python-best-practices

Python coding standards and best practices covering error handling, performance optimization, async patterns, SOLID design principles, documentation, data validation, and object-oriented programming. Use when writing, reviewing, or refactoring Python code, or when the user asks about Python style, design, or best practices.

Python development tooling configuration and best practices for ruff, mypy, pytest, pyscn, and uv. Use when setting up a Python project, configuring linters, formatters, type checkers, or test frameworks, or when editing pyproject.toml or tool config files.

Python test-writing best practices covering test structure, fixtures, parametrization, and mocking with pytest. Use when writing, reviewing, or refactoring tests, adding test coverage, or working in tests directories and conftest.py.