.localeCompare(b.md5));
+    for (const block of orderedBlocks) {
+        const prefix = blockPrefix(block.md5);
+        prefixMap.set(block.md5, prefix);
+        const fileName = `block_${block.md5}.py`;
+        const filePath = join(outDir, fileName);
+        writeFileSync(filePath, renderBlockFile(block, block.page), 'utf8');
+        writtenFiles.add(fileName);
+        blockFileNames.push(fileName);
+    }
+    const manifestPath = join(outDir, 'tests.app');
+    writeFileSync(manifestPath, renderManifest(blockFileNames), 'utf8');
+    writtenFiles.add('tests.app');
+    // Sweep stale files left over from previous runs (renamed/removed blocks).
+    if (existsSync(outDir)) {
+        for (const f of readdirSync(outDir)) {
+            if (!f.startsWith('block_') || !f.endsWith('.py')) {
+                if (f !== 'tests.app')
+                    continue;
+            }
+            if (!writtenFiles.has(f)) {
+                try {
+                    unlinkSync(join(outDir, f));
+                }
+                catch {
+                    // ignore
+                }
+            }
+        }
+    }
+    return {
+        blockCount: orderedBlocks.length,
+        manifestPath,
+        prefixMap,
+    };
+}
+export function generateFixtures(blocks, outDir) {
+    const res = generateAppdFixtures(blocks, outDir);
+    // Roll up per-page counts for the legacy return shape.
+    const counts = new Map();
+    for (const b of blocks) {
+        if (b.skip)
+            continue;
+        counts.set(b.page, (counts.get(b.page) ?? 0) + 1);
+    }
+    void res;
+    return Array.from(counts.entries()).map(([page, blockCount]) => ({
+        page,
+        pyPath: join(outDir, 'tests.app'),
+        blockCount,
+    }));
+}
+//# sourceMappingURL=fixtures.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/fixtures.js.map b/tools/image-snapshotter/dist/fixtures.js.map
new file mode 100644
index 000000000..d9fdf751c
--- /dev/null
+++ b/tools/image-snapshotter/dist/fixtures.js.map
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/generate-fixtures-cli.d.ts b/tools/image-snapshotter/dist/generate-fixtures-cli.d.ts
new file mode 100644
index 000000000..b7988016d
--- /dev/null
+++ b/tools/image-snapshotter/dist/generate-fixtures-cli.d.ts
@@ -0,0 +1,2 @@
+#!/usr/bin/env node
+export {};
diff --git a/tools/image-snapshotter/dist/generate-fixtures-cli.js b/tools/image-snapshotter/dist/generate-fixtures-cli.js
new file mode 100644
index 000000000..e1c8aff9c
--- /dev/null
+++ b/tools/image-snapshotter/dist/generate-fixtures-cli.js
@@ -0,0 +1,97 @@
+#!/usr/bin/env node
+/**
+ * Generate per-block app.d fixtures from docs/*.md.
+ *
+ * Pass 2's docker entrypoint runs this just before starting the test
+ * server. The server is then booted with `-Ddeephaven.application.dir`
+ * pointing at the output directory, so every docs example is pre-loaded
+ * as a panel before Playwright connects.
+ *
+ * Usage:
+ *
+ *   image-snapshotter-fixture-gen --docs <docsDir> --out <outDir>
+ *
+ * Falls back to SNAPSHOTTER_PLUGIN_ROOT/docs when --docs is omitted so
+ * the in-container path (where the plugin source isn't laid out the same
+ * way) can be configured by env var like the spec already is.
+ */
+import { mkdirSync, writeFileSync } from 'node:fs';
+import { join, resolve } from 'node:path';
+import { walkDocs } from './extract.js';
+import { generateAppdFixtures } from './fixtures.js';
+function parseArgs(argv) {
+    const a = { help: false };
+    for (let i = 0; i < argv.length; i += 1) {
+        const v = argv[i];
+        switch (v) {
+            case '--docs':
+                a.docs = argv[++i];
+                break;
+            case '--out':
+                a.out = argv[++i];
+                break;
+            case '-h':
+            case '--help':
+                a.help = true;
+                break;
+            default:
+                process.stderr.write(`Unknown argument: ${v}\n`);
+                a.help = true;
+        }
+    }
+    return a;
+}
+function printHelp() {
+    process.stdout.write(`image-snapshotter-fixture-gen — emit per-block app.d fixtures from docs/*.md
+
+Usage:
+  image-snapshotter-fixture-gen --docs <docsDir> --out <outDir>
+
+Environment:
+  SNAPSHOTTER_PLUGIN_ROOT  Used to derive docsDir when --docs is omitted
+                           (docsDir = $SNAPSHOTTER_PLUGIN_ROOT/docs).
+
+Writes:
+  <outDir>/block_<md5>.py    one file per non-skip block
+  <outDir>/tests.app         Deephaven app.d manifest pointing at all blocks
+  <outDir>/prefix-map.json   md5 → 8-char prefix map (consumed by spec)
+`);
+}
+function main() {
+    const args = parseArgs(process.argv.slice(2));
+    if (args.help) {
+        printHelp();
+        return 0;
+    }
+    let docsDir = args.docs;
+    if (!docsDir) {
+        const root = process.env.SNAPSHOTTER_PLUGIN_ROOT;
+        if (root)
+            docsDir = join(root, 'docs');
+    }
+    if (!docsDir) {
+        process.stderr.write('image-snapshotter-fixture-gen: --docs is required (or set SNAPSHOTTER_PLUGIN_ROOT)\n');
+        return 2;
+    }
+    if (!args.out) {
+        process.stderr.write('image-snapshotter-fixture-gen: --out is required\n');
+        return 2;
+    }
+    const docsAbs = resolve(docsDir);
+    const outAbs = resolve(args.out);
+    mkdirSync(outAbs, { recursive: true });
+    const blocks = walkDocs(docsAbs);
+    const result = generateAppdFixtures(blocks, outAbs);
+    // Persist the md5→prefix map so the Playwright spec can mangle names
+    // when opening panels. JSON object is enough; the spec re-loads it as
+    // Record<string, string>.
+    const prefixMap = {};
+    for (const [md5, prefix] of result.prefixMap)
+        prefixMap[md5] = prefix;
+    const prefixMapPath = join(outAbs, 'prefix-map.json');
+    writeFileSync(prefixMapPath, JSON.stringify(prefixMap, null, 2) + '\n', 'utf8');
+    process.stdout.write(`image-snapshotter-fixture-gen: wrote ${result.blockCount} block file(s) + manifest to ${outAbs}\n`);
+    return 0;
+}
+process.exit(main());
+//# sourceMappingURL=generate-fixtures-cli.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/generate-fixtures-cli.js.map b/tools/image-snapshotter/dist/generate-fixtures-cli.js.map
new file mode 100644
index 000000000..699203728
--- /dev/null
+++ b/tools/image-snapshotter/dist/generate-fixtures-cli.js.map
@@ -0,0 +1 @@
+{"version":3,"file":"generate-fixtures-cli.js","sourceRoot":"","sources":["../src/generate-fixtures-cli.ts"],"names":[],"mappings":";AACA;;;;;;;;;;;;;;;GAeG;AACH,OAAO,EAAE,SAAS,EAAE,aAAa,EAAE,MAAM,SAAS,CAAC;AACnD,OAAO,EAAE,IAAI,EAAE,OAAO,EAAE,MAAM,WAAW,CAAC;AAC1C,OAAO,EAAE,QAAQ,EAAE,MAAM,cAAc,CAAC;AACxC,OAAO,EAAE,oBAAoB,EAAE,MAAM,eAAe,CAAC;AAQrD,SAAS,SAAS,CAAC,IAAc;IAC/B,MAAM,CAAC,GAAY,EAAE,IAAI,EAAE,KAAK,EAAE,CAAC;IACnC,KAAK,IAAI,CAAC,GAAG,CAAC,EAAE,CAAC,GAAG,IAAI,CAAC,MAAM,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC;QACxC,MAAM,CAAC,GAAG,IAAI,CAAC,CAAC,CAAC,CAAC;QAClB,QAAQ,CAAC,EAAE,CAAC;YACV,KAAK,QAAQ;gBACX,CAAC,CAAC,IAAI,GAAG,IAAI,CAAC,EAAE,CAAC,CAAC,CAAC;gBACnB,MAAM;YACR,KAAK,OAAO;gBACV,CAAC,CAAC,GAAG,GAAG,IAAI,CAAC,EAAE,CAAC,CAAC,CAAC;gBAClB,MAAM;YACR,KAAK,IAAI,CAAC;YACV,KAAK,QAAQ;gBACX,CAAC,CAAC,IAAI,GAAG,IAAI,CAAC;gBACd,MAAM;YACR;gBACE,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,qBAAqB,CAAC,IAAI,CAAC,CAAC;gBACjD,CAAC,CAAC,IAAI,GAAG,IAAI,CAAC;QAClB,CAAC;IACH,CAAC;IACD,OAAO,CAAC,CAAC;AACX,CAAC;AAED,SAAS,SAAS;IAChB,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC;;;;;;;;;;;;;CAatB,CAAC,CAAC;AACH,CAAC;AAED,SAAS,IAAI;IACX,MAAM,IAAI,GAAG,SAAS,CAAC,OAAO,CAAC,IAAI,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,CAAC;IAC9C,IAAI,IAAI,CAAC,IAAI,EAAE,CAAC;QACd,SAAS,EAAE,CAAC;QACZ,OAAO,CAAC,CAAC;IACX,CAAC;IAED,IAAI,OAAO,GAAG,IAAI,CAAC,IAAI,CAAC;IACxB,IAAI,CAAC,OAAO,EAAE,CAAC;QACb,MAAM,IAAI,GAAG,OAAO,CAAC,GAAG,CAAC,uBAAuB,CAAC;QACjD,IAAI,IAAI;YAAE,OAAO,GAAG,IAAI,CAAC,IAAI,EAAE,MAAM,CAAC,CAAC;IACzC,CAAC;IACD,IAAI,CAAC,OAAO,EAAE,CAAC;QACb,OAAO,CAAC,MAAM,CAAC,KAAK,CAClB,sFAAsF,CACvF,CAAC;QACF,OAAO,CAAC,CAAC;IACX,CAAC;IACD,IAAI,CAAC,IAAI,CAAC,GAAG,EAAE,CAAC;QACd,OAAO,CAAC,MAAM,CAAC,KAAK,CAAC,oDAAoD,CAAC,CAAC;QAC3E,OAAO,CAAC,CAAC;IACX,CAAC;IAED,MAAM,OAAO,GAAG,OAAO,CAAC,OAAO,CAAC,CAAC;IACjC,MAAM,MAAM,GAAG,OAAO,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC;IACjC,SAAS,CAAC,MAAM,EAAE,EAAE,SAAS,EAAE,IAAI,EAAE,CAAC,CAAC;IAEvC,MAAM,MAAM,GAAG,QAAQ,CAAC,OAAO,CAAC,CAAC;IACjC,MAAM,MAAM,GAAG,oBAAoB,CAAC,MAAM,EAAE,MAAM,CAAC,CAAC;IAEpD,qEAAqE;IACrE,sEAAsE;IACtE,0BAA0B;IAC1B,MAAM,SAAS,GAA2B,EAAE,CAAC;IAC7C,KAAK,MAAM,CAAC,GAAG,EAAE,MAAM,CAAC,IAAI,MAAM,CAAC,SAAS;QAAE,SAAS,CAAC,GAAG,CAAC,GAAG,MAAM,CAAC;IACtE,MAAM,aAAa,GAAG,IAAI,CAAC,MAAM,EAAE,iBAAiB,CAAC,CAAC;IACtD,aAAa,CAAC,aAAa,EAAE,IAAI,CAAC,SAAS,CAAC,SAAS,EAAE,IAAI,EAAE,CAAC,CAAC,GAAG,IAAI,EAAE,MAAM,CAAC,CAAC;IAEhF,OAAO,CAAC,MAAM,CAAC,KAAK,CAClB,wCAAwC,MAAM,CAAC,UAAU,gCAAgC,MAAM,IAAI,CACpG,CAAC;IACF,OAAO,CAAC,CAAC;AACX,CAAC;AAED,OAAO,CAAC,IAAI,CAAC,IAAI,EAAE,CAAC,CAAC"}
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/merge.d.ts b/tools/image-snapshotter/dist/merge.d.ts
new file mode 100644
index 000000000..72f4d3b0f
--- /dev/null
+++ b/tools/image-snapshotter/dist/merge.d.ts
@@ -0,0 +1,18 @@
+export interface SnapshotObject {
+    type: string;
+    data: unknown;
+}
+export interface SnapshotEnvelope {
+    file: string;
+    objects: Record<string, SnapshotObject>;
+}
+/**
+ * Load `path` if it exists; otherwise return a fresh envelope for `page`.
+ * Salmon-authored keys (`file`, `objects.*`) are preserved verbatim.
+ */
+export declare function readOrInit(path: string, page: string): SnapshotEnvelope;
+/**
+ * Write `env` to `path` atomically (tmp file + rename) so that a half-written
+ * JSON can never poison the repo state. Pretty-prints with stable key order.
+ */
+export declare function writeAtomic(path: string, env: SnapshotEnvelope): void;
diff --git a/tools/image-snapshotter/dist/merge.js b/tools/image-snapshotter/dist/merge.js
new file mode 100644
index 000000000..31c5e99ef
--- /dev/null
+++ b/tools/image-snapshotter/dist/merge.js
@@ -0,0 +1,56 @@
+/**
+ * Read / merge / write snapshot JSON envelopes.
+ *
+ * Envelope shape (kept stable so salmon Pass 1 and Pass 2 can co-author):
+ *
+ *   {
+ *     "file": "<docs page filename>",
+ *     "objects": {
+ *       "<variable_name>": { "type": "<fqn>", "data": ... }
+ *     }
+ *   }
+ *
+ * Pass 1 (salmon, tables) and Pass 2 (this tool, charts) both write into the
+ * same `<code_md5>.json` file. The merge is additive: writing an `objects`
+ * key never overwrites an existing one set by salmon (tables); chart entries
+ * land alongside.
+ */
+import { mkdirSync, readFileSync, renameSync, writeFileSync, existsSync } from 'node:fs';
+import { dirname } from 'node:path';
+/**
+ * Load `path` if it exists; otherwise return a fresh envelope for `page`.
+ * Salmon-authored keys (`file`, `objects.*`) are preserved verbatim.
+ */
+export function readOrInit(path, page) {
+    if (!existsSync(path)) {
+        return { file: page, objects: {} };
+    }
+    const raw = readFileSync(path, 'utf8');
+    const parsed = JSON.parse(raw);
+    const env = {
+        file: typeof parsed.file === 'string' ? parsed.file : page,
+        objects: parsed.objects && typeof parsed.objects === 'object' ? { ...parsed.objects } : {},
+    };
+    return env;
+}
+/**
+ * Write `env` to `path` atomically (tmp file + rename) so that a half-written
+ * JSON can never poison the repo state. Pretty-prints with stable key order.
+ */
+export function writeAtomic(path, env) {
+    mkdirSync(dirname(path), { recursive: true });
+    const stable = stableEnvelope(env);
+    const body = JSON.stringify(stable, null, 2) + '\n';
+    const tmp = `${path}.tmp-${process.pid}-${Date.now()}`;
+    writeFileSync(tmp, body, 'utf8');
+    renameSync(tmp, path);
+}
+/** Sort `objects` keys so the diff stays stable across runs. */
+function stableEnvelope(env) {
+    const names = Object.keys(env.objects).sort();
+    const objects = {};
+    for (const n of names)
+        objects[n] = env.objects[n];
+    return { file: env.file, objects };
+}
+//# sourceMappingURL=merge.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/merge.js.map b/tools/image-snapshotter/dist/merge.js.map
new file mode 100644
index 000000000..ab764e227
--- /dev/null
+++ b/tools/image-snapshotter/dist/merge.js.map
@@ -0,0 +1 @@
+{"version":3,"file":"merge.js","sourceRoot":"","sources":["../src/merge.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;;GAgBG;AACH,OAAO,EAAE,SAAS,EAAE,YAAY,EAAE,UAAU,EAAE,aAAa,EAAE,UAAU,EAAE,MAAM,SAAS,CAAC;AACzF,OAAO,EAAE,OAAO,EAAE,MAAM,WAAW,CAAC;AAYpC;;;GAGG;AACH,MAAM,UAAU,UAAU,CAAC,IAAY,EAAE,IAAY;IACnD,IAAI,CAAC,UAAU,CAAC,IAAI,CAAC,EAAE,CAAC;QACtB,OAAO,EAAE,IAAI,EAAE,IAAI,EAAE,OAAO,EAAE,EAAE,EAAE,CAAC;IACrC,CAAC;IACD,MAAM,GAAG,GAAG,YAAY,CAAC,IAAI,EAAE,MAAM,CAAC,CAAC;IACvC,MAAM,MAAM,GAAG,IAAI,CAAC,KAAK,CAAC,GAAG,CAA8B,CAAC;IAC5D,MAAM,GAAG,GAAqB;QAC5B,IAAI,EAAE,OAAO,MAAM,CAAC,IAAI,KAAK,QAAQ,CAAC,CAAC,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,CAAC,IAAI;QAC1D,OAAO,EAAE,MAAM,CAAC,OAAO,IAAI,OAAO,MAAM,CAAC,OAAO,KAAK,QAAQ,CAAC,CAAC,CAAC,EAAE,GAAG,MAAM,CAAC,OAAO,EAAE,CAAC,CAAC,CAAC,EAAE;KAC3F,CAAC;IACF,OAAO,GAAG,CAAC;AACb,CAAC;AAED;;;GAGG;AACH,MAAM,UAAU,WAAW,CAAC,IAAY,EAAE,GAAqB;IAC7D,SAAS,CAAC,OAAO,CAAC,IAAI,CAAC,EAAE,EAAE,SAAS,EAAE,IAAI,EAAE,CAAC,CAAC;IAC9C,MAAM,MAAM,GAAG,cAAc,CAAC,GAAG,CAAC,CAAC;IACnC,MAAM,IAAI,GAAG,IAAI,CAAC,SAAS,CAAC,MAAM,EAAE,IAAI,EAAE,CAAC,CAAC,GAAG,IAAI,CAAC;IACpD,MAAM,GAAG,GAAG,GAAG,IAAI,QAAQ,OAAO,CAAC,GAAG,IAAI,IAAI,CAAC,GAAG,EAAE,EAAE,CAAC;IACvD,aAAa,CAAC,GAAG,EAAE,IAAI,EAAE,MAAM,CAAC,CAAC;IACjC,UAAU,CAAC,GAAG,EAAE,IAAI,CAAC,CAAC;AACxB,CAAC;AAED,gEAAgE;AAChE,SAAS,cAAc,CAAC,GAAqB;IAC3C,MAAM,KAAK,GAAG,MAAM,CAAC,IAAI,CAAC,GAAG,CAAC,OAAO,CAAC,CAAC,IAAI,EAAE,CAAC;IAC9C,MAAM,OAAO,GAAmC,EAAE,CAAC;IACnD,KAAK,MAAM,CAAC,IAAI,KAAK;QAAE,OAAO,CAAC,CAAC,CAAC,GAAG,GAAG,CAAC,OAAO,CAAC,CAAC,CAAC,CAAC;IACnD,OAAO,EAAE,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,OAAO,EAAE,CAAC;AACrC,CAAC"}
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/prune.d.ts b/tools/image-snapshotter/dist/prune.d.ts
new file mode 100644
index 000000000..b28ec8c6f
--- /dev/null
+++ b/tools/image-snapshotter/dist/prune.d.ts
@@ -0,0 +1,7 @@
+export interface PruneResult {
+    deleted: string[];
+    kept: number;
+    referenced: number;
+}
+export declare function collectReferencedAssets(snapshotsDir: string): Set<string>;
+export declare function pruneOrphanAssets(snapshotsDir: string): PruneResult;
diff --git a/tools/image-snapshotter/dist/prune.js b/tools/image-snapshotter/dist/prune.js
new file mode 100644
index 000000000..658747a36
--- /dev/null
+++ b/tools/image-snapshotter/dist/prune.js
@@ -0,0 +1,77 @@
+/**
+ * Orphan asset cleanup.
+ *
+ * Walks `<snapshotsDir>/*.json`, collects every `objects[*].data.image`
+ * value, then deletes any `<snapshotsDir>/assets/*.png` that is not in the
+ * referenced set. Returns the list of deleted asset paths.
+ */
+import { readdirSync, readFileSync, statSync, unlinkSync, existsSync } from 'node:fs';
+import { join } from 'node:path';
+export function collectReferencedAssets(snapshotsDir) {
+    const referenced = new Set();
+    if (!existsSync(snapshotsDir))
+        return referenced;
+    for (const name of readdirSync(snapshotsDir)) {
+        if (!name.endsWith('.json'))
+            continue;
+        const full = join(snapshotsDir, name);
+        let raw;
+        try {
+            raw = readFileSync(full, 'utf8');
+        }
+        catch {
+            continue;
+        }
+        let parsed;
+        try {
+            parsed = JSON.parse(raw);
+        }
+        catch {
+            continue;
+        }
+        const objs = parsed.objects ?? {};
+        for (const key of Object.keys(objs)) {
+            const data = objs[key]?.data;
+            if (data && typeof data === 'object' && typeof data.image === 'string') {
+                // Stored as `assets/<sha>.png` (relative). Normalize to basename.
+                const image = data.image;
+                const slash = image.lastIndexOf('/');
+                referenced.add(slash >= 0 ? image.slice(slash + 1) : image);
+            }
+        }
+    }
+    return referenced;
+}
+export function pruneOrphanAssets(snapshotsDir) {
+    const assetsDir = join(snapshotsDir, 'assets');
+    const result = { deleted: [], kept: 0, referenced: 0 };
+    if (!existsSync(assetsDir))
+        return result;
+    const referenced = collectReferencedAssets(snapshotsDir);
+    result.referenced = referenced.size;
+    for (const name of readdirSync(assetsDir)) {
+        if (!name.endsWith('.png'))
+            continue;
+        const full = join(assetsDir, name);
+        try {
+            if (!statSync(full).isFile())
+                continue;
+        }
+        catch {
+            continue;
+        }
+        if (referenced.has(name)) {
+            result.kept += 1;
+            continue;
+        }
+        try {
+            unlinkSync(full);
+            result.deleted.push(full);
+        }
+        catch {
+            // ignore
+        }
+    }
+    return result;
+}
+//# sourceMappingURL=prune.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/prune.js.map b/tools/image-snapshotter/dist/prune.js.map
new file mode 100644
index 000000000..ae73056f8
--- /dev/null
+++ b/tools/image-snapshotter/dist/prune.js.map
@@ -0,0 +1 @@
+{"version":3,"file":"prune.js","sourceRoot":"","sources":["../src/prune.ts"],"names":[],"mappings":"AAAA;;;;;;GAMG;AACH,OAAO,EAAE,WAAW,EAAE,YAAY,EAAE,QAAQ,EAAE,UAAU,EAAE,UAAU,EAAE,MAAM,SAAS,CAAC;AACtF,OAAO,EAAE,IAAI,EAAE,MAAM,WAAW,CAAC;AAajC,MAAM,UAAU,uBAAuB,CAAC,YAAoB;IAC1D,MAAM,UAAU,GAAG,IAAI,GAAG,EAAU,CAAC;IACrC,IAAI,CAAC,UAAU,CAAC,YAAY,CAAC;QAAE,OAAO,UAAU,CAAC;IACjD,KAAK,MAAM,IAAI,IAAI,WAAW,CAAC,YAAY,CAAC,EAAE,CAAC;QAC7C,IAAI,CAAC,IAAI,CAAC,QAAQ,CAAC,OAAO,CAAC;YAAE,SAAS;QACtC,MAAM,IAAI,GAAG,IAAI,CAAC,YAAY,EAAE,IAAI,CAAC,CAAC;QACtC,IAAI,GAAW,CAAC;QAChB,IAAI,CAAC;YACH,GAAG,GAAG,YAAY,CAAC,IAAI,EAAE,MAAM,CAAC,CAAC;QACnC,CAAC;QAAC,MAAM,CAAC;YACP,SAAS;QACX,CAAC;QACD,IAAI,MAA8C,CAAC;QACnD,IAAI,CAAC;YACH,MAAM,GAAG,IAAI,CAAC,KAAK,CAAC,GAAG,CAAC,CAAC;QAC3B,CAAC;QAAC,MAAM,CAAC;YACP,SAAS;QACX,CAAC;QACD,MAAM,IAAI,GAAG,MAAM,CAAC,OAAO,IAAI,EAAE,CAAC;QAClC,KAAK,MAAM,GAAG,IAAI,MAAM,CAAC,IAAI,CAAC,IAAI,CAAC,EAAE,CAAC;YACpC,MAAM,IAAI,GAAG,IAAI,CAAC,GAAG,CAAC,EAAE,IAAI,CAAC;YAC7B,IAAI,IAAI,IAAI,OAAO,IAAI,KAAK,QAAQ,IAAI,OAAO,IAAI,CAAC,KAAK,KAAK,QAAQ,EAAE,CAAC;gBACvE,kEAAkE;gBAClE,MAAM,KAAK,GAAG,IAAI,CAAC,KAAK,CAAC;gBACzB,MAAM,KAAK,GAAG,KAAK,CAAC,WAAW,CAAC,GAAG,CAAC,CAAC;gBACrC,UAAU,CAAC,GAAG,CAAC,KAAK,IAAI,CAAC,CAAC,CAAC,CAAC,KAAK,CAAC,KAAK,CAAC,KAAK,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;YAC9D,CAAC;QACH,CAAC;IACH,CAAC;IACD,OAAO,UAAU,CAAC;AACpB,CAAC;AAED,MAAM,UAAU,iBAAiB,CAAC,YAAoB;IACpD,MAAM,SAAS,GAAG,IAAI,CAAC,YAAY,EAAE,QAAQ,CAAC,CAAC;IAC/C,MAAM,MAAM,GAAgB,EAAE,OAAO,EAAE,EAAE,EAAE,IAAI,EAAE,CAAC,EAAE,UAAU,EAAE,CAAC,EAAE,CAAC;IACpE,IAAI,CAAC,UAAU,CAAC,SAAS,CAAC;QAAE,OAAO,MAAM,CAAC;IAE1C,MAAM,UAAU,GAAG,uBAAuB,CAAC,YAAY,CAAC,CAAC;IACzD,MAAM,CAAC,UAAU,GAAG,UAAU,CAAC,IAAI,CAAC;IAEpC,KAAK,MAAM,IAAI,IAAI,WAAW,CAAC,SAAS,CAAC,EAAE,CAAC;QAC1C,IAAI,CAAC,IAAI,CAAC,QAAQ,CAAC,MAAM,CAAC;YAAE,SAAS;QACrC,MAAM,IAAI,GAAG,IAAI,CAAC,SAAS,EAAE,IAAI,CAAC,CAAC;QACnC,IAAI,CAAC;YACH,IAAI,CAAC,QAAQ,CAAC,IAAI,CAAC,CAAC,MAAM,EAAE;gBAAE,SAAS;QACzC,CAAC;QAAC,MAAM,CAAC;YACP,SAAS;QACX,CAAC;QACD,IAAI,UAAU,CAAC,GAAG,CAAC,IAAI,CAAC,EAAE,CAAC;YACzB,MAAM,CAAC,IAAI,IAAI,CAAC,CAAC;YACjB,SAAS;QACX,CAAC;QACD,IAAI,CAAC;YACH,UAAU,CAAC,IAAI,CAAC,CAAC;YACjB,MAAM,CAAC,OAAO,CAAC,IAAI,CAAC,IAAI,CAAC,CAAC;QAC5B,CAAC;QAAC,MAAM,CAAC;YACP,SAAS;QACX,CAAC;IACH,CAAC;IACD,OAAO,MAAM,CAAC;AAChB,CAAC"}
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/validate-assets-cli.d.ts b/tools/image-snapshotter/dist/validate-assets-cli.d.ts
new file mode 100644
index 000000000..eced80444
--- /dev/null
+++ b/tools/image-snapshotter/dist/validate-assets-cli.d.ts
@@ -0,0 +1,13 @@
+#!/usr/bin/env node
+interface MissingRef {
+    envelopePath: string;
+    objectName: string;
+    imageRel: string;
+}
+export interface ValidateResult {
+    missing: MissingRef[];
+    envelopesScanned: number;
+    imageRefsScanned: number;
+}
+export declare function validateSnapshotAssets(snapshotsDir: string): ValidateResult;
+export {};
diff --git a/tools/image-snapshotter/dist/validate-assets-cli.js b/tools/image-snapshotter/dist/validate-assets-cli.js
new file mode 100644
index 000000000..d17c1d618
--- /dev/null
+++ b/tools/image-snapshotter/dist/validate-assets-cli.js
@@ -0,0 +1,93 @@
+#!/usr/bin/env node
+/**
+ * Stage-2 snapshot validator: scan envelope JSONs for `data.image` refs
+ * and verify every referenced PNG exists on disk.
+ *
+ * Exits non-zero if any envelope references an asset that's missing — a
+ * common symptom of a half-captured run (capture started, was interrupted,
+ * envelope was written without the asset).
+ *
+ * Usage (from a plugin tree):
+ *   SNAPSHOTTER_PLUGIN_ROOT=/work image-snapshotter-validate-assets
+ *
+ * Or directly:
+ *   node dist/validate-assets-cli.js <snapshots-dir>
+ *
+ * Both `<envelope>.json` -> referenced `assets/<sha>.png` and the reverse
+ * (orphan assets) are reported, but only missing-asset failures cause a
+ * non-zero exit. Orphan detection is handled by `prune.ts` and stays
+ * advisory here.
+ */
+import { existsSync, readFileSync, readdirSync, statSync } from 'node:fs';
+import { join, resolve } from 'node:path';
+export function validateSnapshotAssets(snapshotsDir) {
+    const missing = [];
+    let envelopesScanned = 0;
+    let imageRefsScanned = 0;
+    if (!existsSync(snapshotsDir) || !statSync(snapshotsDir).isDirectory()) {
+        return { missing, envelopesScanned, imageRefsScanned };
+    }
+    const entries = readdirSync(snapshotsDir);
+    for (const name of entries) {
+        if (!name.endsWith('.json'))
+            continue;
+        const path = join(snapshotsDir, name);
+        envelopesScanned += 1;
+        let envelope;
+        try {
+            envelope = JSON.parse(readFileSync(path, 'utf8'));
+        }
+        catch {
+            // Malformed JSON is a hard error — bubble up via a synthetic miss.
+            missing.push({
+                envelopePath: path,
+                objectName: '<parse error>',
+                imageRel: '<n/a>',
+            });
+            continue;
+        }
+        const objects = envelope.objects ?? {};
+        for (const [objectName, entry] of Object.entries(objects)) {
+            const imageRel = entry?.data?.image;
+            if (typeof imageRel !== 'string')
+                continue; // not a Pass-2 entry
+            imageRefsScanned += 1;
+            const assetPath = join(snapshotsDir, imageRel);
+            if (!existsSync(assetPath)) {
+                missing.push({ envelopePath: path, objectName, imageRel });
+            }
+        }
+    }
+    return { missing, envelopesScanned, imageRefsScanned };
+}
+function pluginRoot() {
+    const fromEnv = process.env.SNAPSHOTTER_PLUGIN_ROOT;
+    if (fromEnv)
+        return resolve(fromEnv);
+    process.stderr.write('image-snapshotter-validate-assets: SNAPSHOTTER_PLUGIN_ROOT or a snapshots dir argument is required\n');
+    process.exit(2);
+}
+function main() {
+    const arg = process.argv[2];
+    const snapshotsDir = arg
+        ? resolve(arg)
+        : join(pluginRoot(), 'docs', 'snapshots');
+    const { missing, envelopesScanned, imageRefsScanned } = validateSnapshotAssets(snapshotsDir);
+    process.stdout.write(`validated ${envelopesScanned} envelope(s); ` +
+        `${imageRefsScanned} image reference(s) checked; ` +
+        `${missing.length} missing.\n`);
+    if (missing.length === 0)
+        return 0;
+    process.stderr.write(`\nMissing assets:\n`);
+    for (const m of missing) {
+        process.stderr.write(`  ${m.envelopePath} :: ${m.objectName} -> ${m.imageRel} (not on disk)\n`);
+    }
+    process.stderr.write(`\nRe-run \`image-snapshotter --update\` to recapture the missing assets.\n`);
+    return 1;
+}
+const isMain = import.meta.url === `file://${process.argv[1]}` ||
+    process.argv[1]?.endsWith('validate-assets-cli.js');
+if (isMain) {
+    process.exit(main());
+}
+//# sourceMappingURL=validate-assets-cli.js.map
\ No newline at end of file
diff --git a/tools/image-snapshotter/dist/validate-assets-cli.js.map b/tools/image-snapshotter/dist/validate-assets-cli.js.map
new file mode 100644
index 000000000..407fb6649
--- /dev/null
+++ b/tools/image-snapshotter/dist/validate-assets-cli.js.map
@@ -0,0 +1 @@
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diff --git a/tools/image-snapshotter/docker-entrypoint.sh b/tools/image-snapshotter/docker-entrypoint.sh
new file mode 100755
index 000000000..f2dab970b
--- /dev/null
+++ b/tools/image-snapshotter/docker-entrypoint.sh
@@ -0,0 +1,162 @@
+#!/usr/bin/env bash
+#
+# Pass 2 docs image-snapshotter entrypoint. Plugin-agnostic — the compose
+# file, server container name, and fixture output dir are passed in via env.
+#
+# 1. Generate per-block app.d fixtures from /work/docs into a workspace dir
+#    that's visible on the host (so the test server can bind-mount it).
+# 2. `docker compose -f $SNAPSHOTTER_COMPOSE_FILE up -d server` against a
+#    HOST-path bind-mount of those fixtures.
+# 3. Poll the server URL until it returns 200 — app.d evaluation adds
+#    startup time, so we allow up to 300s.
+# 4. Run `npx playwright test` to capture widget PNGs / merge JSON envelopes.
+# 5. Always tear the server back down before exiting, propagating
+#    Playwright's exit code.
+#
+# Required env (set by docker-compose.docs-snapshots.yml):
+#   SNAPSHOTTER_PLUGIN              Plugin short name; used in path slugs.
+#   SNAPSHOTTER_COMPOSE_FILE        Path (inside /workspace) to the server compose file.
+#   SNAPSHOTTER_SERVER_CONTAINER    Container name docker compose will create.
+#   HOST_PWD                        $PWD as seen by the host (for bind-mount paths).
+#   SNAPSHOTTER_PLUGIN_ROOT, SNAPSHOTTER_WIDGET_TYPE, SNAPSHOTTER_TARGET_SELECTOR
+#                                   Consumed by the playwright spec.
+
+set -u
+
+: "${SNAPSHOTTER_PLUGIN:?SNAPSHOTTER_PLUGIN is required}"
+: "${SNAPSHOTTER_COMPOSE_FILE:?SNAPSHOTTER_COMPOSE_FILE is required}"
+: "${SNAPSHOTTER_SERVER_CONTAINER:?SNAPSHOTTER_SERVER_CONTAINER is required}"
+: "${HOST_PWD:?HOST_PWD is required (parent compose must set HOST_PWD: \${PWD})}"
+
+COMPOSE_FILE="${SNAPSHOTTER_COMPOSE_FILE}"
+SERVER_URL="${SNAPSHOTTER_SERVER_HEALTH_URL:-http://server:10000/}"
+SERVER_CONTAINER="${SNAPSHOTTER_SERVER_CONTAINER}"
+
+# Where we write the generated app.d. /workspace == $HOST_PWD inside this
+# container, so /workspace/snapshot-results/<plugin>-app.d is visible on the
+# host at $HOST_PWD/snapshot-results/<plugin>-app.d.
+APPD_CONTAINER_PATH="/workspace/snapshot-results/${SNAPSHOTTER_PLUGIN}-app.d"
+
+# Mirror every line of output to a host-visible log file so post-mortems
+# don't require `docker logs` access. The path also lands inside the
+# bind-mounted /workspace so the file appears on the host at
+# $HOST_PWD/snapshot-results/<plugin>-snapshotter.log.
+LOG_DIR="/workspace/snapshot-results"
+LOG_FILE="${LOG_DIR}/${SNAPSHOTTER_PLUGIN}-snapshotter.log"
+mkdir -p "${LOG_DIR}"
+# Truncate so the file always reflects only the latest run.
+: > "${LOG_FILE}"
+# Re-open fds so EVERY line written after this point goes to both the
+# original terminal and the log file. tee runs in a process substitution so
+# its lifetime is bound to this shell.
+exec > >(tee -a "${LOG_FILE}") 2>&1
+echo "[entrypoint] log mirrored to host: snapshot-results/${SNAPSHOTTER_PLUGIN}-snapshotter.log"
+
+cleanup() {
+    echo "[entrypoint] tearing down server..."
+    if [ -f "${COMPOSE_FILE}" ]; then
+        docker compose -f "${COMPOSE_FILE}" down --remove-orphans || true
+    fi
+}
+trap cleanup EXIT
+
+# --- 1. Generate fixtures ------------------------------------------------
+echo "[entrypoint] generating per-block app.d fixtures..."
+rm -rf "${APPD_CONTAINER_PATH}"
+mkdir -p "${APPD_CONTAINER_PATH}"
+if ! node /work/dist/generate-fixtures-cli.js \
+        --docs /work/docs \
+        --out "${APPD_CONTAINER_PATH}"; then
+    echo "[entrypoint] fixture generation failed" >&2
+    exit 1
+fi
+
+# --- 2. Resolve HOST path and bring server up ----------------------------
+export PASS2_APPD_HOST_PATH="${HOST_PWD}/snapshot-results/${SNAPSHOTTER_PLUGIN}-app.d"
+# Tell the spec where to find the prefix map (container-local path).
+export SNAPSHOTTER_PREFIX_MAP="${APPD_CONTAINER_PATH}/prefix-map.json"
+
+# Tear down any stale container left behind by an earlier crashed run.
+docker rm -f "${SERVER_CONTAINER}" >/dev/null 2>&1 || true
+
+echo "[entrypoint] starting test server via ${COMPOSE_FILE}..."
+echo "[entrypoint]   PASS2_APPD_HOST_PATH=${PASS2_APPD_HOST_PATH}"
+if ! docker compose -f "${COMPOSE_FILE}" up -d server; then
+    echo "[entrypoint] failed to bring server up" >&2
+    exit 1
+fi
+
+# --- 3. Wait for readiness ----------------------------------------------
+echo "[entrypoint] waiting for ${SERVER_URL} to respond (up to 300s)..."
+i=0
+while [ $i -lt 150 ]; do
+    i=$((i + 1))
+    if curl --silent --fail --output /dev/null --connect-timeout 2 "${SERVER_URL}"; then
+        echo "[entrypoint] server is ready."
+        break
+    fi
+    state=$(docker inspect -f '{{.State.Status}}' "${SERVER_CONTAINER}" 2>/dev/null || echo "missing")
+    if [ "$state" != "running" ]; then
+        echo "[entrypoint] ${SERVER_CONTAINER} died during startup (state=$state)" >&2
+        echo "[entrypoint] ---- last 200 lines of server logs ----" >&2
+        docker logs --tail 200 "${SERVER_CONTAINER}" 2>&1 || true
+        echo "[entrypoint] ---- end of server logs ----" >&2
+        exit 1
+    fi
+    sleep 2
+    if [ $i -eq 150 ]; then
+        echo "[entrypoint] server failed to become ready at ${SERVER_URL} after 300s" >&2
+        echo "[entrypoint] ---- last 200 lines of server logs ----" >&2
+        docker logs --tail 200 "${SERVER_CONTAINER}" 2>&1 || true
+        echo "[entrypoint] ---- end of server logs ----" >&2
+        exit 1
+    fi
+done
+
+# --- 4. Capture ----------------------------------------------------------
+echo "[entrypoint] running playwright tests..."
+echo "[entrypoint]   target selector : ${SNAPSHOTTER_TARGET_SELECTOR:-<unset>}"
+echo "[entrypoint]   widget type     : ${SNAPSHOTTER_WIDGET_TYPE:-<unset>}"
+echo "[entrypoint]   plugin root     : ${SNAPSHOTTER_PLUGIN_ROOT:-<unset>}"
+echo "[entrypoint]   prefix map      : ${SNAPSHOTTER_PREFIX_MAP:-<unset>}"
+# Pre-capture inventory so we can compare after the run.
+SNAPSHOTS_HOST_DIR="${SNAPSHOTTER_PLUGIN_ROOT:-/work}/docs/snapshots"
+PRE_PNG=$(find "${SNAPSHOTS_HOST_DIR}/assets" -maxdepth 1 -name '*.png' 2>/dev/null | wc -l)
+PRE_ENV=$(find "${SNAPSHOTS_HOST_DIR}" -maxdepth 1 -name '*.json' 2>/dev/null | wc -l)
+echo "[entrypoint]   pre-capture PNGs in docs/snapshots/assets/  : ${PRE_PNG}"
+echo "[entrypoint]   pre-capture envelopes in docs/snapshots/    : ${PRE_ENV}"
+
+npx playwright test
+PLAYWRIGHT_EXIT=$?
+
+POST_PNG=$(find "${SNAPSHOTS_HOST_DIR}/assets" -maxdepth 1 -name '*.png' 2>/dev/null | wc -l)
+POST_ENV=$(find "${SNAPSHOTS_HOST_DIR}" -maxdepth 1 -name '*.json' 2>/dev/null | wc -l)
+POST_IMG=$(grep -l '"image"' "${SNAPSHOTS_HOST_DIR}"/*.json 2>/dev/null | wc -l)
+echo "[entrypoint] playwright finished with exit code ${PLAYWRIGHT_EXIT}."
+echo "[entrypoint]   post-capture PNGs in docs/snapshots/assets/        : ${POST_PNG} (delta ${POST_PNG}-${PRE_PNG})"
+echo "[entrypoint]   post-capture envelopes in docs/snapshots/          : ${POST_ENV} (delta ${POST_ENV}-${PRE_ENV})"
+echo "[entrypoint]   post-capture envelopes referencing a PNG           : ${POST_IMG}"
+if [ "${POST_PNG}" = "0" ] && [ "${PLAYWRIGHT_EXIT}" = "0" ]; then
+    echo "[entrypoint] WARNING: playwright reported success but zero PNGs were written." >&2
+    echo "[entrypoint] WARNING: most likely cause is that every chart.waitFor timed out" >&2
+    echo "[entrypoint] WARNING: (panels never registered, or the widget selector doesn't match)." >&2
+    echo "[entrypoint] WARNING: last 80 lines of server log follow:" >&2
+    docker logs --tail 80 "${SERVER_CONTAINER}" 2>&1 || true
+fi
+
+# --- 5. Validate that every envelope image reference exists on disk -------
+# This is Stage 2 of the snapshot validation pipeline. It catches the
+# "envelope was written, asset was not" failure mode that the docs site
+# would otherwise hit at MDX render time.
+echo "[entrypoint] validating snapshot assets..."
+if ! node /work/dist/validate-assets-cli.js "${SNAPSHOTS_HOST_DIR}"; then
+    VALIDATE_EXIT=$?
+    echo "[entrypoint] snapshot asset validation failed (exit ${VALIDATE_EXIT})." >&2
+    # Prefer reporting the playwright failure if there was one, otherwise
+    # surface the validator's exit code.
+    if [ "${PLAYWRIGHT_EXIT}" = "0" ]; then
+        exit "${VALIDATE_EXIT}"
+    fi
+fi
+
+exit "${PLAYWRIGHT_EXIT}"
diff --git a/tools/image-snapshotter/package-lock.json b/tools/image-snapshotter/package-lock.json
new file mode 100644
index 000000000..3e299e5f8
--- /dev/null
+++ b/tools/image-snapshotter/package-lock.json
@@ -0,0 +1,2913 @@
+{
+  "name": "@deephaven/image-snapshotter",
+  "version": "0.1.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "@deephaven/image-snapshotter",
+      "version": "0.1.0",
+      "dependencies": {
+        "@playwright/test": "1.44.1",
+        "glob": "^10.4.5",
+        "mdast-util-from-markdown": "^2.0.3"
+      },
+      "bin": {
+        "image-snapshotter": "dist/cli.js",
+        "image-snapshotter-fixture-gen": "dist/generate-fixtures-cli.js",
+        "image-snapshotter-validate-assets": "dist/validate-assets-cli.js"
+      },
+      "devDependencies": {
+        "@types/node": "^20.14.0",
+        "typescript": "^5.4.5",
+        "vitest": "^1.6.0"
+      }
+    },
+    "node_modules/@esbuild/aix-ppc64": {
+      "version": "0.21.5",
+      "resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.21.5.tgz",
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+      "cpu": [
+        "ppc64"
+      ],
+      "dev": true,
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "aix"
+      ],
+      "engines": {
+        "node": ">=12"
+      }
+    },
+    "node_modules/@esbuild/android-arm": {
+      "version": "0.21.5",
+      "resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.21.5.tgz",
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+      "cpu": [
+        "arm"
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+      "dev": true,
+      "license": "MIT",
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+      "os": [
+        "android"
+      ],
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+    "node_modules/@esbuild/android-arm64": {
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+      "license": "MIT",
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+        "android"
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+      "engines": {
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+    "node_modules/@esbuild/android-x64": {
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+      "resolved": "https://registry.npmjs.org/@esbuild/android-x64/-/android-x64-0.21.5.tgz",
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+      "license": "MIT",
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+        "darwin"
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+    "node_modules/@esbuild/darwin-x64": {
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+        "x64"
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diff --git a/tools/image-snapshotter/package.json b/tools/image-snapshotter/package.json
new file mode 100644
index 000000000..d16f3c5e9
--- /dev/null
+++ b/tools/image-snapshotter/package.json
@@ -0,0 +1,29 @@
+{
+  "name": "@deephaven/image-snapshotter",
+  "version": "0.1.0",
+  "private": true,
+  "type": "module",
+  "description": "Pass 2 docs image snapshotter. Walks a plugin's docs/*.md, captures widget PNGs via Playwright, and writes salmon-compatible JSON envelopes. Plugin-agnostic: the target selector, widget type, fixture app id, and server container name come from the SNAPSHOTTER_* env vars.",
+  "bin": {
+    "image-snapshotter": "./dist/cli.js",
+    "image-snapshotter-fixture-gen": "./dist/generate-fixtures-cli.js",
+    "image-snapshotter-validate-assets": "./dist/validate-assets-cli.js"
+  },
+  "main": "./dist/cli.js",
+  "scripts": {
+    "build": "tsc -p .",
+    "clean": "rm -rf dist",
+    "test": "vitest run",
+    "test:watch": "vitest"
+  },
+  "dependencies": {
+    "@playwright/test": "1.44.1",
+    "glob": "^10.4.5",
+    "mdast-util-from-markdown": "^2.0.3"
+  },
+  "devDependencies": {
+    "@types/node": "^20.14.0",
+    "typescript": "^5.4.5",
+    "vitest": "^1.6.0"
+  }
+}
diff --git a/tools/image-snapshotter/playwright.config.ts b/tools/image-snapshotter/playwright.config.ts
new file mode 100644
index 000000000..c98c35336
--- /dev/null
+++ b/tools/image-snapshotter/playwright.config.ts
@@ -0,0 +1,51 @@
+/**
+ * Playwright config for the docs image-snapshotter capture pass.
+ *
+ * Determinism notes:
+ *   - viewport: 1600x900 — wide enough that the IDE panel content area can
+ *     host an 860x573 chart container with IDE chrome around it
+ *   - chromium 1.44.1 (pinned by the Dockerfile playwright image)
+ *   - single worker; we mutate JSON files on disk per-page
+ */
+import type { PlaywrightTestConfig } from '@playwright/test';
+import { devices } from '@playwright/test';
+
+// SNAPSHOTTER_BASE_URL is the IDE URL. The docs-snapshots compose pipeline
+// injects `http://server:10000/ide/`; local invocations should set it to
+// `http://localhost:10000/ide/` (or whatever a hand-started server uses).
+const baseURL =
+  process.env.SNAPSHOTTER_BASE_URL ?? 'http://localhost:10000/ide/';
+
+const config: PlaywrightTestConfig = {
+  testDir: './tests',
+  // Only match Playwright-style `*.spec.ts` files. Without this, Playwright's
+  // default glob also picks up `*.test.ts` — which would drag in our vitest
+  // unit-test files (e.g. `extract.test.ts`). Vitest's `@vitest/expect`
+  // collides with Playwright's `expect` on `Symbol($$jest-matchers-object)`
+  // the moment both are loaded into the same process, killing the runner.
+  testMatch: /.*\.spec\.ts$/,
+  // The capture pass mutates JSON envelopes on disk and we want strictly
+  // serialized execution to make orphan-pruning correctness obvious.
+  fullyParallel: false,
+  workers: 1,
+  timeout: 180 * 1000,
+  expect: { timeout: 15000 },
+  forbidOnly: !!process.env.CI,
+  retries: 0,
+  reporter: process.env.CI ? [['github'], ['list']] : [['list']],
+  use: {
+    actionTimeout: 0,
+    navigationTimeout: 60 * 1000,
+    baseURL,
+    trace: 'retain-on-failure',
+    video: 'retain-on-failure',
+  },
+  projects: [
+    {
+      name: 'chromium',
+      use: { ...devices['Desktop Chrome'], viewport: { width: 1600, height: 900 } },
+    },
+  ],
+};
+
+export default config;
diff --git a/tools/image-snapshotter/src/cli.ts b/tools/image-snapshotter/src/cli.ts
new file mode 100644
index 000000000..16f64ae60
--- /dev/null
+++ b/tools/image-snapshotter/src/cli.ts
@@ -0,0 +1,159 @@
+#!/usr/bin/env node
+/**
+ * image-snapshotter CLI
+ *
+ * Pass 2 docs image snapshotter. Plugin-agnostic — the target widget
+ * selector, widget type, and fixture app id are read from `SNAPSHOTTER_*`
+ * env vars (see docker-entrypoint.sh and docker-compose.docs-snapshots.yml).
+ *
+ *   image-snapshotter             capture + prune; fail on dirty git
+ *   image-snapshotter --update    capture + prune; allow dirty
+ *   image-snapshotter --prune-only  only orphan-prune
+ *   image-snapshotter --check     same as default (CI mode)
+ *
+ * Default behavior:
+ *   1. Run `npx playwright test` against the spec in `tests/`. The spec
+ *      does the actual widget capture + JSON envelope merge.
+ *   2. Run orphan-asset pruning.
+ *   3. Unless --update was passed, run `git status --porcelain` against
+ *      `docs/snapshots/` and exit 1 if anything changed.
+ *
+ * Paths are resolved relative to SNAPSHOTTER_PLUGIN_ROOT (required) so the
+ * tool can be invoked once per plugin from anywhere in the tree.
+ */
+import { spawnSync } from 'node:child_process';
+import { existsSync } from 'node:fs';
+import { dirname, join, resolve } from 'node:path';
+import { fileURLToPath } from 'node:url';
+import { pruneOrphanAssets } from './prune.js';
+
+interface Args {
+  update: boolean;
+  pruneOnly: boolean;
+  check: boolean;
+  help: boolean;
+}
+
+function parseArgs(argv: string[]): Args {
+  const a: Args = { update: false, pruneOnly: false, check: false, help: false };
+  for (const v of argv) {
+    switch (v) {
+      case '--update':
+        a.update = true;
+        break;
+      case '--prune-only':
+      case '--prune':
+        a.pruneOnly = true;
+        break;
+      case '--check':
+        a.check = true;
+        break;
+      case '--help':
+      case '-h':
+        a.help = true;
+        break;
+      default:
+        process.stderr.write(`Unknown argument: ${v}\n`);
+        a.help = true;
+        break;
+    }
+  }
+  return a;
+}
+
+function printHelp(): void {
+  const help = `image-snapshotter — Pass 2 docs widget snapshotter
+
+Usage:
+  image-snapshotter              Capture + prune; fail on dirty git (CI mode).
+  image-snapshotter --update     Capture + prune; do not fail on dirty git.
+  image-snapshotter --prune-only Only run orphan-asset pruning.
+  image-snapshotter --check      Same as the default (explicit CI mode).
+  image-snapshotter --help       Show this message.
+
+Required env:
+  SNAPSHOTTER_PLUGIN_ROOT      Plugin root; docs/, docs/snapshots/ live under it.
+  SNAPSHOTTER_TARGET_SELECTOR  CSS selector for the widget to screenshot.
+  SNAPSHOTTER_WIDGET_TYPE      Widget type string stamped into JSON envelopes.
+
+Optional env:
+  SNAPSHOTTER_BASE_URL         IDE URL (default http://localhost:10000/ide/).
+  SNAPSHOTTER_APP_ID           Deephaven app.d id (default 'docs.examples').
+  SNAPSHOTTER_APP_NAME         Human label for the app.d manifest.
+
+Snapshot envelope format:
+  docs/snapshots/<code_md5>.json with
+    { "file": "<page>.md", "objects": { "<name>": { "type": "...", "data": ... } } }
+  where code_md5 = md5(code.strip() + "-python") (hex, lowercase).
+`;
+  process.stdout.write(help);
+}
+
+function pluginRoot(): string {
+  const fromEnv = process.env.SNAPSHOTTER_PLUGIN_ROOT;
+  if (fromEnv) return resolve(fromEnv);
+  process.stderr.write(
+    'image-snapshotter: SNAPSHOTTER_PLUGIN_ROOT is required\n',
+  );
+  process.exit(2);
+}
+
+function runPlaywright(toolDir: string): number {
+  const r = spawnSync('npx', ['playwright', 'test'], {
+    cwd: toolDir,
+    stdio: 'inherit',
+    env: process.env,
+  });
+  return r.status ?? 1;
+}
+
+function checkClean(snapshotsDir: string): number {
+  const r = spawnSync('git', ['status', '--porcelain', snapshotsDir], {
+    stdio: ['inherit', 'pipe', 'inherit'],
+    encoding: 'utf8',
+  });
+  const out = (r.stdout ?? '').trim();
+  if (out.length === 0) return 0;
+  process.stderr.write(`docs/snapshots/ is dirty:\n${out}\n`);
+  process.stderr.write(`Re-run with --update to accept the changes.\n`);
+  return 1;
+}
+
+function main(): number {
+  const args = parseArgs(process.argv.slice(2));
+  if (args.help) {
+    printHelp();
+    return 0;
+  }
+
+  const root = pluginRoot();
+  const toolDir = resolve(dirname(fileURLToPath(import.meta.url)), '..');
+  const snapshotsDir = join(root, 'docs', 'snapshots');
+
+  if (!existsSync(snapshotsDir)) {
+    process.stderr.write(`Expected snapshots dir at ${snapshotsDir} — bailing.\n`);
+    return 1;
+  }
+
+  if (!args.pruneOnly) {
+    const code = runPlaywright(toolDir);
+    if (code !== 0) {
+      process.stderr.write(`playwright capture failed (exit ${code}).\n`);
+      return code;
+    }
+  }
+
+  const pruneResult = pruneOrphanAssets(snapshotsDir);
+  process.stdout.write(
+    `pruned ${pruneResult.deleted.length} orphan asset(s); ` +
+      `kept ${pruneResult.kept}, referenced ${pruneResult.referenced}\n`,
+  );
+  for (const p of pruneResult.deleted) process.stdout.write(`  removed ${p}\n`);
+
+  if (args.pruneOnly) return 0;
+  if (args.update) return 0;
+  return checkClean(snapshotsDir);
+}
+
+const code = main();
+process.exit(code);
diff --git a/tools/image-snapshotter/src/extract.ts b/tools/image-snapshotter/src/extract.ts
new file mode 100644
index 000000000..a70ed24db
--- /dev/null
+++ b/tools/image-snapshotter/src/extract.ts
@@ -0,0 +1,148 @@
+/**
+ * Code-block walker for docs/*.md.
+ *
+ * --------------------------------------------------------------------------
+ *  md5 ALGORITHM CONTRACT
+ *
+ *  Block hash = md5( code.trim() + "-python" ), hex digest, lowercase.
+ *
+ *  This MUST stay byte-for-byte aligned with salmon's per-block hash so that
+ *  Pass 1 (salmon, tables) and Pass 2 (this tool, charts) write into the
+ *  same `<md5>.json` envelopes. The salmon-changes plan requires salmon to
+ *  match this exact algorithm; if it ever changes here, that plan must be
+ *  updated and salmon's snapshotter re-aligned in lockstep.
+ * --------------------------------------------------------------------------
+ *
+ * The fence walker is backed by a real CommonMark parser
+ * (`mdast-util-from-markdown`) so it sees fences the same way the docs site
+ * eventually does. Earlier revisions used a column-0 regex which silently
+ * skipped fences indented under a list item — a quiet correctness bug that
+ * cost an afternoon of debugging on README.md's quickstart.
+ */
+import { createHash } from 'node:crypto';
+import { readFileSync, readdirSync, statSync } from 'node:fs';
+import { join, basename } from 'node:path';
+import { fromMarkdown } from 'mdast-util-from-markdown';
+import type { Code, Root, RootContent } from 'mdast';
+
+/** Stable across runs and across hosts. See contract block above. */
+export function codeMd5(code: string): string {
+  const normalized = code.trim() + '-python';
+  return createHash('md5').update(normalized, 'utf8').digest('hex').toLowerCase();
+}
+
+export interface Block {
+  /** Page filename, e.g. `"candlestick.md"`. */
+  page: string;
+  /** Raw code body (no fence lines). */
+  code: string;
+  /** Variable names to capture from this block, parsed from `order=a,b,c`. */
+  order: string[];
+  /** True if the block opts out of snapshotting. */
+  skip: boolean;
+  /** Hex md5 of `code.trim() + "-python"`. */
+  md5: string;
+}
+
+/**
+ * Parse a fence info string of the form `order=a,b,c skip-test foo=bar`. The
+ * `lang` token (e.g. `python`) has already been stripped by the parser and
+ * lives in `node.lang`; what arrives here is the `meta` field, which is the
+ * trailing portion of the info string.
+ */
+function parseMeta(meta: string | null | undefined): {
+  order: string[];
+  skipFlag: boolean;
+} {
+  if (!meta) return { order: [], skipFlag: false };
+  const tokens = meta
+    .trim()
+    .split(/\s+/)
+    .filter(t => t.length > 0);
+  let order: string[] = [];
+  let skipFlag = false;
+  for (const tok of tokens) {
+    if (tok === 'skip-test' || tok === 'no-snapshot') {
+      skipFlag = true;
+    } else if (tok.startsWith('order=')) {
+      order = tok
+        .slice('order='.length)
+        .split(',')
+        .map(s => s.trim())
+        .filter(s => s.length > 0);
+    }
+  }
+  return { order, skipFlag };
+}
+
+/**
+ * Yield every `code` node in `tree` (any depth), including ones nested
+ * inside list items / block quotes / etc.
+ */
+function* iterCodeNodes(tree: Root | RootContent): Generator<Code> {
+  if (tree.type === 'code') {
+    yield tree;
+    return;
+  }
+  if ('children' in tree && Array.isArray(tree.children)) {
+    for (const child of tree.children) {
+      yield* iterCodeNodes(child as RootContent);
+    }
+  }
+}
+
+/** Pull blocks out of a single markdown file. */
+export function extractBlocks(page: string, source: string): Block[] {
+  const tree = fromMarkdown(source);
+  const blocks: Block[] = [];
+  for (const node of iterCodeNodes(tree)) {
+    const lang = (node.lang ?? '').toLowerCase();
+    if (lang !== 'python' && lang !== 'py') continue;
+    const code = node.value ?? '';
+    const { order, skipFlag } = parseMeta(node.meta);
+    const firstLine = code.split('\n', 1)[0]?.trim() ?? '';
+    const skipComment = firstLine === '# no-snapshot';
+    blocks.push({
+      page,
+      code,
+      order,
+      skip: skipFlag || skipComment,
+      md5: codeMd5(code),
+    });
+  }
+  return blocks;
+}
+
+/** Recursively walk `docsDir` for `.md` files and return every block found. */
+export function walkDocs(docsDir: string): Block[] {
+  const blocks: Block[] = [];
+  const stack: string[] = [docsDir];
+  while (stack.length > 0) {
+    const dir = stack.pop()!;
+    let entries: string[];
+    try {
+      entries = readdirSync(dir);
+    } catch {
+      continue;
+    }
+    for (const name of entries) {
+      const full = join(dir, name);
+      let st;
+      try {
+        st = statSync(full);
+      } catch {
+        continue;
+      }
+      if (st.isDirectory()) {
+        // Skip build output and asset dumps.
+        if (name === 'build' || name === '_assets' || name === 'snapshots') continue;
+        stack.push(full);
+        continue;
+      }
+      if (!name.endsWith('.md')) continue;
+      const src = readFileSync(full, 'utf8');
+      for (const b of extractBlocks(basename(full), src)) blocks.push(b);
+    }
+  }
+  return blocks;
+}
diff --git a/tools/image-snapshotter/src/fixtures.ts b/tools/image-snapshotter/src/fixtures.ts
new file mode 100644
index 000000000..4fc072f01
--- /dev/null
+++ b/tools/image-snapshotter/src/fixtures.ts
@@ -0,0 +1,219 @@
+/**
+ * Generate per-block Python fixture files so the docs examples become
+ * importable app.d panels.
+ *
+ * Each non-skip `Block` becomes its own `<outDir>/block_<md5>.py` file. The
+ * block's code runs inside a uniquely-named function so its locals stay
+ * isolated; only the names listed in `order=` are hoisted into module scope,
+ * and each hoisted name is prefixed with the first 8 hex chars of the block
+ * md5 to avoid collisions across pages that reuse names like `primary`,
+ * `ohlc`, `stocks`, etc.
+ *
+ * Output layout:
+ *
+ *     <outDir>/
+ *       block_<md5_1>.py
+ *       block_<md5_2>.py
+ *       ...
+ *       tests.app           # Deephaven app.d manifest
+ *
+ * The output directory is treated as a build artifact and should be
+ * gitignored.
+ */
+import {
+  mkdirSync,
+  writeFileSync,
+  existsSync,
+  readdirSync,
+  unlinkSync,
+} from 'node:fs';
+import { join } from 'node:path';
+import type { Block } from './extract.js';
+
+export interface GenerateAppdResult {
+  blockCount: number;
+  manifestPath: string;
+  /** md5 → prefix used to mangle that block's exported names. */
+  prefixMap: Map<string, string>;
+}
+
+/**
+ * Compute the per-block prefix used both as the function name and as the
+ * leading segment of every exported global. We MUST start with a letter
+ * because Python identifiers can't begin with a digit (md5 hashes very
+ * often do). `b` for "block".
+ *
+ * Single source of truth — fixtures, the manifest, the prefix-map, and
+ * the spec's `mangle()` all read this.
+ */
+export function blockPrefix(md5: string): string {
+  return `b${md5.slice(0, 8)}`;
+}
+
+/**
+ * Build the body of a single per-block fixture file.
+ * Exposed for unit tests.
+ */
+export function renderBlockFile(block: Block, page: string): string {
+  // `prefix` is what user-visible exported globals get tagged with — it
+  // must be a valid Python identifier (i.e. start with a letter), so it
+  // carries the leading `b` from `blockPrefix()`. The internal function
+  // name and locals dict are private (`_block_<md5_8>`) and don't need
+  // the `b` since the leading underscore already makes them valid.
+  const md5_8 = block.md5.slice(0, 8);
+  const prefix = blockPrefix(block.md5);
+  const funcName = `_block_${md5_8}`;
+  const localsVar = `_block_${md5_8}_locals`;
+  const orderTxt = block.order.length > 0 ? block.order.join(',') : '';
+
+  // Indent each line of the original code by four spaces so it sits inside
+  // the wrapper function. Preserve blank lines but don't leave trailing
+  // whitespace on them.
+  const body = block.code
+    .replace(/\s+$/g, '')
+    .split('\n')
+    .map(line => (line.length === 0 ? '' : '    ' + line))
+    .join('\n');
+
+  const lines: string[] = [
+    `# Auto-generated by @deephaven/image-snapshotter. Do not edit.`,
+    `# Source: docs/${page}`,
+    `# Block md5: ${block.md5}`,
+    `# order=${orderTxt}`,
+    ``,
+    ``,
+    `def ${funcName}():`,
+    body,
+    `    return locals()`,
+    ``,
+    ``,
+    `${localsVar} = ${funcName}()`,
+    ``,
+  ];
+  for (const name of block.order) {
+    lines.push(`${prefix}_${name} = ${localsVar}[${JSON.stringify(name)}]`);
+  }
+  // Trailing newline so the file ends cleanly.
+  lines.push('');
+  return lines.join('\n');
+}
+
+/**
+ * Build the app.d manifest body listing every block fixture file.
+ * Exposed for unit tests.
+ */
+export function renderManifest(
+  blockFileNames: string[],
+  appId: string = process.env.SNAPSHOTTER_APP_ID ?? 'docs.examples',
+  appName: string = process.env.SNAPSHOTTER_APP_NAME ?? 'Docs Examples',
+): string {
+  const lines: string[] = [
+    `type=script`,
+    `scriptType=python`,
+    `enabled=true`,
+    `id=${appId}`,
+    `name=${appName}`,
+  ];
+  blockFileNames.forEach((name, idx) => {
+    lines.push(`file_${idx}=${name}`);
+  });
+  return lines.join('\n') + '\n';
+}
+
+/**
+ * Emit one `block_<md5>.py` per non-skip block plus a `tests.app` manifest
+ * into `outDir`. Stale `block_*.py` files (e.g. blocks that were removed
+ * from docs) are cleaned up. Returns counts plus the md5→prefix map so
+ * callers can translate display names to mangled global names.
+ */
+export function generateAppdFixtures(
+  blocks: Block[],
+  outDir: string,
+): GenerateAppdResult {
+  mkdirSync(outDir, { recursive: true });
+
+  const nonSkip = blocks.filter(b => !b.skip);
+
+  // Dedupe by md5 — identical code in different pages would otherwise
+  // collide on filename anyway, and the prefix is keyed by md5 so they'd
+  // get the same mangled names regardless.
+  const seen = new Map<string, Block>();
+  for (const b of nonSkip) {
+    if (!seen.has(b.md5)) seen.set(b.md5, b);
+  }
+
+  const prefixMap = new Map<string, string>();
+  const writtenFiles = new Set<string>();
+  const blockFileNames: string[] = [];
+
+  // Stable file ordering by md5 so the manifest diffs cleanly.
+  const orderedBlocks = Array.from(seen.values()).sort((a, b) =>
+    a.md5.localeCompare(b.md5),
+  );
+
+  for (const block of orderedBlocks) {
+    const prefix = blockPrefix(block.md5);
+    prefixMap.set(block.md5, prefix);
+    const fileName = `block_${block.md5}.py`;
+    const filePath = join(outDir, fileName);
+    writeFileSync(filePath, renderBlockFile(block, block.page), 'utf8');
+    writtenFiles.add(fileName);
+    blockFileNames.push(fileName);
+  }
+
+  const manifestPath = join(outDir, 'tests.app');
+  writeFileSync(manifestPath, renderManifest(blockFileNames), 'utf8');
+  writtenFiles.add('tests.app');
+
+  // Sweep stale files left over from previous runs (renamed/removed blocks).
+  if (existsSync(outDir)) {
+    for (const f of readdirSync(outDir)) {
+      if (!f.startsWith('block_') || !f.endsWith('.py')) {
+        if (f !== 'tests.app') continue;
+      }
+      if (!writtenFiles.has(f)) {
+        try {
+          unlinkSync(join(outDir, f));
+        } catch {
+          // ignore
+        }
+      }
+    }
+  }
+
+  return {
+    blockCount: orderedBlocks.length,
+    manifestPath,
+    prefixMap,
+  };
+}
+
+// ---------------------------------------------------------------------------
+// Legacy per-page fixture writer.
+//
+// Older flows (local dev) imported `generateFixtures` to write one .py per
+// docs page. Kept here as a thin compatibility shim that delegates to the
+// new per-block generator so existing callers don't break.
+// ---------------------------------------------------------------------------
+
+export interface FixtureWrite {
+  page: string;
+  pyPath: string;
+  blockCount: number;
+}
+
+export function generateFixtures(blocks: Block[], outDir: string): FixtureWrite[] {
+  const res = generateAppdFixtures(blocks, outDir);
+  // Roll up per-page counts for the legacy return shape.
+  const counts = new Map<string, number>();
+  for (const b of blocks) {
+    if (b.skip) continue;
+    counts.set(b.page, (counts.get(b.page) ?? 0) + 1);
+  }
+  void res;
+  return Array.from(counts.entries()).map(([page, blockCount]) => ({
+    page,
+    pyPath: join(outDir, 'tests.app'),
+    blockCount,
+  }));
+}
diff --git a/tools/image-snapshotter/src/generate-fixtures-cli.ts b/tools/image-snapshotter/src/generate-fixtures-cli.ts
new file mode 100644
index 000000000..ce2c2180c
--- /dev/null
+++ b/tools/image-snapshotter/src/generate-fixtures-cli.ts
@@ -0,0 +1,113 @@
+#!/usr/bin/env node
+/**
+ * Generate per-block app.d fixtures from docs/*.md.
+ *
+ * Pass 2's docker entrypoint runs this just before starting the test
+ * server. The server is then booted with `-Ddeephaven.application.dir`
+ * pointing at the output directory, so every docs example is pre-loaded
+ * as a panel before Playwright connects.
+ *
+ * Usage:
+ *
+ *   image-snapshotter-fixture-gen --docs <docsDir> --out <outDir>
+ *
+ * Falls back to SNAPSHOTTER_PLUGIN_ROOT/docs when --docs is omitted so
+ * the in-container path (where the plugin source isn't laid out the same
+ * way) can be configured by env var like the spec already is.
+ */
+import { mkdirSync, writeFileSync } from 'node:fs';
+import { join, resolve } from 'node:path';
+import { walkDocs } from './extract.js';
+import { generateAppdFixtures } from './fixtures.js';
+
+interface CliArgs {
+  docs?: string;
+  out?: string;
+  help: boolean;
+}
+
+function parseArgs(argv: string[]): CliArgs {
+  const a: CliArgs = { help: false };
+  for (let i = 0; i < argv.length; i += 1) {
+    const v = argv[i];
+    switch (v) {
+      case '--docs':
+        a.docs = argv[++i];
+        break;
+      case '--out':
+        a.out = argv[++i];
+        break;
+      case '-h':
+      case '--help':
+        a.help = true;
+        break;
+      default:
+        process.stderr.write(`Unknown argument: ${v}\n`);
+        a.help = true;
+    }
+  }
+  return a;
+}
+
+function printHelp(): void {
+  process.stdout.write(`image-snapshotter-fixture-gen — emit per-block app.d fixtures from docs/*.md
+
+Usage:
+  image-snapshotter-fixture-gen --docs <docsDir> --out <outDir>
+
+Environment:
+  SNAPSHOTTER_PLUGIN_ROOT  Used to derive docsDir when --docs is omitted
+                           (docsDir = $SNAPSHOTTER_PLUGIN_ROOT/docs).
+
+Writes:
+  <outDir>/block_<md5>.py    one file per non-skip block
+  <outDir>/tests.app         Deephaven app.d manifest pointing at all blocks
+  <outDir>/prefix-map.json   md5 → 8-char prefix map (consumed by spec)
+`);
+}
+
+function main(): number {
+  const args = parseArgs(process.argv.slice(2));
+  if (args.help) {
+    printHelp();
+    return 0;
+  }
+
+  let docsDir = args.docs;
+  if (!docsDir) {
+    const root = process.env.SNAPSHOTTER_PLUGIN_ROOT;
+    if (root) docsDir = join(root, 'docs');
+  }
+  if (!docsDir) {
+    process.stderr.write(
+      'image-snapshotter-fixture-gen: --docs is required (or set SNAPSHOTTER_PLUGIN_ROOT)\n',
+    );
+    return 2;
+  }
+  if (!args.out) {
+    process.stderr.write('image-snapshotter-fixture-gen: --out is required\n');
+    return 2;
+  }
+
+  const docsAbs = resolve(docsDir);
+  const outAbs = resolve(args.out);
+  mkdirSync(outAbs, { recursive: true });
+
+  const blocks = walkDocs(docsAbs);
+  const result = generateAppdFixtures(blocks, outAbs);
+
+  // Persist the md5→prefix map so the Playwright spec can mangle names
+  // when opening panels. JSON object is enough; the spec re-loads it as
+  // Record<string, string>.
+  const prefixMap: Record<string, string> = {};
+  for (const [md5, prefix] of result.prefixMap) prefixMap[md5] = prefix;
+  const prefixMapPath = join(outAbs, 'prefix-map.json');
+  writeFileSync(prefixMapPath, JSON.stringify(prefixMap, null, 2) + '\n', 'utf8');
+
+  process.stdout.write(
+    `image-snapshotter-fixture-gen: wrote ${result.blockCount} block file(s) + manifest to ${outAbs}\n`,
+  );
+  return 0;
+}
+
+process.exit(main());
diff --git a/tools/image-snapshotter/src/merge.ts b/tools/image-snapshotter/src/merge.ts
new file mode 100644
index 000000000..9469ea824
--- /dev/null
+++ b/tools/image-snapshotter/src/merge.ts
@@ -0,0 +1,67 @@
+/**
+ * Read / merge / write snapshot JSON envelopes.
+ *
+ * Envelope shape (kept stable so salmon Pass 1 and Pass 2 can co-author):
+ *
+ *   {
+ *     "file": "<docs page filename>",
+ *     "objects": {
+ *       "<variable_name>": { "type": "<fqn>", "data": ... }
+ *     }
+ *   }
+ *
+ * Pass 1 (salmon, tables) and Pass 2 (this tool, charts) both write into the
+ * same `<code_md5>.json` file. The merge is additive: writing an `objects`
+ * key never overwrites an existing one set by salmon (tables); chart entries
+ * land alongside.
+ */
+import { mkdirSync, readFileSync, renameSync, writeFileSync, existsSync } from 'node:fs';
+import { dirname } from 'node:path';
+
+export interface SnapshotObject {
+  type: string;
+  data: unknown;
+}
+
+export interface SnapshotEnvelope {
+  file: string;
+  objects: Record<string, SnapshotObject>;
+}
+
+/**
+ * Load `path` if it exists; otherwise return a fresh envelope for `page`.
+ * Salmon-authored keys (`file`, `objects.*`) are preserved verbatim.
+ */
+export function readOrInit(path: string, page: string): SnapshotEnvelope {
+  if (!existsSync(path)) {
+    return { file: page, objects: {} };
+  }
+  const raw = readFileSync(path, 'utf8');
+  const parsed = JSON.parse(raw) as Partial<SnapshotEnvelope>;
+  const env: SnapshotEnvelope = {
+    file: typeof parsed.file === 'string' ? parsed.file : page,
+    objects: parsed.objects && typeof parsed.objects === 'object' ? { ...parsed.objects } : {},
+  };
+  return env;
+}
+
+/**
+ * Write `env` to `path` atomically (tmp file + rename) so that a half-written
+ * JSON can never poison the repo state. Pretty-prints with stable key order.
+ */
+export function writeAtomic(path: string, env: SnapshotEnvelope): void {
+  mkdirSync(dirname(path), { recursive: true });
+  const stable = stableEnvelope(env);
+  const body = JSON.stringify(stable, null, 2) + '\n';
+  const tmp = `${path}.tmp-${process.pid}-${Date.now()}`;
+  writeFileSync(tmp, body, 'utf8');
+  renameSync(tmp, path);
+}
+
+/** Sort `objects` keys so the diff stays stable across runs. */
+function stableEnvelope(env: SnapshotEnvelope): SnapshotEnvelope {
+  const names = Object.keys(env.objects).sort();
+  const objects: Record<string, SnapshotObject> = {};
+  for (const n of names) objects[n] = env.objects[n];
+  return { file: env.file, objects };
+}
diff --git a/tools/image-snapshotter/src/prune.ts b/tools/image-snapshotter/src/prune.ts
new file mode 100644
index 000000000..38cffb9c2
--- /dev/null
+++ b/tools/image-snapshotter/src/prune.ts
@@ -0,0 +1,82 @@
+/**
+ * Orphan asset cleanup.
+ *
+ * Walks `<snapshotsDir>/*.json`, collects every `objects[*].data.image`
+ * value, then deletes any `<snapshotsDir>/assets/*.png` that is not in the
+ * referenced set. Returns the list of deleted asset paths.
+ */
+import { readdirSync, readFileSync, statSync, unlinkSync, existsSync } from 'node:fs';
+import { join } from 'node:path';
+
+export interface PruneResult {
+  deleted: string[];
+  kept: number;
+  referenced: number;
+}
+
+interface ObjEntry {
+  type?: unknown;
+  data?: { image?: unknown } & Record<string, unknown>;
+}
+
+export function collectReferencedAssets(snapshotsDir: string): Set<string> {
+  const referenced = new Set<string>();
+  if (!existsSync(snapshotsDir)) return referenced;
+  for (const name of readdirSync(snapshotsDir)) {
+    if (!name.endsWith('.json')) continue;
+    const full = join(snapshotsDir, name);
+    let raw: string;
+    try {
+      raw = readFileSync(full, 'utf8');
+    } catch {
+      continue;
+    }
+    let parsed: { objects?: Record<string, ObjEntry> };
+    try {
+      parsed = JSON.parse(raw);
+    } catch {
+      continue;
+    }
+    const objs = parsed.objects ?? {};
+    for (const key of Object.keys(objs)) {
+      const data = objs[key]?.data;
+      if (data && typeof data === 'object' && typeof data.image === 'string') {
+        // Stored as `assets/<sha>.png` (relative). Normalize to basename.
+        const image = data.image;
+        const slash = image.lastIndexOf('/');
+        referenced.add(slash >= 0 ? image.slice(slash + 1) : image);
+      }
+    }
+  }
+  return referenced;
+}
+
+export function pruneOrphanAssets(snapshotsDir: string): PruneResult {
+  const assetsDir = join(snapshotsDir, 'assets');
+  const result: PruneResult = { deleted: [], kept: 0, referenced: 0 };
+  if (!existsSync(assetsDir)) return result;
+
+  const referenced = collectReferencedAssets(snapshotsDir);
+  result.referenced = referenced.size;
+
+  for (const name of readdirSync(assetsDir)) {
+    if (!name.endsWith('.png')) continue;
+    const full = join(assetsDir, name);
+    try {
+      if (!statSync(full).isFile()) continue;
+    } catch {
+      continue;
+    }
+    if (referenced.has(name)) {
+      result.kept += 1;
+      continue;
+    }
+    try {
+      unlinkSync(full);
+      result.deleted.push(full);
+    } catch {
+      // ignore
+    }
+  }
+  return result;
+}
diff --git a/tools/image-snapshotter/src/validate-assets-cli.ts b/tools/image-snapshotter/src/validate-assets-cli.ts
new file mode 100644
index 000000000..690206002
--- /dev/null
+++ b/tools/image-snapshotter/src/validate-assets-cli.ts
@@ -0,0 +1,124 @@
+#!/usr/bin/env node
+/**
+ * Stage-2 snapshot validator: scan envelope JSONs for `data.image` refs
+ * and verify every referenced PNG exists on disk.
+ *
+ * Exits non-zero if any envelope references an asset that's missing — a
+ * common symptom of a half-captured run (capture started, was interrupted,
+ * envelope was written without the asset).
+ *
+ * Usage (from a plugin tree):
+ *   SNAPSHOTTER_PLUGIN_ROOT=/work image-snapshotter-validate-assets
+ *
+ * Or directly:
+ *   node dist/validate-assets-cli.js <snapshots-dir>
+ *
+ * Both `<envelope>.json` -> referenced `assets/<sha>.png` and the reverse
+ * (orphan assets) are reported, but only missing-asset failures cause a
+ * non-zero exit. Orphan detection is handled by `prune.ts` and stays
+ * advisory here.
+ */
+import { existsSync, readFileSync, readdirSync, statSync } from 'node:fs';
+import { join, resolve } from 'node:path';
+
+interface Envelope {
+  file?: string;
+  objects?: Record<string, { type?: string; data?: { image?: string } }>;
+}
+
+interface MissingRef {
+  envelopePath: string;
+  objectName: string;
+  imageRel: string;
+}
+
+export interface ValidateResult {
+  missing: MissingRef[];
+  envelopesScanned: number;
+  imageRefsScanned: number;
+}
+
+export function validateSnapshotAssets(snapshotsDir: string): ValidateResult {
+  const missing: MissingRef[] = [];
+  let envelopesScanned = 0;
+  let imageRefsScanned = 0;
+
+  if (!existsSync(snapshotsDir) || !statSync(snapshotsDir).isDirectory()) {
+    return { missing, envelopesScanned, imageRefsScanned };
+  }
+
+  const entries = readdirSync(snapshotsDir);
+  for (const name of entries) {
+    if (!name.endsWith('.json')) continue;
+    const path = join(snapshotsDir, name);
+    envelopesScanned += 1;
+    let envelope: Envelope;
+    try {
+      envelope = JSON.parse(readFileSync(path, 'utf8')) as Envelope;
+    } catch {
+      // Malformed JSON is a hard error — bubble up via a synthetic miss.
+      missing.push({
+        envelopePath: path,
+        objectName: '<parse error>',
+        imageRel: '<n/a>',
+      });
+      continue;
+    }
+    const objects = envelope.objects ?? {};
+    for (const [objectName, entry] of Object.entries(objects)) {
+      const imageRel = entry?.data?.image;
+      if (typeof imageRel !== 'string') continue; // not a Pass-2 entry
+      imageRefsScanned += 1;
+      const assetPath = join(snapshotsDir, imageRel);
+      if (!existsSync(assetPath)) {
+        missing.push({ envelopePath: path, objectName, imageRel });
+      }
+    }
+  }
+  return { missing, envelopesScanned, imageRefsScanned };
+}
+
+function pluginRoot(): string {
+  const fromEnv = process.env.SNAPSHOTTER_PLUGIN_ROOT;
+  if (fromEnv) return resolve(fromEnv);
+  process.stderr.write(
+    'image-snapshotter-validate-assets: SNAPSHOTTER_PLUGIN_ROOT or a snapshots dir argument is required\n',
+  );
+  process.exit(2);
+}
+
+function main(): number {
+  const arg = process.argv[2];
+  const snapshotsDir = arg
+    ? resolve(arg)
+    : join(pluginRoot(), 'docs', 'snapshots');
+
+  const { missing, envelopesScanned, imageRefsScanned } =
+    validateSnapshotAssets(snapshotsDir);
+
+  process.stdout.write(
+    `validated ${envelopesScanned} envelope(s); ` +
+      `${imageRefsScanned} image reference(s) checked; ` +
+      `${missing.length} missing.\n`,
+  );
+
+  if (missing.length === 0) return 0;
+
+  process.stderr.write(`\nMissing assets:\n`);
+  for (const m of missing) {
+    process.stderr.write(
+      `  ${m.envelopePath} :: ${m.objectName} -> ${m.imageRel} (not on disk)\n`,
+    );
+  }
+  process.stderr.write(
+    `\nRe-run \`image-snapshotter --update\` to recapture the missing assets.\n`,
+  );
+  return 1;
+}
+
+const isMain =
+  import.meta.url === `file://${process.argv[1]}` ||
+  process.argv[1]?.endsWith('validate-assets-cli.js');
+if (isMain) {
+  process.exit(main());
+}
diff --git a/tools/image-snapshotter/tests/docs-snapshots.spec.ts b/tools/image-snapshotter/tests/docs-snapshots.spec.ts
new file mode 100644
index 000000000..25bb350c8
--- /dev/null
+++ b/tools/image-snapshotter/tests/docs-snapshots.spec.ts
@@ -0,0 +1,360 @@
+/**
+ * Docs snapshot capture spec — Pass 2.
+ *
+ * For each docs page, opens the IDE once, then iterates every block's
+ * `order=` names, opens the matching panel, waits for the target widget to
+ * settle, screenshots, and merges the resulting PNG path + dims into the
+ * matching `<code_md5>.json` envelope.
+ *
+ * The widget CSS selector and the widget-type string stamped into envelopes
+ * come from `SNAPSHOTTER_TARGET_SELECTOR` and `SNAPSHOTTER_WIDGET_TYPE` so
+ * this spec can be reused across plugins.
+ *
+ * If a panel for a given name does not produce a matching element (e.g. the
+ * variable is a table), the name is silently skipped — salmon Pass 1 will
+ * serialize tables on its own pass and the envelope merge is additive.
+ */
+import { createHash } from 'node:crypto';
+import { existsSync, mkdirSync, readFileSync, writeFileSync } from 'node:fs';
+import { dirname, join, resolve } from 'node:path';
+import { fileURLToPath } from 'node:url';
+import { test, expect, type Page, type Locator } from '@playwright/test';
+
+import { walkDocs, type Block } from '../src/extract.js';
+import { readOrInit, writeAtomic } from '../src/merge.js';
+
+function requireEnv(name: string): string {
+  const v = process.env[name];
+  if (!v) throw new Error(`${name} is required`);
+  return v;
+}
+
+const WIDGET_TYPE = requireEnv('SNAPSHOTTER_WIDGET_TYPE');
+const TARGET_SELECTOR = requireEnv('SNAPSHOTTER_TARGET_SELECTOR');
+
+// Docs screenshot dimensions — 860px wide at 3:2 aspect ratio. The chart
+// container is force-sized before each capture so every PNG in the docs
+// renders at the same intrinsic size regardless of panel layout.
+const SCREENSHOT_WIDTH = 860;
+const SCREENSHOT_HEIGHT = 573;
+
+// Resolve plugin paths via SNAPSHOTTER_PLUGIN_ROOT (required). The compose
+// pipeline binds the plugin's docs/ at /work/docs and exports
+// SNAPSHOTTER_PLUGIN_ROOT=/work; local-dev invocations should point at the
+// plugin checkout root.
+const PLUGIN_ROOT = requireEnv('SNAPSHOTTER_PLUGIN_ROOT');
+const DOCS_DIR = join(PLUGIN_ROOT, 'docs');
+const SNAPSHOTS_DIR = join(DOCS_DIR, 'snapshots');
+const ASSETS_DIR = join(SNAPSHOTS_DIR, 'assets');
+
+// Optional prefix map written by `image-snapshotter-fixture-gen` next to the generated
+// app.d. When present (the docker pipeline), the spec mangles each panel
+// name with its block's 8-char md5 prefix so colliding names across pages
+// resolve unambiguously. When absent (local-dev / hand-loaded server),
+// names are used raw exactly as the user typed them in the docs.
+const PREFIX_MAP_PATH = process.env.SNAPSHOTTER_PREFIX_MAP ?? '';
+// When SNAPSHOTTER_FORCE is set to anything truthy, ignore the
+// "envelope-entry + asset both present" cache and recapture every block.
+// Useful when the plugin's JS/Python changed but the doc code block (and
+// therefore its md5 envelope key) did not, so the cache would otherwise
+// skip recapture and ship a stale PNG.
+const FORCE = (process.env.SNAPSHOTTER_FORCE ?? '').trim() !== '' &&
+  process.env.SNAPSHOTTER_FORCE !== '0' &&
+  process.env.SNAPSHOTTER_FORCE?.toLowerCase() !== 'false';
+const prefixMap: Record<string, string> = (() => {
+  if (!PREFIX_MAP_PATH) return {};
+  try {
+    if (!existsSync(PREFIX_MAP_PATH)) return {};
+    return JSON.parse(readFileSync(PREFIX_MAP_PATH, 'utf8')) as Record<
+      string,
+      string
+    >;
+  } catch {
+    return {};
+  }
+})();
+
+/**
+ * Translate a docs-author-visible variable name into the global symbol
+ * actually defined in the server. With a prefix map loaded (docker run),
+ * each block's exports are namespaced as `<md5_first8>_<name>`. Without
+ * a map (local dev), the name is returned unchanged.
+ */
+function mangle(md5: string, name: string): string {
+  const prefix = prefixMap[md5];
+  return prefix ? `${prefix}_${name}` : name;
+}
+
+// --------------------------------------------------------------------------
+// Helpers — copied from tests/utils.ts (the canonical helpers live one
+// level up out of reach of this tool's tsconfig). Keep behavior identical.
+// --------------------------------------------------------------------------
+
+async function gotoPage(page: Page, url: string): Promise<void> {
+  await page.goto(url);
+  await expect(page.getByRole('progressbar', { name: 'Loading...', exact: true })).toHaveCount(0);
+}
+
+async function waitForLoad(page: Page): Promise<void> {
+  await expect(page.locator('.loading-spinner')).toHaveCount(0);
+}
+
+async function openPanel(page: Page, name: string): Promise<void> {
+  const appPanels = page.getByRole('button', { name: 'Panels', exact: true });
+  await expect(appPanels).toBeEnabled();
+  const before = await page.locator('.dh-panel').count();
+  await appPanels.click();
+  const search = page.getByRole('searchbox', { name: 'Find Table, Plot or Widget', exact: true });
+  await search.fill(name);
+  const target = page.getByRole('button', { name, exact: true });
+  await expect(target).toBeEnabled();
+  await target.click();
+  await page.mouse.move(0, 0);
+  await expect(page.locator('.dh-panel')).toHaveCount(before + 1);
+  await waitForLoad(page);
+}
+
+/**
+ * Wait until two consecutive RAFs report the same bounding box for `loc`.
+ * Mirrors the stability pattern Playwright's toHaveScreenshot uses
+ * internally, applied here so we can take a raw .screenshot() and hash it
+ * deterministically.
+ */
+/**
+ * If the target element opts in via ``data-snapshot-ready`` (initially
+ * ``"false"``), block until the plugin flips it to ``"true"``. This lets
+ * the chart say "my initial data has flowed through and I'm done
+ * resampling" instead of us guessing via fixed timeouts or just-the-box.
+ *
+ * Plugins that don't set the attribute (e.g. plotly-express or any chart
+ * type that renders synchronously) are still supported — we treat the
+ * absence of the attribute as "no opt-in, don't wait".
+ */
+async function waitForSnapshotReady(
+  loc: Locator,
+  timeoutMs = 30_000,
+): Promise<void> {
+  const hasAttr = await loc.evaluate(
+    el => (el as HTMLElement).hasAttribute('data-snapshot-ready'),
+  );
+  if (!hasAttr) return;
+  try {
+    await loc
+      .page()
+      .waitForFunction(
+        el => el?.getAttribute('data-snapshot-ready') === 'true',
+        await loc.elementHandle(),
+        { timeout: timeoutMs },
+      );
+  } catch {
+    // Best-effort — fall through and screenshot what we have. The chart
+    // may legitimately never become "ready" (e.g. an empty source table).
+    // eslint-disable-next-line no-console
+    console.log(
+      '[snapshotter] data-snapshot-ready did not flip true within',
+      timeoutMs,
+      'ms — capturing anyway',
+    );
+  }
+}
+
+async function waitForStableBox(loc: Locator, attempts = 30): Promise<void> {
+  let prev: { x: number; y: number; w: number; h: number } | null = null;
+  for (let i = 0; i < attempts; i += 1) {
+    const box = await loc.boundingBox();
+    if (box && prev && box.x === prev.x && box.y === prev.y && box.width === prev.w && box.height === prev.h) {
+      // Yield two RAFs and re-check once more to be safe.
+      await loc.page().evaluate(
+        () =>
+          new Promise<void>(r => requestAnimationFrame(() => requestAnimationFrame(() => r())))
+      );
+      const again = await loc.boundingBox();
+      if (
+        again &&
+        again.x === prev.x &&
+        again.y === prev.y &&
+        again.width === prev.w &&
+        again.height === prev.h
+      ) {
+        return;
+      }
+    }
+    if (box) prev = { x: box.x, y: box.y, w: box.width, h: box.height };
+    await loc.page().evaluate(
+      () => new Promise<void>(r => requestAnimationFrame(() => requestAnimationFrame(() => r())))
+    );
+  }
+}
+
+async function closeLastPanel(page: Page): Promise<void> {
+  // Click the close button on the most recently-active panel tab.
+  const closeBtn = page.locator('.lm_tab.lm_active .lm_close_tab').last();
+  const count = await closeBtn.count();
+  if (count === 0) return;
+  try {
+    await closeBtn.click({ timeout: 2000 });
+  } catch {
+    // best-effort teardown
+  }
+}
+
+function sha256(buf: Buffer): string {
+  return createHash('sha256').update(buf).digest('hex');
+}
+
+// --------------------------------------------------------------------------
+// Capture pass
+// --------------------------------------------------------------------------
+
+interface PageGroup {
+  page: string;
+  blocks: Block[];
+}
+
+function groupByPage(blocks: Block[]): PageGroup[] {
+  const m = new Map<string, Block[]>();
+  for (const b of blocks) {
+    if (b.skip) continue;
+    if (b.order.length === 0) continue;
+    const list = m.get(b.page) ?? [];
+    list.push(b);
+    m.set(b.page, list);
+  }
+  return Array.from(m.entries()).map(([page, blocks]) => ({ page, blocks }));
+}
+
+const allBlocks = existsSync(DOCS_DIR) ? walkDocs(DOCS_DIR) : [];
+const pageGroups = groupByPage(allBlocks);
+
+test.describe.configure({ mode: 'serial' });
+
+if (pageGroups.length === 0) {
+  // Empty docs dir — emit a placeholder so the spec runner has *something*.
+  test('docs snapshot capture (no pages with capturable blocks)', () => {
+    test.skip(true, 'No docs pages with `order=` blocks were found under docs/.');
+  });
+}
+
+for (const group of pageGroups) {
+  test(`capture ${group.page}`, async ({ page }) => {
+    test.setTimeout(5 * 60 * 1000);
+    await gotoPage(page, '');
+
+    mkdirSync(ASSETS_DIR, { recursive: true });
+
+    // Counters so the entrypoint summary shows what actually happened.
+    let captured = 0;
+    let skippedExisting = 0;
+    let skippedNoChart = 0;
+
+    for (const block of group.blocks) {
+      const envelopePath = join(SNAPSHOTS_DIR, `${block.md5}.json`);
+      const envelope = readOrInit(envelopePath, group.page);
+      let dirty = false;
+
+      for (const name of block.order) {
+        // Skip recapture only when the envelope entry AND the asset it
+        // references are both present. A bare envelope hit is not enough —
+        // assets/<sha>.png may have been deleted (git clean, dirty checkout,
+        // manual cleanup) while the envelope still points at it, and silently
+        // skipping would leave dangling image references in the docs build.
+        const existing = envelope.objects[name];
+        if (existing) {
+          const imageRel = (existing as { data?: { image?: string } })?.data?.image;
+          if (imageRel === undefined) {
+            // Salmon-authored entry (Table or any other non-image type).
+            // Pass 2 must never touch entries it doesn't own — deleting them
+            // would only succeed in destroying salmon's work without anything
+            // to put back (the panel hosts the table, not a chart).
+            skippedExisting += 1;
+            continue;
+          }
+          if (!FORCE && existsSync(join(SNAPSHOTS_DIR, imageRel))) {
+            // Pass-2 entry whose PNG still exists on disk — nothing to do.
+            // FORCE bypasses this cache so plugin-code changes propagate
+            // even when the doc block (envelope key) is unchanged.
+            skippedExisting += 1;
+            continue;
+          }
+          // Pass-2 entry whose asset went missing (git clean, etc.). Drop
+          // the dangling entry and fall through to recapture.
+          delete envelope.objects[name];
+          dirty = true;
+        }
+
+        // Use the mangled global symbol when opening the panel so reused
+        // names like `primary` / `stocks` don't collide across pages. The
+        // envelope key (below) keeps the original docs name as the
+        // user-facing identifier.
+        const panelName = mangle(block.md5, name);
+        await openPanel(page, panelName);
+        const chart = page.locator(TARGET_SELECTOR).last();
+        // Allow up to 5s for a chart container to materialize in the new panel.
+        try {
+          await chart.waitFor({ state: 'visible', timeout: 5000 });
+        } catch {
+          // Not a chart panel (table / something else, OR the chart simply
+          // never rendered). Salmon will cover table cases. Log a hint so the
+          // entrypoint summary makes silent skips visible.
+          // eslint-disable-next-line no-console
+          console.log(
+            `[snapshotter] no chart for "${name}" (panel="${panelName}", selector="${TARGET_SELECTOR}") — skipping`,
+          );
+          skippedNoChart += 1;
+          await closeLastPanel(page);
+          continue;
+        }
+        await waitForStableBox(chart);
+
+        // Force a uniform render size before capture so every docs PNG has
+        // the same intrinsic dimensions. LWC's autoSize observer refits
+        // the canvas to the new container box; waitForStableBox below
+        // blocks until that resize has settled.
+        await chart.evaluate(
+          (el, dims) => {
+            const e = el as HTMLElement;
+            e.style.width = `${dims.w}px`;
+            e.style.height = `${dims.h}px`;
+            e.style.flex = 'none';
+          },
+          { w: SCREENSHOT_WIDTH, h: SCREENSHOT_HEIGHT }
+        );
+        await waitForStableBox(chart);
+        // After the container has settled at its capture dimensions, wait
+        // for the chart to signal its data is fully flowed through. This
+        // catches charts whose data arrives asynchronously after the box
+        // is already stable — most notably `by`-partitioned charts that
+        // discover keys and subscribe per-key after panel mount.
+        await waitForSnapshotReady(chart);
+
+        const buf = await chart.screenshot();
+        const sha = sha256(buf);
+        const assetRel = `assets/${sha}.png`;
+        const assetAbs = join(SNAPSHOTS_DIR, assetRel);
+        if (!existsSync(assetAbs)) {
+          writeFileSync(assetAbs, buf);
+        }
+        const box = await chart.boundingBox();
+        envelope.objects[name] = {
+          type: WIDGET_TYPE,
+          data: {
+            image: assetRel,
+            width: Math.round(box?.width ?? 0),
+            height: Math.round(box?.height ?? 0),
+            alt: name,
+          },
+        };
+        captured += 1;
+        dirty = true;
+        await closeLastPanel(page);
+      }
+
+      if (dirty) writeAtomic(envelopePath, envelope);
+    }
+
+    // eslint-disable-next-line no-console
+    console.log(
+      `[snapshotter] ${group.page}: captured=${captured}, skipped(existing)=${skippedExisting}, skipped(no chart)=${skippedNoChart}`,
+    );
+  });
+}
diff --git a/tools/image-snapshotter/tests/extract.test.ts b/tools/image-snapshotter/tests/extract.test.ts
new file mode 100644
index 000000000..023f0148e
--- /dev/null
+++ b/tools/image-snapshotter/tests/extract.test.ts
@@ -0,0 +1,118 @@
+import { describe, it, expect } from 'vitest';
+import { mkdtempSync, writeFileSync, mkdirSync } from 'node:fs';
+import { tmpdir } from 'node:os';
+import { join } from 'node:path';
+
+import { codeMd5, extractBlocks, walkDocs } from '../src/extract.js';
+
+describe('codeMd5', () => {
+  it('is stable for a known input', () => {
+    // md5("x = 1-python") computed once and pinned. This MUST NOT change
+    // without coordinating with salmon (see extract.ts contract block).
+    expect(codeMd5('x = 1')).toBe('de0ffed875c44f394a3ab83febe157a1');
+  });
+
+  it('ignores surrounding whitespace', () => {
+    expect(codeMd5('  x = 1\n')).toBe(codeMd5('x = 1'));
+  });
+});
+
+describe('extractBlocks', () => {
+  it('parses an order=a,b block', () => {
+    const md = [
+      'Some prose.',
+      '',
+      '```python order=foo,bar',
+      'foo = tvl.line(t, time="t", value="v")',
+      'bar = tvl.candlestick(t, time="t", open="o", high="h", low="l", close="c")',
+      '```',
+      '',
+      'Trailing prose.',
+    ].join('\n');
+
+    const blocks = extractBlocks('demo.md', md);
+    expect(blocks).toHaveLength(1);
+    const b = blocks[0];
+    expect(b.page).toBe('demo.md');
+    expect(b.order).toEqual(['foo', 'bar']);
+    expect(b.skip).toBe(false);
+    expect(b.md5).toBe(codeMd5(b.code));
+  });
+
+  it('skips a block whose first line is `# no-snapshot`', () => {
+    const md = [
+      '```python order=helper',
+      '# no-snapshot',
+      'helper = tvl.line(t, time="t", value="v")',
+      '```',
+    ].join('\n');
+    const blocks = extractBlocks('demo.md', md);
+    expect(blocks).toHaveLength(1);
+    expect(blocks[0].skip).toBe(true);
+  });
+
+  it('honors a `skip-test` flag in the info string', () => {
+    const md = ['```python skip-test', 'x = 1', '```'].join('\n');
+    const blocks = extractBlocks('demo.md', md);
+    expect(blocks).toHaveLength(1);
+    expect(blocks[0].skip).toBe(true);
+  });
+
+  it('ignores non-python fences', () => {
+    const md = ['```js', 'console.log("hi");', '```'].join('\n');
+    expect(extractBlocks('demo.md', md)).toHaveLength(0);
+  });
+
+  it('finds fences indented under a list item', () => {
+    // Regression test: the prior regex-based parser required column-0
+    // backticks and silently skipped fences nested in list items, which
+    // caused README.md's quickstart block to be invisible to Pass 2.
+    const md = [
+      '1. Install with pip:',
+      '',
+      '   ```bash',
+      '   pip install thing',
+      '   ```',
+      '',
+      '2. Then run the example:',
+      '',
+      '   ```python order=chart',
+      '   chart = tvl.line(t, timestamp="t", value="v")',
+      '   ```',
+    ].join('\n');
+    const blocks = extractBlocks('readme.md', md);
+    expect(blocks).toHaveLength(1);
+    expect(blocks[0].order).toEqual(['chart']);
+    expect(blocks[0].code).toBe('chart = tvl.line(t, timestamp="t", value="v")');
+  });
+
+  it('produces stable md5 hashes for a column-0 fence (salmon-contract guard)', () => {
+    // The exact code body must produce the same hash that salmon's Pass 1
+    // computes on the same block. Drift here = misaligned envelope files.
+    const md = ['```python order=foo', 'foo = 1', '```'].join('\n');
+    const [block] = extractBlocks('demo.md', md);
+    expect(block.code).toBe('foo = 1');
+    expect(block.md5).toBe(codeMd5('foo = 1'));
+  });
+});
+
+describe('walkDocs', () => {
+  it('discovers blocks across files', () => {
+    const dir = mkdtempSync(join(tmpdir(), 'tvl-snap-test-'));
+    mkdirSync(join(dir, 'sub'), { recursive: true });
+    writeFileSync(
+      join(dir, 'a.md'),
+      '```python order=alpha\nalpha = tvl.line(t, time="t", value="v")\n```\n'
+    );
+    writeFileSync(
+      join(dir, 'sub', 'b.md'),
+      '```python order=beta\n# no-snapshot\nbeta = "skipme"\n```\n```python order=gamma\ngamma = tvl.area(t, time="t", value="v")\n```\n'
+    );
+    const blocks = walkDocs(dir);
+    const byName = new Map(blocks.map(b => [b.order[0], b]));
+    expect(byName.get('alpha')?.skip).toBe(false);
+    expect(byName.get('beta')?.skip).toBe(true);
+    expect(byName.get('gamma')?.skip).toBe(false);
+    expect(blocks).toHaveLength(3);
+  });
+});
diff --git a/tools/image-snapshotter/tests/fixtures.test.ts b/tools/image-snapshotter/tests/fixtures.test.ts
new file mode 100644
index 000000000..229395165
--- /dev/null
+++ b/tools/image-snapshotter/tests/fixtures.test.ts
@@ -0,0 +1,144 @@
+import { describe, it, expect } from 'vitest';
+import { mkdtempSync, readFileSync, readdirSync, existsSync } from 'node:fs';
+import { tmpdir } from 'node:os';
+import { join } from 'node:path';
+
+import { codeMd5, type Block } from '../src/extract.js';
+import {
+  blockPrefix,
+  generateAppdFixtures,
+  renderBlockFile,
+  renderManifest,
+} from '../src/fixtures.js';
+
+function block(page: string, code: string, order: string[], skip = false): Block {
+  return { page, code, order, skip, md5: codeMd5(code) };
+}
+
+describe('blockPrefix', () => {
+  // Regression: md5 hashes routinely start with a digit, but Python
+  // identifiers can't. The prefix MUST begin with a letter or every
+  // generated fixture is a SyntaxError, which in turn crashes the DH
+  // server during app.d evaluation.
+  it('always starts with a letter', () => {
+    for (const md5 of [
+      '00343a16f0d2ab66ebe4b87f531d2343',
+      '9b7f78980cffde4bb7542b637b1f76ec',
+      'f000000000000000000000000000000a',
+    ]) {
+      const p = blockPrefix(md5);
+      expect(p).toMatch(/^[A-Za-z][A-Za-z0-9_]*$/);
+      // And it must be deterministic — same md5 → same prefix.
+      expect(blockPrefix(md5)).toBe(p);
+    }
+  });
+});
+
+describe('renderBlockFile', () => {
+  it('wraps code in an isolated function and hoists order= names with md5 prefix', () => {
+    const b = block('candlestick.md', 'primary = 42\nignored = 99', ['primary']);
+    const out = renderBlockFile(b, b.page);
+    const p = blockPrefix(b.md5); // exported-global prefix (e.g. b1234abcd)
+    const md5_8 = b.md5.slice(0, 8); // private function-name suffix
+
+    // Header includes source page + md5 + order list.
+    expect(out).toContain(`# Source: docs/candlestick.md`);
+    expect(out).toContain(`# Block md5: ${b.md5}`);
+    expect(out).toContain(`# order=primary`);
+    // Function carrying isolated locals. Private name uses the raw 8-hex
+    // since the leading underscore already makes it a valid identifier.
+    expect(out).toContain(`def _block_${md5_8}():`);
+    expect(out).toContain(`    primary = 42`);
+    expect(out).toContain(`    ignored = 99`);
+    expect(out).toContain(`    return locals()`);
+    // Hoist line uses the mangled GLOBAL name (must start with a letter).
+    expect(out).toContain(`${p}_primary = _block_${md5_8}_locals["primary"]`);
+    // Only `order=` names are hoisted; `ignored` is NOT.
+    expect(out).not.toMatch(new RegExp(`^${p}_ignored\\s*=`, 'm'));
+  });
+
+  it('only hoists declared order= names', () => {
+    const b = block('demo.md', 'a = 1\nb = 2\nc = 3', ['a', 'c']);
+    const out = renderBlockFile(b, b.page);
+    const p = blockPrefix(b.md5);
+    const md5_8 = b.md5.slice(0, 8);
+    expect(out).toContain(`${p}_a = _block_${md5_8}_locals["a"]`);
+    expect(out).toContain(`${p}_c = _block_${md5_8}_locals["c"]`);
+    expect(out).not.toContain(`${p}_b =`);
+  });
+});
+
+describe('renderManifest', () => {
+  it('emits one file_N= entry per block file', () => {
+    const m = renderManifest(['block_aaa.py', 'block_bbb.py']);
+    expect(m).toContain('type=script');
+    expect(m).toContain('scriptType=python');
+    expect(m).toContain('enabled=true');
+    expect(m).toContain('id=docs.examples');
+    expect(m).toContain('name=Docs Examples');
+    expect(m).toContain('file_0=block_aaa.py');
+    expect(m).toContain('file_1=block_bbb.py');
+  });
+});
+
+describe('generateAppdFixtures', () => {
+  it('writes one block_<md5>.py per non-skip block, plus tests.app, plus a prefix map', () => {
+    const dir = mkdtempSync(join(tmpdir(), 'tvl-fix-'));
+
+    // Two blocks on different pages reusing the SAME variable name `primary`.
+    const b1 = block('a.md', 'primary = 1', ['primary']);
+    const b2 = block('b.md', 'primary = 2', ['primary']);
+    const bSkip = block('c.md', 'should_not_exist = 3', ['should_not_exist'], true);
+
+    const res = generateAppdFixtures([b1, b2, bSkip], dir);
+
+    expect(res.blockCount).toBe(2);
+    expect(res.prefixMap.size).toBe(2);
+    expect(res.prefixMap.get(b1.md5)).toBe(blockPrefix(b1.md5));
+    expect(res.prefixMap.get(b2.md5)).toBe(blockPrefix(b2.md5));
+
+    // Files on disk.
+    const files = readdirSync(dir).sort();
+    expect(files).toContain(`block_${b1.md5}.py`);
+    expect(files).toContain(`block_${b2.md5}.py`);
+    expect(files).toContain('tests.app');
+    // Skipped block has no file.
+    expect(files.find(f => f.includes(bSkip.md5))).toBeUndefined();
+
+    // Each file should hoist its mangled symbol.
+    const f1 = readFileSync(join(dir, `block_${b1.md5}.py`), 'utf8');
+    const f2 = readFileSync(join(dir, `block_${b2.md5}.py`), 'utf8');
+    expect(f1).toContain(`${blockPrefix(b1.md5)}_primary`);
+    expect(f2).toContain(`${blockPrefix(b2.md5)}_primary`);
+    // The two prefixes differ so the duplicate `primary` doesn't collide.
+    expect(blockPrefix(b1.md5)).not.toBe(blockPrefix(b2.md5));
+
+    // Manifest lists both blocks.
+    const manifest = readFileSync(res.manifestPath, 'utf8');
+    expect(manifest).toContain(`block_${b1.md5}.py`);
+    expect(manifest).toContain(`block_${b2.md5}.py`);
+  });
+
+  it('cleans up stale block_*.py from previous runs', () => {
+    const dir = mkdtempSync(join(tmpdir(), 'tvl-fix-stale-'));
+    const oldBlock = block('old.md', 'gone = 1', ['gone']);
+    generateAppdFixtures([oldBlock], dir);
+    expect(existsSync(join(dir, `block_${oldBlock.md5}.py`))).toBe(true);
+
+    // Second run: different blocks. Old file should be removed.
+    const newBlock = block('new.md', 'kept = 1', ['kept']);
+    generateAppdFixtures([newBlock], dir);
+    expect(existsSync(join(dir, `block_${oldBlock.md5}.py`))).toBe(false);
+    expect(existsSync(join(dir, `block_${newBlock.md5}.py`))).toBe(true);
+  });
+
+  it('dedupes blocks with identical md5 (same code reused verbatim)', () => {
+    const dir = mkdtempSync(join(tmpdir(), 'tvl-fix-dup-'));
+    const b1 = block('a.md', 'shared = 1', ['shared']);
+    const b2 = block('b.md', 'shared = 1', ['shared']); // identical code → same md5
+    expect(b1.md5).toBe(b2.md5);
+    const res = generateAppdFixtures([b1, b2], dir);
+    expect(res.blockCount).toBe(1);
+    expect(res.prefixMap.size).toBe(1);
+  });
+});
diff --git a/tools/image-snapshotter/tsconfig.json b/tools/image-snapshotter/tsconfig.json
new file mode 100644
index 000000000..6e3e3d1b2
--- /dev/null
+++ b/tools/image-snapshotter/tsconfig.json
@@ -0,0 +1,19 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "module": "NodeNext",
+    "moduleResolution": "NodeNext",
+    "lib": ["ES2022"],
+    "outDir": "dist",
+    "rootDir": "src",
+    "strict": true,
+    "esModuleInterop": true,
+    "skipLibCheck": true,
+    "forceConsistentCasingInFileNames": true,
+    "declaration": true,
+    "sourceMap": true,
+    "resolveJsonModule": true
+  },
+  "include": ["src/**/*.ts"],
+  "exclude": ["dist", "node_modules", "tests"]
+}
diff --git a/tools/image-snapshotter/vitest.config.ts b/tools/image-snapshotter/vitest.config.ts
new file mode 100644
index 000000000..0ee821fda
--- /dev/null
+++ b/tools/image-snapshotter/vitest.config.ts
@@ -0,0 +1,15 @@
+import { defineConfig } from 'vitest/config';
+import { fileURLToPath } from 'node:url';
+import { dirname } from 'node:path';
+
+const here = dirname(fileURLToPath(import.meta.url));
+
+export default defineConfig({
+  // Anchor to this directory so vitest does not climb the parent tree and
+  // try to load the repo-root vitest.config.mts (which lives outside our
+  // node_modules and can't resolve `vitest`).
+  root: here,
+  test: {
+    include: ['tests/**/*.test.ts'],
+  },
+});
diff --git a/tools/run_docker.sh b/tools/run_docker.sh
index d44eb0eb3..edd630774 100755
--- a/tools/run_docker.sh
+++ b/tools/run_docker.sh
@@ -3,6 +3,13 @@
 COMPOSE_FILE=$1
 shift
 
+# Pass host UID/GID into compose so the docs error-reporter service can
+# chown the docs/snapshots dirs back to the calling user after the
+# (root-running) salmon snapshotter / image-snapshotter have written into
+# them. Files would otherwise be root-owned and uneditable on the host.
+export SNAPSHOT_UID="${SNAPSHOT_UID:-$(id -u)}"
+export SNAPSHOT_GID="${SNAPSHOT_GID:-$(id -g)}"
+
 # Start the containers
 if [[ "${CI}" == "1" || "${CI}" == "true" ]]; then
   # In CI, keep the container in case we need to dump logs in another