Python decorators — how they work and how to write one

Decorators

A decorator is a function that takes a function and returns a modified version. The @decorator syntax is shorthand for func = decorator(func).

def log(func):
    def wrapper(*args, **kwargs):
        print(f"Calling {func.__name__}")
        result = func(*args, **kwargs)
        print(f"Done")
        return result
    return wrapper

@log
def add(a, b):
    return a + b

print(add(2, 3))
# Calling add
# Done
# 5

Preserving Metadata

from functools import wraps

def log(func):
    @wraps(func)         # preserves __name__, __doc__
    def wrapper(*args, **kwargs):
        print(f"Calling {func.__name__}")
        return func(*args, **kwargs)
    return wrapper

Decorator with Arguments

def repeat(n):
    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            for _ in range(n):
                func(*args, **kwargs)
        return wrapper
    return decorator

@repeat(3)
def say(msg):
    print(msg)

say("hello")  # prints hello 3 times

Always use @wraps(func) inside your wrapper to preserve the original function's identity.

Decorators are one of Python's most powerful metaprogramming features. The standard library uses them everywhere: @property, @classmethod, @staticmethod, @functools.lru_cache, and @dataclass are all decorators. Web frameworks like Flask and FastAPI use decorators to register route handlers: @app.route("/"). Once you understand that a decorator is just a function that receives and returns a function, the pattern becomes natural. Stacking multiple decorators is valid — they apply bottom-up, so the decorator closest to the function runs first.