python 高阶函数：Decorator(装饰器)

超、凢脫俗 2022-01-11 10:21 232阅读 0赞

装饰器：原函数基础 ------> **动态**添加功能

一、不带参数的decorator

\#decorator封装

def log(func):  
def wrapper(\*args, \*\*kw):  
print 'call %s():' %func.\_\_name\_\_  
return func(\*args, \*\*kw)  
return wrapper

\#此函数一定要放在 def log(func)： 之后

@log  
def now():  
print "haha"

now()

![log.PNG][]

log(now())  
![log.PNG][log.PNG 1]

print "now\_name:%s"%now.\_\_name\_\_

![log1.PNG][]

简单的图解：（待以后深入理解后再详细补）

![log图解.png][log_.png]

二、带参数的docurator

\#!/usr/bin/python

\#docurator封装

def log(text):  
def decorator(func):  
def wrapper(\*args, \*\*kw):  
print('%s %s():' % (text, func.\_\_name\_\_))  
return func(\*args, \*\*kw)  
return wrapper  
return decorator

@log('execute')  
def now():  
print "haha"

print "now\_name:%s"%now.\_\_name\_\_

![log1.PNG][log1.PNG 1]

now()

![log2.PNG][]

print log('execute')  
print log(now)  
print log('execute')(now)

![log3.PNG][]

三、完整的decorator的写法:Python内置的functools.wraps

import functools \#导入functools模块

def log(text):  
def decorator(func):  
@functools.wraps(func)  
def wrapper(\*args, \*\*kw):  
print('%s %s():' % (text, func.\_\_name\_\_))  
return func(\*args, \*\*kw)  
return wrapper  
return decorator

@log('execute')  
def now():  
print "haha"  
  
print "now\_name:%s"%now.\_\_name\_\_

![log4.PNG][]

now()

![log2.PNG][log2.PNG 1]

print log('execute')  
print log(now)  
print log('execute')(now)

![log5.PNG][]

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日期：2018/8/18

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补充：

1.  多个装饰器的执行顺序是无序的，但执行过程是有序的。
2.  装饰器执行过程是：遇到外接函数就跳转到另一个装饰器中执行，若再另一个装饰器中遇到同样的外接函数，则继续执行

证明1：多个装饰器的执行顺序是无序的

#!/usr/bin/python
    # -*- coding: utf-8 -*-
    
    import time
    
    
    def extend(func):
        def wrapper(*args, **kwargs):
            print "Begin AAAAAA"
            func(*args, **kwargs)
            print("A:%s"%(func.__name__))
            print(reduce(lambda x,y:x+y, args), kwargs)
            print "End AAAAA"
        return wrapper
    
    
    def extend1(func):
        def wrapper(*args, **kwargs):
            print "Begin BBBBB"
            func(*args, **kwargs)
            print("B:%s"%(func.__name__))
            print(map(lambda x:x*2, args), kwargs)
            print "End BBBBB"    
        return wrapper
    
    @extend      
    @extend1
    def get_time1(*args,**kwargs):
        begin_time = time.time()
        for n in range(3,4):
            time.sleep(1)
        end_time = time.time()
        print("run %d "% (end_time - begin_time))
        #print(reduce(lambda x,y:x+y, args), kwargs)
    
        
    if __name__ == "__main__":
    
        get_time1(1,2,3,4,5,6,ma=1,du=2)

执行结果：先从第一个装饰器标志@extend开始

Begin AAAAAA
    Begin BBBBB
    run 1 
    B:get_time1
    ([2, 4, 6, 8, 10, 12], {'du': 2, 'ma': 1})
    End BBBBB
    A:wrapper
    (21, {'du': 2, 'ma': 1})
    End AAAAA

另一个例子：

#!/usr/bin/python
    # -*- coding: utf-8 -*-
    def dec1(func):  
        print("1111")  
        def wrapper(*args, **kwargs):  
            print("2222")  
            func()  
            print("3333")  
        return wrapper  
    
    def dec2(func):  
        print("aaaa")  
        def wrapper(*args, **kwargs):  
            print("bbbb")  
            func()  
            print("cccc")  
        return wrapper  
    
    @dec1  
    @dec2  
    def test():  
        print("test test")  
    
    test()

运行结果：从第二个装饰器标志@dec2开始

aaaa
    1111
    2222
    bbbb
    test test
    cccc
    3333

通过比较，多个解释器的执行顺序是无序的。若大家觉得证明不够严谨，可自己多添几个试试。

证明2：装饰器的执行过程是有序的

图1：

![装饰器原函数1.png][1.png]

图2：

![装饰器原函数倒装1.png][1.png 1]

没看懂？没关系，进行步骤解析：

![装饰器原函数结果解析1.png][1.png 2]

\-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

2018/8/20

补充：一个讲的很好的BLOG: https://blog.csdn.net/xiangxianghehe/article/details/77170585

转载于:https://blog.51cto.com/13502993/2146021

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