Cargo.toml

[package]
name = "rustograd"
version = "0.1.0"
edition = "2024"
authors = ["aubrey <aubrey.shay.dyer@gmail.com>"]
description = "A from-scratch Rust reimplementation of Karpathy's micrograd: a tiny scalar-valued autograd engine with a small neural-net library on top."

# The autograd engine + nn library live in the lib crate (src/lib.rs).
# cdylib is needed for the wasm build; rlib keeps the bin/examples/tests working.
[lib]
name = "rustograd"
path = "src/lib.rs"
crate-type = ["cdylib", "rlib"]

# An interactive REPL for poking at Values and networks. `cargo run --bin repl`
[[bin]]
name = "repl"
path = "src/bin/repl.rs"

[dependencies]
# Random weight init for Neuron (parity with Python's random.uniform).
rand = "0.8"

# wasm-only: bindings + getrandom's JS shim (pinned to the installed wasm-bindgen
# CLI so generated glue matches). Native builds pull neither.
[target.'cfg(target_arch = "wasm32")'.dependencies]
wasm-bindgen = "=0.2.126"
getrandom = { version = "0.2", features = ["js"] }

# --- Suggested deps you'll likely want as you tick off the roadmap ---
# Uncomment when you reach the relevant checklist item.
#
# rustyline = "14"        # line editing / history for the REPL
# plotters  = "0.3"       # plotting decision boundaries & loss curves (matplotlib parity)
# graphviz-rust = "0.9"   # render the computation graph (graphviz/trace_graph parity)
#                         #   or just emit DOT text yourself and shell out to `dot`.

[dev-dependencies]
# approx = "0.5"          # assert_relative_eq! for gradient-check tests