python-type-safety

Enforce strict type checking in Python by adding type annotations to functions and variables, then running mypy or pyright with strict settings to catch type errors statically before runtime.

Python protocols enable structural typing for defining interfaces without heavy inheritance. Use protocols when you need flexible, type-safe abstractions that allow safer refactors and easier collaboration across modules.

Create type-safe generics in Python by defining classes or functions with type variables, enabling scalable and reusable abstractions. Static analysers like mypy or pyright then verify type consistency across usages.

Both mypy and pyright enforce Python type annotations with strict settings. Mypy is widely adopted for continuous verification, while pyright offers faster static checking and strict type safety analysis.

Yes, you can incrementally add type safety to an existing Python project by annotating functions and variables, introducing generics and protocols, and running mypy or pyright to catch issues early.

mypy strict mode fails because it requires explicit type annotations on all functions, classes, and variables to document intent and enable continuous static verification, preventing untyped code from passing checks.