python-best-practices

Enforce Python best practices by applying explicit naming, type hints, and dataclass usage, while standardizing tooling with Black, Ruff, and mypy to improve readability and maintainability across your codebase.

Structure data models in Python using dataclasses to improve readability and tooling support, applying type annotations to ensure explicit interfaces and robust API design.

Refactor Python code to use composition over inheritance by restructuring classes into modular components with clear interfaces, reducing coupling, and improving debugging and collaboration.

Type hints and standardized tooling like mypy and Ruff are essential for Python testing, as they enforce explicit interfaces and standardized guidelines that improve debugging and code robustness.

You can get a concise Python best-practices review for your project by requesting an analysis that proposes three concrete improvements with examples covering typing, dataclasses, and error handling.