The typing module provides support for type hints in Python code. Use it to add type annotations for better code documentation, IDE support, and static type checking with tools like mypy.

A user-defined generic class can have ABCs as base classes without a metaclass conflict. Generic metaclasses are not supported. The outcome of parameterizing generics is cached, and most types in the typing module are hashable and comparable for equality.

Built-in Modules Random Module Requests Module Statistics Module Math Module cMath Module · Remove List Duplicates Reverse a String Add Two Numbers · Python Examples Python Compiler Python Exercises Python Quiz Python Challenges Python Server Python Syllabus Python Study Plan Python Interview Q&A Python Bootcamp Python Certificate Python Training ... a = ('apple', 'banana', 'cherry') b = "Hello World" c = 33 x = type(a) y = type(b) z = type(c) Try it Yourself »

The notation can be used for documenting code in a concise, standard format, and it has been designed to also be used by static and runtime type checkers, static analyzers, IDEs and other tools. NOTE: in Python 3.5 and later, the typing module lives in the stdlib, and installing this package has NO EFFECT, because stdlib takes higher precedence than the installation directory.

# For most types, just use the ... x: tuple[int, ...] = (1, 2, 3) # Python 3.9+ # On Python 3.8 and earlier, the name of the collection type is # capitalized, and the type is imported from the 'typing' module from typing import List, Set, Dict, Tuple x: List[int] = [1] ...

August 4, 2022 - This makes Python code much more readable and robust as well, to other readers! NOTE: This does not do actual type checking at compile time. If the actual object returned was not of the same type as hinted, there will be no compilation error. This is why we use external type checkers, such as mypy to identify any type errors. For using the typing module effectively, it is recommended that you use an external type checker/linter to check for static type matching.

Imagine you’re building an order processing system where you want to apply discounts to products. Using the typing module, you can create distinct type aliases, type variables, and callables to make your code safer and more expressive:

July 15, 2024 - Note: Static type checkers are more than able to figure out that 3.142 is a float, so in this example the annotation of pi is not necessary. As you learn more about the Python type system, you’ll see more relevant examples of variable annotations. Annotations of variables are stored in the module level __annotations__ dictionary:

July 26, 2025 - The typing-extensions module is an essential library in Python that allows developers to use advanced type hinting features before they are officially added to the standard typing module.

Learn how to use the Python Typing Module for type hints and annotations in your code.

May 17, 2024 - Before Python 3.5, developers who wanted to include type annotations in their code had to rely on external libraries. The introduction of the typing module in Python 3.5 made type annotations an integral part of the language, enhancing code readability and maintainability.

The proposal is strongly inspired by mypy. For example, the type “sequence of integers” can be written as Sequence[int]. The square brackets mean that no new syntax needs to be added to the language. The example here uses a custom type Sequence, imported from a pure-Python module typing.

January 27, 2026 - Master Python's typing module for better code quality. Learn how to use type hints, generics, protocols, and type guards to write safer, more maintainable code.

December 11, 2024 - To work effectively, a developer should consider Python's strong dynamic typing, use type annotations and the typing module, remember the possibility of creating custom data structures, and not neglect type-checking tools.

The return type for an __init__ method does not need to be specified, since it is always None. The following module-level symbols do not require type annotations: __all__,__author__, __copyright__, __email__, __license__, __title__, __uri__, __version__.

Python has the following data types built-in by default, in these categories: You can get the data type of any object by using the type() function: ... If you want to use W3Schools services as an educational institution, team or enterprise, ...

Conformance test for Python static type checkers. The latest conformance test results are here. ... The typing_extensions package, which now lives in the typing_extensions repo. It used to be in the typing_extensions directory. A backport of the typing module for older Python versions.

Class definition syntax follows general Python syntax, but type checkers are expected to understand only the following constructs in class bodies: The ellipsis literal ... is used for empty class bodies. Using pass in class bodies is undefined. Instance attributes follow the same rules as module level attributes (see above).

May 30, 2025 - The typing module provides a standard way to specify the expected data types of variables, function parameters, and return values. This is known as type annotation or type hinting.