Decorators are a powerful and elegant way to modify or extend the behavior of functions in Python. However, their flexibility often comes at the cost of clarity—what arguments should be passed, which functions can they wrap, and how do they affect return types? These uncertainties can lead to unexpected bugs and runtime errors.

By incorporating type annotations, we can eliminate ambiguity and leverage static type checkers like mypy and pyright to catch mistakes before they become problems. Well-typed decorators not only enhance code readability but also provide early warnings about incorrect usage, reducing debugging time and improving maintainability.

In this talk, we will explore practical techniques for defining type-safe decorators using typing.ParamSpec, TypeVarTuple, Protocol, Concatenate, and Type Parameter Syntax. You'll learn how to build decorators that preserve function signatures, work seamlessly with type checkers, and integrate smoothly into robust Python projects. Whether you're new to type hints or looking to refine your decorator skills, this session will equip you with the tools and best practices to write cleaner, safer, and more maintainable Python code.