12 Dynamic Python Decorators for Enhanced Code Performance
2 min readFeb 11, 2023
Python decorators:
@staticmethod
: This decorator is used to define static methods, which are methods that don't access or modify the object's state.@classmethod
: This decorator defines class methods, which operate on the class rather than on class instances.@property
: This decorator is used to describe getter methods for class attributes.@attribute.setter
: This decorator is used to describe setter methods for class attributes.@attribute.deleter
: This decorator is used to describe deleter methods for class attributes.functools.lru_cache
: This decorator is used to cache the result of a function so that subsequent calls with the same arguments return the cached result rather than recalculating it.functools.singledispatch
: This decorator is used to create a single-dispatch generic function, which is a function that dispatches on the type of its first argument.functools. wraps
: This decorator is used to preserve the metadata of a function, such as its name and docstring, when defining a new function that wraps it.unittest.mock.patch
: This decorator is used to temporarily replace the behavior of an object, such as a function or module, for the duration of a test.debug
: This custom decorator can be used to add debugging information to functions.timing
: This is a custom decorator that can be used to measure the execution time of a function.authentication
: This is a custom decorator that can be used to enforce authentication for certain parts of an application.
These are just a few examples of the many ways that Python decorators can be used to enhance your code. Decorators are a powerful feature of Python, allowing you to easily add functionality to existing code without having to modify it directly.