1. 简单装饰器

import timedef timer(func):    def wrapper(*args,**kwargs):        t1 = time.time()        func(*args,**kwargs)        t2 = time.time()        run_time = t2 - t1        print(run_time)    return wrapper@timerdef foo():    time.sleep(3)#foo()                   # 3.0006301403045654foo = timer(foo)        # 等同于使用timer装饰器foo()                   # 3.0006301403045654

2. 带参数的装饰器

import loggingdef log(level):    def decorator(func):        def wrapper(*args,**kwargs):            if level == 'warn':                logging.warn("%s is running" % func.__name__)            return func(*args,**kwargs)        return wrapper    return decorator@log('warn')def foo(a='123'):    print('the number is %s' %a)foo()the number is 123WARNING:root:foo is running

3. 类装饰器

import loggingdef log(level):    def decorator(func):        def wrapper(*args,**kwargs):            if level == 'warn':                logging.warn("%s is running" % func.__name__)            return func(*args,**kwargs)        return wrapper    return decorator@log('warn')def foo(a='123'):    print('the number is %s' %a)foo()the number is 123WARNING:root:foo is running

4. 类装饰器

import loggingdef log(level):    def decorator(func):        def wrapper(*args,**kwargs):            if level == 'warn':                logging.warn("%s is running" % func.__name__)            return func(*args,**kwargs)        return wrapper    return decorator@log('warn')def foo(a='123'):    print('the number is %s' %a)foo()the number is 123WARNING:root:foo is running

5. functools.wraps

#装饰器有个缺点，会改变原函数的元信息#functools.wraps本身也是装饰器，可把元信息拷贝到装饰器函数中，使元信息和原装饰器一致from functools import wrapsdef logged(func):    @wraps(func)    def with_logging(*args,**kwargs):        print(func.__name__ + "was called")        return func(*args,**kwargs)    return with_logging@loggeddef f(x):    """does soma math"""return x + x * xprint(f.__name__)print(f.__doc__)

6. 装饰器顺序

@a@b@cdef f():    pass# 等价于f = a(b(c(f)))