style: fix black/isort/flake8 formatting for CI

- Run black + isort on all source and test files (19 reformatted)
- Add .flake8 config (max-line-length=88, ignore E203/W503)
- All lint checks now pass: black, isort, flake8
- 66 tests pass, 81% coverage

Author: jajupmochi

.flake8

@@ -0,0 +1,3 @@
+[flake8]
+max-line-length = 88
+extend-ignore = E203, W503

liulian/data/local.py

@@ -8,7 +8,7 @@
 
 import csv
 import os
-from typing import Any, Dict, List, Tuple
+from typing import List, Tuple
 
 import numpy as np
 
@@ -85,7 +85,6 @@ def list_data_files(
     files = [
         os.path.join(directory, f)
         for f in sorted(os.listdir(directory))
-        if os.path.isfile(os.path.join(directory, f))
-        and f.lower().endswith(extensions)
+        if os.path.isfile(os.path.join(directory, f)) and f.lower().endswith(extensions)
     ]
     return files

liulian/data/manifest.py

@@ -11,7 +11,6 @@
 
 import yaml
 
-
 # Required top-level keys in a valid manifest
 _REQUIRED_KEYS: List[str] = ["name", "version", "fields", "splits"]
 
@@ -74,8 +73,6 @@ def load_manifest(path: str) -> Dict[str, Any]:
 
     errors = validate_manifest(manifest)
     if errors:
-        raise ValueError(
-            f"Invalid manifest '{path}':\n  " + "\n  ".join(errors)
-        )
+        raise ValueError(f"Invalid manifest '{path}':\n  " + "\n  ".join(errors))
 
     return manifest

liulian/data/spec.py

@@ -76,6 +76,4 @@ def to_dict(self) -> Dict[str, Any]:
         }
 
     def __repr__(self) -> str:
-        return (
-            f"TopologySpec(nodes={self.num_nodes}, edges={self.num_edges})"
-        )
+        return f"TopologySpec(nodes={self.num_nodes}, edges={self.num_edges})"

liulian/loggers/interface.py

@@ -26,7 +26,9 @@ def log_metrics(self, step: int, metrics: Dict[str, float]) -> None:
         """
 
     @abstractmethod
-    def log_artifact(self, path: str, metadata: Optional[Dict[str, Any]] = None) -> None:
+    def log_artifact(
+        self, path: str, metadata: Optional[Dict[str, Any]] = None
+    ) -> None:
         """Log an artifact file (checkpoint, config snapshot, etc.).
 
         Args:

liulian/loggers/local_logger.py

@@ -43,7 +43,9 @@ def log_metrics(self, step: int, metrics: Dict[str, float]) -> None:
         with open(self._metrics_path, "a", encoding="utf-8") as fh:
             fh.write(json.dumps(record) + "\n")
 
-    def log_artifact(self, path: str, metadata: Optional[Dict[str, Any]] = None) -> None:
+    def log_artifact(
+        self, path: str, metadata: Optional[Dict[str, Any]] = None
+    ) -> None:
         """Copy an artifact file into the run directory.
 
         Args:

liulian/optim/base.py

@@ -35,9 +35,7 @@ class BaseOptimizer(ABC):
     """
 
     @abstractmethod
-    def run(
-        self, spec: Any, search_space: Dict[str, Any]
-    ) -> OptimizationResult:
+    def run(self, spec: Any, search_space: Dict[str, Any]) -> OptimizationResult:
         """Execute a hyperparameter search.
 
         Args:

liulian/optim/ray_optimizer.py

@@ -209,15 +209,17 @@ def _run_fallback(
             # Without a real training loop we use a deterministic hash-based
             # proxy metric.  In production code the caller should supply a
             # ``trainable`` and use the Ray path instead.
-            proxy = sum(abs(hash(str(v))) % 1000 for v in combo) / max(len(combo), 1) / 1000.0
+            proxy = (
+                sum(abs(hash(str(v))) % 1000 for v in combo)
+                / max(len(combo), 1)
+                / 1000.0
+            )
             trial_metrics = {metric: proxy}
             trials_summary.append(
                 {"trial_id": i, "config": config, "metrics": trial_metrics}
             )
 
-            is_better = (
-                proxy < best_value if mode == "min" else proxy > best_value
-            )
+            is_better = proxy < best_value if mode == "min" else proxy > best_value
             if is_better:
                 best_value = proxy
                 best_config = config

liulian/runtime/experiment.py

@@ -11,8 +11,6 @@
 import os
 from typing import Any, Callable, Dict, List, Optional
 
-import yaml
-
 from liulian.data.base import BaseDataset
 from liulian.loggers.interface import LoggerInterface
 from liulian.models.base import ExecutableModel

liulian/runtime/state_machine.py

@@ -30,8 +30,8 @@ class ExecutionMode(Enum):
     """
 
     OFFLINE = "offline"
-    ONLINE = "online"          # streaming / real-time (v1+)
-    HITL = "hitl"              # human-in-the-loop (v1+)
+    ONLINE = "online"  # streaming / real-time (v1+)
+    HITL = "hitl"  # human-in-the-loop (v1+)
     AGENT_ASSIST = "agent_assist"  # LLM-assisted (v1+)