Understanding type annotation in Python

Python, known for its dynamic typing, allows datatypes to be determined at runtime, offering flexibility but also potential for runtime errors and performance issues typically not present in statically typed languages like Java or C++. To address these issues, Python introduced type hints, allowing developers to annotate variables and functions with datatypes and employ tools like mypy for static type-checking. This tutorial delves into the use of type hints in Python, focusing on the mypy tool, which provides warnings for inconsistencies in type usage. It covers adding type hints to variables, functions, lists, dictionaries, and tuples, and explores advanced features like the Protocol class, function overloading, and annotating constants. Static typing in Python is optional and supports gradual typing, enabling developers to introduce type hints incrementally, improving code documentation, reducing bugs, and enhancing IDE functionality.