python-type-safety

Enforce strict type checking by applying explicit type annotations to public APIs, using modern syntax like PEP 604 unions and generics, and configuring mypy or pyright for strict static analysis in your CI pipeline.

Add type hints to legacy Python projects by annotating public APIs, return values, and variables first, then enabling strict checking with mypy or pyright to catch errors and enable safer refactors.

Python generics and protocols build reusable, type-safe components by allowing functions and classes to adapt to multiple types, helping type checkers reason about optional and union types during static analysis.

Yes, mypy and pyright support static analysis for both new and legacy Python libraries, APIs, and data models, enforcing strict typing and catching runtime errors early when integrated into development workflows.

Python dynamic typing causes hard-to-trace runtime errors because types are checked at execution. Type guards and narrowing fix this by helping static analysis tools reason about optional and union types before runtime.

Using PEP 604 union syntax is required by this approach to make Python code type-safe, as it provides modern type hinting syntax that enables accurate static analysis and strict checking with mypy or pyright.