Decorators

Syntax

@decorator_name\ndef function():\n    ...

Examples

def announce(func):
    def wrapper():
        print("Starting function...")
        func()
        print("Function finished.")
    return wrapper

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

say_hello()
# Starting function...
# Hello!
# Function finished.

import time

def timer(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        elapsed = time.time() - start
        print(f"{func.__name__} took {elapsed:.4f}s")
        return result
    return wrapper

@timer
def slow_add(a, b):
    time.sleep(0.1)
    return a + b

print(slow_add(3, 4))

import functools

def log_call(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        print(f"Calling {func.__name__}")
        return func(*args, **kwargs)
    return wrapper

@log_call
def greet(name):
    """Greet someone by name."""
    return f"Hello, {name}!"

print(greet("Fola"))
print(greet.__name__)  # greet (not "wrapper")

from functools import lru_cache

@lru_cache(maxsize=None)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

print(fibonacci(30))  # computed quickly thanks to caching

Best practices

• Always use functools.wraps inside your decorator's wrapper function, so the decorated function keeps its original name, docstring, and metadata
• Accept *args and **kwargs in the wrapper so your decorator works with functions of any signature
• Use built-in decorators like @staticmethod, @classmethod, @property, and @functools.lru_cache before writing your own for common needs
• Keep decorators focused on one concern (logging, timing, caching) rather than bundling multiple responsibilities into one

At a glance

Purpose

Scripting and general-purpose applications

File extension

.py

Runs in

Python interpreter

Usually used with

Python standard library and packages

Specifications & further reading

• Python language reference

Related Python documentation