python-style

name: python-style description: Reviews anomalib Python style, typing, imports, and public API conventions

Anomalib Python Style Review

Use this skill when reviewing Python code in src/anomalib/ or tests/.

Purpose and scope

This skill covers Python style, typing, imports, exports, copyright headers, and basic code hygiene.

Core rules

• Target the repository's Python baseline.
• Follow the Ruff-configured line length of 120 characters.
• Match nearby anomalib code before suggesting stylistic rewrites.
• Prefer explicit, readable code over clever shortcuts.

Request changes when

• public APIs are missing type annotations;
• new code introduces weak typing such as unnecessary Any or untyped public **kwargs;
• imports or exports drift from nearby package patterns;
• a touched Python file is missing the expected copyright/SPDX header;
• error handling becomes less explicit or debug code is left behind.

Typing

• Public functions, methods, and constructors should have explicit type annotations.
• Prefer repository-established typing patterns such as X | None, type[...], Sequence[...], TypeVar, and Generic where they fit.
• Do not weaken types without a strong reason.
• Flag vague escape hatches such as unnecessary Any, broad untyped **kwargs, or type suppressions that hide real issues.

Imports and exports

• Keep imports grouped as standard library, third-party, then local imports.
• Prefer absolute imports inside anomalib.
• When a public symbol is added to an __init__.py, verify that __all__ stays accurate.

Copyright and license header

• Python source files should include the standard Intel copyright and SPDX header used across the repository.
• For a new file, use the current year only, for example:
  • # Copyright (C) 2026 Intel Corporation
  • # SPDX-License-Identifier: Apache-2.0
• For an existing file updated in 2026, ensure the year or year range includes 2026.
  • Example: update 2024 to 2024-2026.
  • Example: keep 2026 for a single-year file created in 2026.

Error handling and code hygiene

• Catch specific exceptions instead of broad or silent failure patterns.
• Ask for explicit exceptions and informative error messages.
• Flag debug prints, dead code, commented-out code, and magic values that should be named constants or config.
• Prefer explicit validation with raised exceptions over fragile assumptions.

Repo-grounded review anchors

• pyproject.toml defines Ruff, pydocstyle, mypy, pytest, and Commitizen expectations.

Reviewer checklist

• Check typing on public APIs.
• Check imports and exports.
• Check the copyright/SPDX header on touched Python files.
• Check for obvious code hygiene regressions.