python-typing-patterns

Type hints annotate function parameters and return values with expected types, enabling static type checkers like mypy and pyright to catch errors before runtime. Use basic syntax like `def func(x: int) -> str:` and advance to generics, Protocols, and TypedDict for complex data structures in Python 3.10+.

Protocols enable structural typing—objects matching a method signature work interchangeably without inheritance. TypedDict defines typed dictionaries with fixed keys and value types. Use Protocols for flexible interfaces and TypedDict for type-safe dictionary data models without class overhead.

TypeVar creates type variables; generics parameterize functions and classes to work with multiple types while preserving type safety. Use `T = TypeVar('T')` and `class Container(Generic[T]):` to write code once that type-checks correctly across different input types.

Yes. mypy and pyright integrate with type hints to provide real-time IDE hints, catch type mismatches before runtime, and validate against function signatures. Configure via `mypy.ini` or `pyrightconfig.json` to enforce typing across your Python 3.10+ project.

Static type checkers verify code at development time but don't enforce checks at runtime. Add runtime validation using `isinstance()` checks, Pydantic models, or type-guard decorators to catch type violations when code executes with unexpected data.

Literal restricts values to specific constants (e.g., `Literal['read', 'write']`). Overload allows multiple valid type signatures for one function. Together they express precise input-output contracts for code generation, type-safe APIs, and utilities with context-dependent behavior.