python-best-practices

To check Python code for best practices and security, you can use this Skill to automate comprehensive code reviews, validating type hints, PEP 8 compliance, testing, and security using bandit. It analyzes your codebase to ensure adherence to project standards and identifies common security flaws.

Yes, this tool enforces code quality checks for FastAPI and Django projects. It includes specific framework integration checks alongside standard Python validation to ensure your web applications maintain high test coverage and adhere to best practices.

The best way to automate Python dependency management and linting before a merge is running this Skill. It validates dependency management using uv and performs linting with ruff, ensuring your new features meet project standards, are well-tested, and reduce technical debt.

Yes, this Skill validates type hinting and test coverage using mypy and pytest. It analyzes your Python project against these specific standards, ensuring strict type checking and verifying that your codebase maintains high test coverage.

You should use uv for package management because this Skill ensures projects utilize uv to maintain consistent environments. Integrating uv standardizes dependency management during code quality analysis, preventing environment-related bugs and technical debt.