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Default Python stack for Lambda: uv + Astral tools, typed code, schemas, and Hypothesis.

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SKILL.md

name python
description Default Python stack for Lambda: uv + Astral tools, typed code, schemas, and Hypothesis.

Python Workflow

Use this skill when working on Python projects or adding Python support.

Tooling baseline

  • Use uv for environments, dependency management, and running commands.
  • Prefer Astral tooling for quality gates: ruff for lint/format and ty for type checking.
  • Favor strict typing everywhere; avoid Any unless the boundary truly requires it.

Typing and schemas

  • Type every function signature (params + return) and keep types narrow.
  • Use Pydantic models for inputs, outputs, and configuration schemas.
  • Prefer typed collections and typing_extensions for newer typing features.

Testing

  • Write tests with pytest and property tests with hypothesis when behavior is stateful or rule-based.
  • Add coverage checks (e.g., pytest-cov) and keep coverage green for new code paths.

Packaging

  • Structure the code as a releasable PyPI package.
  • Use a pyproject.toml with build metadata, versioning, and a src/ layout.
  • Ensure imports and entrypoints work when installed from a wheel.

Quality gates

  • For pre-commit hooks, run formatting last so lint fixes land before formatting.
  • Keep linting, type checking, and tests passing before closing work.