Python in a Nutshell, 4th Edition

Chapter 5. Type Annotations

Annotating your Python code with type information is an optional step which can be very helpful during development and maintenance of a large project or a library. Static type checkers and lint tools help identify and locate data type mismatches in function arguments and return values. IDEs can use these type annotations (also called type hints) to improve autocompletion and to provide pop-up documentation. Third-party packages and frameworks can use type annotations to tailor runtime behavior, or to autogenerate code based on type annotations for methods and variables.

Type annotations and checking in Python continue to evolve, and touch on many complicated issues. This chapter covers some of the most common use cases for type annotations; you can find more comprehensive material in the resources listed at the end of the chapter.

Type Annotation Support Varies by Python Version

Python’s features supporting type annotations have evolved from version to version, with some significant additions and deletions. The rest of this chapter will describe the type annotation support in the most recent versions of Python (3.10 and later), with notes to indicate features that might be present or absent in other versions.

History

Python is, fundamentally, a dynamically typed language. This lets you rapidly develop code by naming and using variables without having to declare them. Dynamic typing allows for flexible coding idioms, generic containers, and polymorphic ...