Python裝飾器原理與實(shí)戰(zhàn)全解

更新時(shí)間：2026年05月05日 11:31:25 作者：第一程序員

這篇文章主要介紹了Python裝飾器原理與實(shí)戰(zhàn),裝飾器是Python中一種強(qiáng)大的特性,它允許我們以一種簡潔、優(yōu)雅的方式增強(qiáng)函數(shù)的功能,通過掌握裝飾器的高級(jí)應(yīng)用,我們可以編寫更加模塊化、可維護(hù)的代碼

1. 裝飾器基礎(chǔ)

裝飾器是 Python 中一種強(qiáng)大的特性，它允許我們?cè)诓恍薷脑瘮?shù)代碼的情況下，增強(qiáng)函數(shù)的功能。

def decorator(func):
    def wrapper(*args, **kwargs):
        print("Before function call")
        result = func(*args, **kwargs)
        print("After function call")
        return result
    return wrapper
@decorator
def greet(name):
    print(f"Hello, {name}!")
# 調(diào)用被裝飾的函數(shù)
greet("Alice")

2. 帶參數(shù)的裝飾器

2.1 基本帶參裝飾器

def repeat(n):
    def decorator(func):
        def wrapper(*args, **kwargs):
            for i in range(n):
                result = func(*args, **kwargs)
            return result
        return wrapper
    return decorator
@repeat(3)
def greet(name):
    print(f"Hello, {name}!")
greet("Alice")

2.2 裝飾器類

class Timer:
    def __init__(self, unit="seconds"):
        self.unit = unit
    def __call__(self, func):
        def wrapper(*args, **kwargs):
            import time
            start = time.time()
            result = func(*args, **kwargs)
            end = time.time()
            duration = end - start
            if self.unit == "milliseconds":
                duration *= 1000
            print(f"Function {func.__name__} took {duration:.2f} {self.unit}")
            return result
        return wrapper
@Timer(unit="milliseconds")
def slow_function():
    import time
    time.sleep(1)
    print("Function executed")
slow_function()

3. 高級(jí)裝飾器技巧

3.1 保留函數(shù)元數(shù)據(jù)

使用 functools.wraps 可以保留被裝飾函數(shù)的元數(shù)據(jù)。

import functools
def decorator(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        """Wrapper function"""
        print("Before function call")
        result = func(*args, **kwargs)
        print("After function call")
        return result
    return wrapper
@decorator
def greet(name):
    """Greet someone"""
    print(f"Hello, {name}!")
print(greet.__name__)  # 輸出: greet
print(greet.__doc__)   # 輸出: Greet someone

3.2 疊加裝飾器

多個(gè)裝飾器可以疊加使用，執(zhí)行順序是從下到上。

def decorator1(func):
    def wrapper(*args, **kwargs):
        print("Decorator 1 before")
        result = func(*args, **kwargs)
        print("Decorator 1 after")
        return result
    return wrapper
def decorator2(func):
    def wrapper(*args, **kwargs):
        print("Decorator 2 before")
        result = func(*args, **kwargs)
        print("Decorator 2 after")
        return result
    return wrapper
@decorator1
@decorator2
def greet(name):
    print(f"Hello, {name}!")
greet("Alice")
# 輸出順序:
# Decorator 1 before
# Decorator 2 before
# Hello, Alice!
# Decorator 2 after
# Decorator 1 after

3.3 裝飾器工廠

裝飾器工廠是一個(gè)函數(shù)，它返回一個(gè)裝飾器。

def create_decorator(prefix):
    def decorator(func):
        def wrapper(*args, **kwargs):
            print(f"{prefix}: Before function call")
            result = func(*args, **kwargs)
            print(f"{prefix}: After function call")
            return result
        return wrapper
    return decorator
@create_decorator("DEBUG")
def greet(name):
    print(f"Hello, {name}!")
greet("Alice")

4. 實(shí)際應(yīng)用場(chǎng)景

4.1 日志記錄

import functools
import logging
logging.basicConfig(level=logging.INFO)
def log(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}")
        result = func(*args, **kwargs)
        logging.info(f"{func.__name__} returned: {result}")
        return result
    return wrapper
@log
def add(a, b):
    return a + b
result = add(1, 2)
print(result)

4.2 緩存

import functools
def cache(func):
    cache_dict = {}
    @functools.wraps(func)
    def wrapper(*args):
        if args in cache_dict:
            return cache_dict[args]
        result = func(*args)
        cache_dict[args] = result
        return result
    return wrapper
@cache
def fibonacci(n):
    if n <= 1:
        return n
    return fibonacci(n-1) + fibonacci(n-2)
print(fibonacci(30))  # 第一次計(jì)算較慢
print(fibonacci(30))  # 第二次使用緩存，速度很快

4.3 權(quán)限驗(yàn)證

import functools
def requires_permission(permission):
    def decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            # 假設(shè) current_user 是當(dāng)前登錄用戶
            current_user = {"permissions": ["read", "write"]}
            if permission not in current_user["permissions"]:
                raise PermissionError(f"User does not have {permission} permission")
            return func(*args, **kwargs)
        return wrapper
    return decorator
@requires_permission("write")
def create_post(title, content):
    print(f"Creating post: {title}")
    return {"title": title, "content": content}
@requires_permission("admin")
def delete_post(post_id):
    print(f"Deleting post: {post_id}")
    return True
create_post("Hello", "World")  # 成功
# delete_post(1)  # 拋出 PermissionError

4.4 性能分析

import functools
import time
def performance(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        start_time = time.time()
        result = func(*args, **kwargs)
        end_time = time.time()
        print(f"{func.__name__} took {end_time - start_time:.4f} seconds")
        return result
    return wrapper
@performance
def slow_function():
    time.sleep(1)
    return "Done"
slow_function()