What problem does it solve? Python codebases often drift into inconsistent formatting, missing type annotations, weak test coverage, and ad-hoc error handling, making them hard to maintain and review. This Skill provides a complete, opinionated set of coding standards so teams write uniform, typed, tested, production-ready Python code. ## Core Features & Use Cases - Style and Type Standards: PEP 8 formatting with Black and isort, type hint patterns including Protocols, Generics, TypedDict, and Literal, plus mypy and Ruff configuration. - Testing and Quality Tooling: pytest best practices with fixtures, parametrization, mocking, and async tests, plus ready-to-use scripts for project scaffolding and running the full quality gate (Black, isort, Ruff, mypy, Bandit, coverage). - Production Patterns: FastAPI service examples, SQLAlchemy models, exception hierarchies, Pydantic validation, secrets management, and async patterns. - Use Case: When starting a new FastAPI backend, run the setup script to scaffold a src-layout project with pyproject.toml, pre-commit hooks, and tests, then apply the standards while writing endpoints so every commit passes lint, type check, and 80% coverage. ## Quick Start Ask the AI to review your Python module against these coding standards and fix any PEP 8, typing, or testing violations it finds.
