装饰器--棉花糖语法Python

最近很多人问我关于Python装饰器的问题，我把它总结成blog方便他人和自己。

借鉴了这篇关于装饰器的博文，http://www.cnblogs.com/rhcad/archive/2011/12/21/2295507.html。同时加入了自己的补充和心得。

我用Python IDE来调试，用了Python3.4.2。输出用>>>表示。

第一步：编写一个最简单的函数

#!/usr/bin/env pythondef myfunc():    print('myfunc() called')myfunc()

>>>myfunc() called

第二步：使用装饰函数在函数执行前后分别附加额外功能

#!/usr/bin/env pythondef deco(func):    print('before myfunc() called')    func()    print('after myfunc() called')    return funcdef myfunc():    print('myfunc() called')    deco(myfunc)

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called

如果调用函数改为：

myfunc = deco(myfunc)myfunc()

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called
>>>myfunc() called          <====myfunc()的输出

如果调用函数改为：

myfunc = deco(myfunc)

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called

第三步：使用棉花糖@语法来装饰函数

#!/usr/bin/env pythondef deco(func):    print('before myfunc() called')    func()    print('after myfunc() called')    return func@decodef myfunc():    print('myfunc() called')    myfunc()

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called
>>>myfunc() called          
解析：调用myfunc()，实际上等于 deco(myfunc)()

如果改为：

myfunc

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called
解析：调用myfunc，实际上等于 deco(myfunc)

第四步：使用内嵌包装函数来确保每次新函数都被调用

#!/usr/bin/env pythondef deco(func):    def wrapper():        print('before myfunc() called')        func()        print('after myfunc() called')    return wrapper@decodef myfunc():    print('myfunc() called')    <pre name="code" class="python">myfunc()

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called

myfunc()相当于执行包装函数wrapper().

如果调用改为

myfunc

>>>

没有输出，因为这样只是得到了包装函数wrapper的地址，并没有真正去运行它。

第五步：对带固定参数的函数进行装饰

#!/usr/bin/env pythondef deco(func):    def wrapper(a,b):  ##wrapper的入参必须和func一致        print('before myfunc() called')        func(a,b)        print('after myfunc() called')    return wrapper@decodef myfunc(a,b):    ret = a+b    print('{}+{}={}'.format(a,b,ret))    print('myfunc() called')    myfunc(1,2)

>>>before myfunc() called
>>>1+2=3
>>>myfunc() called
>>>after myfunc() called

包装函数wrapper的入参格式，数量必须和func函数一致，因为wrapper就是相当于调用装饰后的func函数。

第六步：对可变入参的函数进行装饰

#!/usr/bin/env pythondef deco(func):    def wrapper(*args,**kwargs):        print('before myfunc() called')        func(*args,**kwargs)        print('after myfunc() called')    return wrapper@decodef myfunc(a,b,c):    ret = a+b+c    print('{}+{}+{}={}'.format(a,b,c,ret))    print('myfunc() called')    myfunc(1,2,3)

类似于第五步，只是用*args表示可变数量，**kwargs表示key-value形式的参数数量可变

第七步：让装饰器带参数

#!/usr/bin/env pythonis_debug = True def deco(arg):    def midwrapper(func):        def innerwrapper(*args,**kwargs):            print('before myfunc() called')            func(*args,**kwargs)            print('after myfunc() called')        return innerwrapper    return midwrapper@deco(is_debug)def myfunc(a,b,c):    ret = a+b+c    if is_debug:        print('{}+{}+{}={}'.format(a,b,c,ret))    print('myfunc() called')  myfunc(1,2,3)

>>>before myfunc() called
>>>1+2+3=6
>>>myfunc() called
>>>after myfunc() called

通过让装饰器带参数is_debug控制log的输出.

当is_debug = False时，输出为myfunc里面有一段代码没有log。

>>>before myfunc() called
>>>myfunc() called
>>>after myfunc() called

第八步：让装饰器带类参数

#!/usr/bin/env pythonclass locker:    def __init__(self):        print("locker.__init__() should be not called")    @staticmethod    def acquire():        print("locker.acquire() called")    @staticmethod    def release():        print("locker.release() called")def deco(cls):    def midwrapper(func):        def innerwrapper(*args,**kwargs):            print("before {} called {}.".format(func.__name__,cls.__name__))            cls.acquire()            try:                func(*args,**kwargs)            finally:                cls.release()        return innerwrapper    return midwrapper@deco(locker)def myfunc(*args,**kwargs):    print('myfunc() called')myfunc()

>>>before myfunc called locker.
>>>locker.acquire() called
>>>myfunc() called
>>>locker.release() called
解析：

1. deco(locker) ==>midwrapper
2. myfunc(*args,**kwargs) ==> midwrapper(myfunc) ==>innerwrapper(*args,**kwargs)
3. myfunc() ==> innerwrapper()

第九步：装饰器带多个类参数，即一个函数应用多个装饰器分析起来比较晦涩，我需要先把函数调用顺序学习一下，再来理顺这里的调用关系和返回值的处理方法。

#!/usr/bin/env python            class mylocker:    def __init__(self):        print('mylocker.__init__() called.')    @staticmethod    def acquire():        print('mylocker.acquire() called.')    @staticmethod    def unlock():        print('mylokcer.unlock() called.')class lockerex(mylocker):    @staticmethod    def acquire():        print('lockerex.acquire() called.')    @staticmethod    def unlock():        print('lockerex.unlock() called.')def lockhelper(cls):    def midwrapper(func):        def innerwrapper(*args, **kwargs):            print('before {} called.'.format(func.__name__))            cls.acquire()            try:                func(*args,**kwargs)            finally:                cls.unlock()        return innerwrapper    return midwrapperclass example:    @lockhelper(mylocker)    def myfunc(self):        print('myfunc() called')    @lockhelper(mylocker)    @lockhelper(lockerex)    def myfunc2(self,a,b):        print('{}+{}={}'.format(a,b,a+b))        print('myfunc2() called')        return a+bif __name__ == '__main__':    a = example()    a.myfunc()    print('=='*15)    a.myfunc2(a=1,b=2)

>>>before myfunc called.
>>>mylocker.acquire() called.
>>>myfunc() called
>>>mylokcer.unlock() called.
>>>==============================
>>>before innerwrapper called.
>>>mylocker.acquire() called.
>>>before myfunc2 called.
>>>lockerex.acquire() called.
>>>1+2=3
>>>myfunc2() called
>>>lockerex.unlock() called.
>>>mylokcer.unlock() called.
看到多个装饰器有些头晕了，让我们慢慢一层一层的剥离就很清晰了。分析起来比较晦涩，我需要先把函数调用顺序学习一下，再来理顺这里的调用关系和返回值得

同时，我将code稍微改变了一下，运行结果也大大超出了我的预期，看来我需要好好再深入研究一下。

#!/usr/bin/env python            class mylocker:    def __init__(self):        print('mylocker.__init__() called.')    @staticmethod    def acquire():        print('mylocker.acquire() called.')    @staticmethod    def unlock():        print('mylokcer.unlock() called.')class lockerex(mylocker):    @staticmethod    def acquire():        print('lockerex.acquire() called.')    @staticmethod    def unlock():        print('lockerex.unlock() called.')def lockhelper(cls):    def midwrapper(func):        print('before {} called.'.format(func.__name__))        def innerwrapper(*args, **kwargs):            print('before {} called.'.format(func.__name__))            cls.acquire()            try:                func(*args,**kwargs)            finally:                cls.unlock()        return innerwrapper    return midwrapperclass example:    @lockhelper(mylocker)    def my2func(self):        print('myfunc() called')    @lockhelper(mylocker)    @lockhelper(lockerex)    def myfunc2(self,a,b):        print('{}+{}={}'.format(a,b,a+b))        print('myfunc2() called')        return a+bif __name__ == '__main__':    a = example()    a.myfunc2(a=1,b=2)

这里预留一个疑问，就是如何清晰解析多个装饰器。