How Type Hints and mypy Bring Compile-Time Checks to Python

Python's dynamic typing moves type errors from runtime to edit time when combined with type hints and mypy, cutting debugging costs and making large codebases more maintainable. The staged adoption plan makes this feasible for codebases already running in production, without a full rewrite.

Python's dynamic typing defers type errors to runtime. Type hints, introduced in PEP 484, declare types in source without affecting runtime. Running mypy catches incompatible arguments, missing None checks, and return-type mismatches during development. The syntax ranges from simple variable annotations to generics: built-in generics like list[str] and dict[str, int] work from Python 3.9, and the | operator shortens Optional and Union from 3.10. For classes, dataclasses pair naturally with annotations, and TypeVar preserves type information through generic functions and classes, with PEP 695 simplifying the syntax in 3.12.

Adopting mypy on an existing codebase follows a staged path: check only new code, exempt old modules with # type: ignore, enable strict per module, then wire mypy into CI. Configuration lives in pyproject.toml with options like disallow_untyped_defs and warn_return_any. Three recurring problems get concrete fixes: third-party libraries missing stubs (install types-requests or add ignore_missing_imports), circular imports (use from __future__ import annotations or string forward references), and dynamic attributes (prefer TypedDict or Protocol).