python-type-safety

Enforce static typing in Python by applying type annotations, generics, and protocols, then running mypy --strict or pyright in CI to catch type errors before production. This workflow improves readability and reliability across modules.

Python protocols and generics define structural interfaces and type-safe classes to ensure consistent interoperability across modules. They allow static type checkers like mypy and pyright to validate that different components interact correctly.

Configure strict type checks by running mypy --strict or pyright on your project, ensuring annotated function signatures and protocol definitions are integrated into your CI pipeline for consistent checks and early issue detection.

Static type checking can be introduced to existing codebases by annotating public APIs with precise types and implementing type narrowing guards. Tools like mypy and pyright then analyze the code to catch issues early and improve maintainability.

The best way to annotate Python public APIs is by applying precise type hints, defining generics for reusable classes, and using protocols for structural interfaces, enabling mypy or pyright to validate type safety consistently.

Mypy strict mode fails on dynamically typed modules because it requires annotated function signatures, explicit type narrowing guards, and protocol definitions to validate code. Without these annotations, static checks cannot verify type safety.