| 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
- Run formatting last.
- Keep linting, type checking, and tests passing before closing work.