Python装饰器实战：5个高级应用场景

1. 基础函数装饰器

实现简单的日志记录装饰器：

def log_execution(func):
    def wrapper(*args, **kwargs):
        print(f"开始执行: {func.__name__}")
        result = func(*args, **kwargs)
        print(f"执行完成: {func.__name__}")
        return result
    return wrapper

@log_execution
def calculate_sum(a, b):
    return a + b

# 使用
result = calculate_sum(3, 5)
print(f"结果: {result}")

2. 带参数的装饰器

创建可配置的重试机制：

def retry(max_attempts=3, delay=1):
    def decorator(func):
        import time
        def wrapper(*args, **kwargs):
            attempts = 0
            while attempts < max_attempts:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    attempts += 1
                    print(f"尝试 {attempts} 失败: {e}")
                    if attempts == max_attempts:
                        raise
                    time.sleep(delay)
        return wrapper
    return decorator

@retry(max_attempts=5, delay=2)
def fetch_data(url):
    # 模拟可能失败的请求
    if "example" not in url:
        raise ValueError("无效的URL")
    return "数据内容"

3. 类装饰器

为类添加单例模式：

def singleton(cls):
    instances = {}
    def wrapper(*args, **kwargs):
        if cls not in instances:
            instances[cls] = cls(*args, **kwargs)
        return instances[cls]
    return wrapper

@singleton
class DatabaseConnection:
    def __init__(self):
        print("创建新的数据库连接")
        
# 使用
conn1 = DatabaseConnection()
conn2 = DatabaseConnection()
print(conn1 is conn2)  # 输出: True

4. 方法装饰器

实现属性缓存：

def cached_property(func):
    @property
    def wrapper(self):
        cache_attr = f"_cached_{func.__name__}"
        if not hasattr(self, cache_attr):
            setattr(self, cache_attr, func(self))
        return getattr(self, cache_attr)
    return wrapper

class DataProcessor:
    @cached_property
    def processed_data(self):
        print("执行耗时计算...")
        return [i**2 for i in range(1000000)]

5. 装饰器组合与顺序

def validate_input(func):
    def wrapper(a, b):
        if not isinstance(a, (int, float)) or not isinstance(b, (int, float)):
            raise ValueError("参数必须是数字")
        return func(a, b)
    return wrapper

def log_arguments(func):
    def wrapper(a, b):
        print(f"调用参数: a={a}, b={b}")
        return func(a, b)
    return wrapper

@validate_input
@log_arguments
def divide(a, b):
    return a / b

# 使用
result = divide(10, 2)  # 先验证参数，再记录日志

合理使用装饰器可以大幅提升Python代码的可维护性和复用性，是Python高级开发者的必备技能。