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Add guarded behavior-preserving ruff repairs
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‎.github/workflows/apply-ruff-repairs.yml‎

Lines changed: 230 additions & 0 deletions
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name: Apply guarded ruff repairs
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on:
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push:
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branches:
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- claude/inference-comparison-4vlt4q
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paths:
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- .github/workflows/apply-ruff-repairs.yml
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permissions:
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contents: write
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jobs:
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repair:
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runs-on: ubuntu-latest
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steps:
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- name: Check out branch
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uses: actions/checkout@v4
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with:
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ref: claude/inference-comparison-4vlt4q
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fetch-depth: 0
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- name: Apply exact guarded replacements
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run: |
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python - <<'PY'
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from pathlib import Path
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def replace_once(path: str, old: str, new: str) -> None:
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p = Path(path)
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text = p.read_text()
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count = text.count(old)
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if count != 1:
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raise RuntimeError(f"{path}: expected exactly one match, found {count}: {old!r}")
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p.write_text(text.replace(old, new, 1))
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replace_once(
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"src/nns/_reg_engine.py",
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"import math\nimport re\n",
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"import math\nimport re\nfrom itertools import pairwise\n",
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)
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replace_once(
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"src/nns/_reg_engine.py",
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"ord_value = max(1, int(math.floor(dep * 10 + 0.5)))",
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"ord_value = max(1, math.floor(dep * 10 + 0.5))",
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)
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replace_once(
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"src/nns/_reg_engine.py",
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"ord_value = max(1, int(math.floor(ord_value / 2)))",
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"ord_value = max(1, math.floor(ord_value / 2))",
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)
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replace_once(
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"src/nns/_reg_engine.py",
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"for a, b in zip(unique_knots[:-1], unique_knots[1:]):",
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"for a, b in pairwise(unique_knots):",
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)
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replace_once(
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"src/nns/_reg_engine.py",
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'"Variable": names + ["DENOMINATOR"],',
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'"Variable": [*names, "DENOMINATOR"],',
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)
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replace_once(
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"src/nns/_reg_engine.py",
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"k = max(1, int(math.floor((1.0 - dep) * math.sqrt(x.shape[0]))))",
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"k = max(1, math.floor((1.0 - dep) * math.sqrt(x.shape[0])))",
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)
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replace_once(
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"src/nns/_rrng.py",
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"v1 = int(math.floor(self.unif_rand() * 65536))",
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"v1 = math.floor(self.unif_rand() * 65536)",
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)
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replace_once(
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"src/nns/_rrng.py",
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"bits = int(math.ceil(math.log2(dn)))",
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"bits = math.ceil(math.log2(dn))",
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)
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replace_once(
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"src/nns/_rrng.py",
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" def sample_int(self, n: int, size: int | None = None, replace: bool = False) -> NDArray[np.int64]:\n",
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" def sample_int(\n self, n: int, size: int | None = None, replace: bool = False\n ) -> NDArray[np.int64]:\n",
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)
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replace_once(
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"src/nns/boost.py",
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"size = max(1, min(n_obs - 1, int(round(cv_fraction * n_obs))))",
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"size = max(1, min(n_obs - 1, round(cv_fraction * n_obs)))",
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)
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replace_once(
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"src/nns/boost.py",
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"k_small = max(1, int(math.floor(math.sqrt(minimum_train_size))))",
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"k_small = max(1, math.floor(math.sqrt(minimum_train_size)))",
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)
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replace_once(
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"src/nns/boost.py",
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"k_candidates = list(dict.fromkeys(list(range(1, k_small + 1)) + [minimum_train_size]))",
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"k_candidates = list(dict.fromkeys([*range(1, k_small + 1), minimum_train_size]))",
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)
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replace_once(
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"src/nns/stack.py",
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"def _scalar_integer(value: Any, name: str, minimum: int = 0, allow_null: bool = False) -> int | None:\n",
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"def _scalar_integer(\n value: Any, name: str, minimum: int = 0, allow_null: bool = False\n) -> int | None:\n",
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)
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replace_once(
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"src/nns/stack.py",
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" [class_values.index(v) + 1 for v in (dv.tolist() if response_categorical else dv.astype(np.float64).tolist())],\n",
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" [\n class_values.index(v) + 1\n for v in (\n dv.tolist()\n if response_categorical\n else dv.astype(np.float64).tolist()\n )\n ],\n",
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)
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replace_once(
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"src/nns/stack.py",
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' "Method 2 was removed because dimension reduction requires more than one original predictor.",\n',
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' "Method 2 was removed because dimension reduction requires more than "\n "one original predictor.",\n',
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)
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replace_once(
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"src/nns/stack.py",
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" return np.clip(np.asarray(code, dtype=np.float64), 1, n_classes).astype(np.int64).astype(np.float64)\n",
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" return (\n np.clip(np.asarray(code, dtype=np.float64), 1, n_classes)\n .astype(np.int64)\n .astype(np.float64)\n )\n",
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)
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replace_once(
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"src/nns/stack.py",
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"size = min(g.size - 1, max(1, int(round(holdout_size * g.size))))",
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"size = min(g.size - 1, max(1, round(holdout_size * g.size)))",
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)
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replace_once(
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"src/nns/stack.py",
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"size = max(1, min(n_obs - 1, int(round(holdout_size * n_obs))))",
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"size = max(1, min(n_obs - 1, round(holdout_size * n_obs)))",
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)
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replace_once(
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"src/nns/stack.py",
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" def coefficient_vector(design: NDArray[np.float64], response: NDArray[np.float64]) -> NDArray[np.float64]:\n",
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" def coefficient_vector(\n design: NDArray[np.float64], response: NDArray[np.float64]\n ) -> NDArray[np.float64]:\n",
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)
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replace_once(
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"src/nns/stack.py",
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"l_small = max(1, int(math.floor(math.sqrt(n_obs))))",
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"l_small = max(1, math.floor(math.sqrt(n_obs)))",
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)
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replace_once(
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"src/nns/var.py",
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" _METHOD1_GUARD_MESSAGE = (\n",
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" method1_guard_message = (\n",
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)
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replace_once(
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"src/nns/var.py",
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''' def run_var_stack(stack_obj_fn: Any, stack_objective: str) -> dict[str, Any]:
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return nns_stack(
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lagged_iv,
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lagged_dv,
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ivs_test=ivs_test,
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obj_fn=cast(Any, stack_obj_fn),
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objective=cast(Any, stack_objective),
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folds=1,
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method=(1, 2),
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order=None,
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stack=True,
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dim_red_method=cast(Any, dim_red_threshold_method),
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ts_test=ts_test,
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)
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try:
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result = run_var_stack(var_obj_fn, objective_value)
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except ValueError as error:
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if not (use_default_objective and str(error) == _METHOD1_GUARD_MESSAGE):
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raise
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result = run_var_stack(mse_obj_fn, "min")
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''',
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''' def run_var_stack(
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stack_obj_fn: Any,
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stack_objective: str,
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stack_iv: np.ndarray,
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stack_dv: np.ndarray,
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stack_test: np.ndarray,
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stack_ts_test: int,
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) -> dict[str, Any]:
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return nns_stack(
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stack_iv,
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stack_dv,
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ivs_test=stack_test,
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obj_fn=cast(Any, stack_obj_fn),
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objective=cast(Any, stack_objective),
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folds=1,
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method=(1, 2),
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order=None,
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stack=True,
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dim_red_method=cast(Any, dim_red_threshold_method),
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ts_test=stack_ts_test,
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)
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try:
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result = run_var_stack(
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var_obj_fn,
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objective_value,
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lagged_iv,
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lagged_dv,
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ivs_test,
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ts_test,
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)
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except ValueError as error:
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if not (use_default_objective and str(error) == method1_guard_message):
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raise
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result = run_var_stack(
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mse_obj_fn,
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"min",
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lagged_iv,
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lagged_dv,
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ivs_test,
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ts_test,
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)
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''',
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)
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replace_once(
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"tests/parity/test_regression.py",
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'with pytest.raises(ValueError, match="noise.reduction"):',
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'with pytest.raises(ValueError, match=r"noise\\.reduction"):',
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)
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PY
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- name: Verify ruff and commit
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run: |
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python -m pip install -q ruff
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ruff check .
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git config user.name "github-actions[bot]"
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git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
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git rm .github/workflows/apply-ruff-repairs.yml
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git add src tests
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git commit -m "Resolve remaining ruff findings without behavior changes"
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git push origin HEAD:claude/inference-comparison-4vlt4q

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