Understanding Python Decorators

Decorators are one of Python's most elegant features. They allow you to modify the behavior of functions or classes without changing their source code.

What are Decorators?

A decorator is a function that takes another function and extends its behavior without explicitly modifying it. It's essentially a wrapper function.

Basic Decorator Syntax

def my_decorator(func):
    def wrapper():
        print("Something is happening before the function is called.")
        func()
        print("Something is happening after the function is called.")
    return wrapper

@my_decorator
def say_hello():
    print("Hello!")

say_hello()

Common Use Cases

1. Timing Functions

import time

def timing_decorator(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        print(f"{func.__name__} took {end - start} seconds")
        return result
    return wrapper

2. Caching

from functools import lru_cache

@lru_cache(maxsize=128)
def expensive_function(n):
    # Expensive computation
    return n * n

3. Authentication

def require_auth(func):
    def wrapper(*args, **kwargs):
        if not is_authenticated():
            raise PermissionError("Authentication required")
        return func(*args, **kwargs)
    return wrapper

Class Decorators

You can also use decorators with classes:

def add_method(cls):
    def new_method(self):
        return "New method added!"
    cls.new_method = new_method
    return cls

@add_method
class MyClass:
    pass

Best Practices

• Use functools.wraps to preserve function metadata
• Keep decorators simple and focused
• Document what your decorator does
• Consider using decorator factories for parameterized decorators

Decorators are a powerful tool that can make your code more elegant and maintainable.