python中函数和方法的装饰器

python中函数和方法的装饰器

 

Python3.0之后加入新特性Decorators，以@为标记修饰function和class。有点类似c++的宏和java的注解。Decorators用以修饰约束function和class，分为带参数和不带参数，影响原有输出，例如类静态函数我们要表达的时候需要函数前面加上修饰@staticmethod或@classmethod,

 

不带参数的单一使用

In [1]:

def spamrun(fn):
    def sayspam(*args):
        print("spam,spam,spam")
        fn(*args)
    return sayspam


@spamrun
def useful(a, b):
    print(a * b)


if __name__ == "__main__":
    useful(2, 5)

 

spam,spam,spam
10

 

函数useful本身应该只是打印10，可是为什么最后的结果是这样的呢，其实我们可以简单的把这个代码理解为

In [4]:

"""
if __name__ == "__main__":
    useful = spamrun(useful)
    useful(a, b)
"""

Out[4]:

'\nif __name__ == "__main__":\n    useful = spamrun(useful)\n    useful(a, b)\n'

 

不带参数的多次使用

In [ ]:

def spamrun(fn):
    def sayspam(*args):
        print("spam,spam,spam")
        fn(*args)
    return sayspam


def spamrun1(fn):
    def sayspam1(*args):
        print("spam1,spam1,spam1")
        fn(*args)
    return sayspam1

@spamrun
@spamrun
@spamrun1
def useful(a, b):
    print(a * b)
    

if __name__ == "__main__":
    useful(2, 5)

 

带参数的单次使用

In [8]:

def attrs(**kwds):
    def decorate(f):
        for k in kwds:
            setattr(f, k, kwds[k])
        return f

    return decorate


@attrs(versionadded="2.2", author="Guido van Rossum")
def mymethod(f):
    print(getattr(mymethod, 'versionadded', 0))
    print(getattr(mymethod, 'author', 0))
    print(f)


if __name__ == "__main__":
    mymethod(2)

 

2.2
Guido van Rossum
2

 

实际应用：记录函数执行的时间

In [13]:

import time


def timer(func):
    def wrapper(*args, **kw):
        begin_time = time.time()
        func(*args, **kw)
        end_time = time.time()
        print(f'{func.__name__} cost time:{end_time-begin_time}s')
    return wrapper


@timer
def test():
    time.sleep(1)
    print('test_1111')


if __name__ == '__main__':
    test()

 

test_1111
test cost time:1.0069596767425537s