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Python 装饰器高级应用指南

news 2026/4/16 3:51:56

Python 装饰器高级应用指南

1. 什么是装饰器？

装饰器是 Python 中一种特殊的语法结构，用于修改函数或类的行为。它允许我们在不修改原函数代码的情况下，为函数添加额外的功能。

2. 基本语法

装饰器使用@符号来应用，放在函数定义的上方。

@decorator def function(): pass

3. 装饰器的实现

3.1 简单装饰器

def my_decorator(func): def wrapper(): print("Before function call") func() print("After function call") return wrapper @my_decorator def say_hello(): print("Hello") say_hello() # 输出: # Before function call # Hello # After function call

3.2 带参数的装饰器

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

3.3 保留函数元数据

使用functools.wraps可以保留原函数的元数据，如函数名、文档字符串等。

import functools def my_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 @my_decorator def say_hello(): """Say hello function""" print("Hello") print(say_hello.__name__) # 输出: say_hello print(say_hello.__doc__) # 输出: Say hello function

4. 高级应用

4.1 类装饰器

类装饰器是使用类来实现的装饰器，它通过__call__方法来实现装饰功能。

class CountCalls: def __init__(self, func): self.func = func self.count = 0 def __call__(self, *args, **kwargs): self.count += 1 print(f"Call {self.count} of {self.func.__name__}") return self.func(*args, **kwargs) @CountCalls def say_hello(): print("Hello") say_hello() # 输出: Call 1 of say_hello # Hello say_hello() # 输出: Call 2 of say_hello # Hello

4.2 装饰器链

多个装饰器可以同时应用到一个函数上，形成装饰器链。

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 say_hello(): print("Hello") say_hello() # 输出: # Decorator 1 before # Decorator 2 before # Hello # Decorator 2 after # Decorator 1 after

4.3 带状态的装饰器

装饰器可以保持状态，例如缓存函数结果。

import functools def cache(func): """Cache function results""" cache_dict = {} @functools.wraps(func) def wrapper(*args, **kwargs): key = str(args) + str(kwargs) if key not in cache_dict: cache_dict[key] = func(*args, **kwargs) return cache_dict[key] return wrapper @cache def fibonacci(n): if n <= 1: return n return fibonacci(n-1) + fibonacci(n-2) print(fibonacci(30)) # 第一次计算，会缓存结果 print(fibonacci(30)) # 直接从缓存获取结果

4.4 装饰器工厂

装饰器工厂是返回装饰器的函数，允许我们为装饰器提供配置参数。

def log_level(level): def decorator(func): @functools.wraps(func) def wrapper(*args, **kwargs): print(f"[{level.upper()}] Calling {func.__name__}") result = func(*args, **kwargs) print(f"[{level.upper()}] {func.__name__} completed") return result return wrapper return decorator @log_level("info") def process_data(data): print(f"Processing data: {data}") return data * 2 @log_level("error") def handle_error(): print("Handling error") process_data(42) # 输出: [INFO] Calling process_data # Processing data: 42 # [INFO] process_data completed handle_error() # 输出: [ERROR] Calling handle_error # Handling error # [ERROR] handle_error completed

5. 实际应用场景

5.1 日志记录

def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): print(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") result = func(*args, **kwargs) print(f"{func.__name__} returned: {result}") return result return wrapper @log_function def add(a, b): return a + b add(3, 5) # 输出调用信息和返回值

5.2 性能计时

import time def timer(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 @timer def slow_function(): time.sleep(1) return "Done" slow_function() # 输出执行时间

5.3 权限验证

def require_permission(permission): def decorator(func): @functools.wraps(func) def wrapper(*args, **kwargs): # 假设当前用户权限存储在 current_user.permissions 中 current_user = {"permissions": ["read", "write"]} if permission not in current_user["permissions"]: raise PermissionError(f"Required permission: {permission}") return func(*args, **kwargs) return wrapper return decorator @require_permission("write") def create_post(content): print(f"Creating post: {content}") return "Post created" @require_permission("admin") def delete_post(post_id): print(f"Deleting post: {post_id}") return "Post deleted" create_post("Hello World") # 成功执行 try: delete_post(1) except PermissionError as e: print(e) # 抛出权限错误

5.4 输入验证

def validate_input(*types): def decorator(func): @functools.wraps(func) def wrapper(*args, **kwargs): for arg, type_ in zip(args, types): if not isinstance(arg, type_): raise TypeError(f"Expected {type_}, got {type(arg)}") return func(*args, **kwargs) return wrapper return decorator @validate_input(int, str) def process_user(user_id, name): print(f"Processing user {user_id}: {name}") return f"User {user_id} processed" process_user(1, "Alice") # 成功执行 try: process_user("1", "Alice") except TypeError as e: print(e) # 抛出类型错误