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Python decorators provide a simple yet powerful way to modify functions and methods. Decorators wrap a function to extend its behavior without permanently modifying it.
They allow you to encapsulate code functionality that you may want to apply to various functions with slight differences. This makes decorators ideal for things like logging, timing functions, rate limiting, authentication, caching, and more.
In this tutorial, I’ll explain what decorators are and why they’re useful. Then we’ll walk through examples to help you understand how to write your own decorators in Python.
What Are Python Decorators?
A Python decorator is a design pattern that allows a function or class to be wrapped in a callable object, preserving its signature.
The decorator can process the function arguments, call the function, and modify the return value or exception raised without explicitly modifying the function source code.
Decorators provide an alternative to using subclassing to extend functionality.
As Python ships with many utility decorators in its standard library, they are commonly used to add logging, enforce access control and caching, measure performance, rate limit execution, and more.
