import functools


class Example:

    def wrapper(func):
        @functools.wraps(func)
        def wrap(self, *args, **kwargs):
            print("inside wrap")
            return func(self, *args, **kwargs)
        return wrap

    @wrapper
    def method(self):
        print("METHOD")

    wrapper = staticmethod(wrapper)


e = Example()
e.method()

我在一些调试情况下使用这种类型的装饰器，它允许通过装饰来重写类属性，而不必找到调用函数。

class myclass(object):
    def __init__(self):
        self.property = "HELLO"

    @adecorator(property="GOODBYE")
    def method(self):
        print self.property

下面是装饰器代码

class adecorator (object):
    def __init__ (self, *args, **kwargs):
        # store arguments passed to the decorator
        self.args = args
        self.kwargs = kwargs

    def __call__(self, func):
        def newf(*args, **kwargs):

            #the 'self' for a method function is passed as args[0]
            slf = args[0]

            # replace and store the attributes
            saved = {}
            for k,v in self.kwargs.items():
                if hasattr(slf, k):
                    saved[k] = getattr(slf,k)
                    setattr(slf, k, v)

            # call the method
            ret = func(*args, **kwargs)

            #put things back
            for k,v in saved.items():
                setattr(slf, k, v)

            return ret
        newf.__doc__ = func.__doc__
        return newf 

注意:因为我使用了一个类装饰器，所以你需要使用@adecorator()来装饰函数，即使你没有向装饰器类构造函数传递任何参数。

我在研究一个非常相似的问题时发现了这个问题。我的解决办法是把问题分成两部分。首先，您需要捕获希望与类方法关联的数据。在这种情况下，handler_for将Unix命令与该命令输出的处理程序相关联。

class OutputAnalysis(object):
    "analyze the output of diagnostic commands"
    def handler_for(name):
        "decorator to associate a function with a command"
        def wrapper(func):
            func.handler_for = name
            return func
        return wrapper
    # associate mount_p with 'mount_-p.txt'
    @handler_for('mount -p')
    def mount_p(self, slurped):
        pass

现在我们已经将一些数据与每个类方法关联起来，我们需要收集这些数据并将其存储在一个类属性中。

OutputAnalysis.cmd_handler = {}
for value in OutputAnalysis.__dict__.itervalues():
    try:
        OutputAnalysis.cmd_handler[value.handler_for] = value
    except AttributeError:
        pass

你可以装饰装饰器:

import decorator

class Test(object):
    @decorator.decorator
    def _decorator(foo, self):
        foo(self)

    @_decorator
    def bar(self):
        pass

以下是对迈克尔•施佩尔的回答的进一步扩展:

一个实例方法装饰器，它接受参数并作用于带有参数和返回值的函数。

class Test(object):
    "Prints if x == y. Throws an error otherwise."
    def __init__(self, x):
        self.x = x

    def _outer_decorator(y):
        def _decorator(foo):
            def magic(self, *args, **kwargs) :
                print("start magic")
                if self.x == y:
                    return foo(self, *args, **kwargs)
                else:
                    raise ValueError("x ({}) != y ({})".format(self.x, y))
                print("end magic")
            return magic

        return _decorator

    @_outer_decorator(y=3)
    def bar(self, *args, **kwargs) :
        print("normal call")
        print("args: {}".format(args))
        print("kwargs: {}".format(kwargs))

        return 27

然后

In [2]:

    test = Test(3)
    test.bar(
        13,
        'Test',
        q=9,
        lollipop=[1,2,3]
    )
    ​
    start magic
    normal call
    args: (13, 'Test')
    kwargs: {'q': 9, 'lollipop': [1, 2, 3]}
Out[2]:
    27
In [3]:

    test = Test(4)
    test.bar(
        13,
        'Test',
        q=9,
        lollipop=[1,2,3]
    )
    ​
    start magic
    ---------------------------------------------------------------------------
    ValueError                                Traceback (most recent call last)
    <ipython-input-3-576146b3d37e> in <module>()
          4     'Test',
          5     q=9,
    ----> 6     lollipop=[1,2,3]
          7 )

    <ipython-input-1-428f22ac6c9b> in magic(self, *args, **kwargs)
         11                     return foo(self, *args, **kwargs)
         12                 else:
    ---> 13                     raise ValueError("x ({}) != y ({})".format(self.x, y))
         14                 print("end magic")
         15             return magic

    ValueError: x (4) != y (3)

装饰器似乎更适合修改整个对象(包括函数对象)的功能，而不是对象方法的功能，后者通常依赖于实例属性。例如:

def mod_bar(cls):
    # returns modified class

    def decorate(fcn):
        # returns decorated function

        def new_fcn(self):
            print self.start_str
            print fcn(self)
            print self.end_str

        return new_fcn

    cls.bar = decorate(cls.bar)
    return cls

@mod_bar
class Test(object):
    def __init__(self):
        self.start_str = "starting dec"
        self.end_str = "ending dec" 

    def bar(self):
        return "bar"

输出结果为:

>>> import Test
>>> a = Test()
>>> a.bar()
starting dec
bar
ending dec