类中的Python装饰器

问题:类中的Python装饰器

可以这样写吗:

class Test(object):
    def _decorator(self, foo):
        foo()

    @self._decorator
    def bar(self):
        pass

这将失败:@self中的self未知

我也尝试过:

@Test._decorator(self)

也会失败:测试未知

我想在装饰器中临时更改一些实例变量,然后运行装饰的方法,然后再将其更改回。

Can one write something like:

class Test(object):
    def _decorator(self, foo):
        foo()

    @self._decorator
    def bar(self):
        pass

This fails: self in @self is unknown

I also tried:

@Test._decorator(self)

which also fails: Test unknown

I would like to temporarily change some instance variables in the decorator and then run the decorated method, before changing them back.


回答 0

这样的事情会满足您的需求吗?

class Test(object):
    def _decorator(foo):
        def magic( self ) :
            print "start magic"
            foo( self )
            print "end magic"
        return magic

    @_decorator
    def bar( self ) :
        print "normal call"

test = Test()

test.bar()

这样可以避免调用self来访问装饰器,并将其作为常规方法隐藏在类命名空间中。

>>> import stackoverflow
>>> test = stackoverflow.Test()
>>> test.bar()
start magic
normal call
end magic
>>> 

编辑以回答评论中的问题:

如何在另一个类中使用隐藏的装饰器

class Test(object):
    def _decorator(foo):
        def magic( self ) :
            print "start magic"
            foo( self )
            print "end magic"
        return magic

    @_decorator
    def bar( self ) :
        print "normal call"

    _decorator = staticmethod( _decorator )

class TestB( Test ):
    @Test._decorator
    def bar( self ):
        print "override bar in"
        super( TestB, self ).bar()
        print "override bar out"

print "Normal:"
test = Test()
test.bar()
print

print "Inherited:"
b = TestB()
b.bar()
print

输出:

Normal:
start magic
normal call
end magic

Inherited:
start magic
override bar in
start magic
normal call
end magic
override bar out
end magic

Would something like this do what you need?

class Test(object):
    def _decorator(foo):
        def magic( self ) :
            print "start magic"
            foo( self )
            print "end magic"
        return magic

    @_decorator
    def bar( self ) :
        print "normal call"

test = Test()

test.bar()

This avoids the call to self to access the decorator and leaves it hidden in the class namespace as a regular method.

>>> import stackoverflow
>>> test = stackoverflow.Test()
>>> test.bar()
start magic
normal call
end magic
>>> 

edited to answer question in comments:

How to use the hidden decorator in another class

class Test(object):
    def _decorator(foo):
        def magic( self ) :
            print "start magic"
            foo( self )
            print "end magic"
        return magic

    @_decorator
    def bar( self ) :
        print "normal call"

    _decorator = staticmethod( _decorator )

class TestB( Test ):
    @Test._decorator
    def bar( self ):
        print "override bar in"
        super( TestB, self ).bar()
        print "override bar out"

print "Normal:"
test = Test()
test.bar()
print

print "Inherited:"
b = TestB()
b.bar()
print

Output:

Normal:
start magic
normal call
end magic

Inherited:
start magic
override bar in
start magic
normal call
end magic
override bar out
end magic

回答 1

您想做的事是不可能的。例如,下面的代码是否有效:

class Test(object):

    def _decorator(self, foo):
        foo()

    def bar(self):
        pass
    bar = self._decorator(bar)

当然,它是无效的,因为那时self还没有定义。同样的道理,Test直到定义了类本身(在过程中)才被定义。我正在向您显示此代码段,因为这是您的装饰程序段所转换的内容。

因此,正如您所看到的那样,实际上不可能在这样的装饰器中访问实例,因为装饰器是在定义它们所附加的函数/方法的过程中而不是在实例化过程中应用的。

如果您需要类级别的访问权限,请尝试以下操作:

class Test(object):

    @classmethod
    def _decorator(cls, foo):
        foo()

    def bar(self):
        pass
Test.bar = Test._decorator(Test.bar)

What you’re wanting to do isn’t possible. Take, for instance, whether or not the code below looks valid:

class Test(object):

    def _decorator(self, foo):
        foo()

    def bar(self):
        pass
    bar = self._decorator(bar)

It, of course, isn’t valid since self isn’t defined at that point. The same goes for Test as it won’t be defined until the class itself is defined (which its in the process of). I’m showing you this code snippet because this is what your decorator snippet transforms into.

So, as you can see, accessing the instance in a decorator like that isn’t really possible since decorators are applied during the definition of whatever function/method they are attached to and not during instantiation.

If you need class-level access, try this:

class Test(object):

    @classmethod
    def _decorator(cls, foo):
        foo()

    def bar(self):
        pass
Test.bar = Test._decorator(Test.bar)

回答 2

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()
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()

回答 3

我在某些调试情况下使用这种类型的装饰器,它允许通过装饰来覆盖类属性,而无需找到调用函数。

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

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

这是装饰代码

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:因为我使用了类装饰器,所以即使您没有将任何参数传递给装饰器类构造函数,也需要使用@adecorator()放在方括号中来装饰函数。

I use this type of decorator in some debugging situations, it allows overriding class properties by decorating, without having to find the calling function.

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

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

Here is the decorator code

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 

Note: because I’ve used a class decorator you’ll need to use @adecorator() with the brackets on to decorate functions, even if you don’t pass any arguments to the decorator class constructor.


回答 4

这是selfdecorator同一类内部定义的内部访问(并已使用)的一种方法:

class Thing(object):
    def __init__(self, name):
        self.name = name

    def debug_name(function):
        def debug_wrapper(*args):
            self = args[0]
            print 'self.name = ' + self.name
            print 'running function {}()'.format(function.__name__)
            function(*args)
            print 'self.name = ' + self.name
        return debug_wrapper

    @debug_name
    def set_name(self, new_name):
        self.name = new_name

输出(在上测试Python 2.7.10):

>>> a = Thing('A')
>>> a.name
'A'
>>> a.set_name('B')
self.name = A
running function set_name()
self.name = B
>>> a.name
'B'

上面的示例很愚蠢,但是可以。

This is one way to access(and have used) self from inside a decorator defined inside the same class:

class Thing(object):
    def __init__(self, name):
        self.name = name

    def debug_name(function):
        def debug_wrapper(*args):
            self = args[0]
            print 'self.name = ' + self.name
            print 'running function {}()'.format(function.__name__)
            function(*args)
            print 'self.name = ' + self.name
        return debug_wrapper

    @debug_name
    def set_name(self, new_name):
        self.name = new_name

Output (tested on Python 2.7.10):

>>> a = Thing('A')
>>> a.name
'A'
>>> a.set_name('B')
self.name = A
running function set_name()
self.name = B
>>> a.name
'B'

The example above is silly, but it works.


回答 5

我在研究一个非常相似的问题时发现了这个问题。我的解决方案是将问题分为两部分。首先,您需要捕获要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,我们已将某些数据与每个类方法相关联,我们需要收集该数据并将其存储在class属性中。

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

I found this question while researching a very similar problem. My solution is to split the problem into two parts. First, you need to capture the data that you want to associate with the class methods. In this case, handler_for will associate a Unix command with handler for that command’s output.

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

Now that we’ve associated some data with each class method, we need to gather that data and store it in a class attribute.

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

回答 6

这是迈克尔·斯佩尔(Michael Speer)的答案的扩展,以进一步采取一些措施:

一个实例方法装饰器,它接受参数并通过参数和返回值作用于函数。

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)

Here’s an expansion on Michael Speer’s answer to take it a few steps further:

An instance method decorator which takes arguments and acts on a function with arguments and a return value.

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

And then

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)

回答 7

装饰器似乎更适合于修改整个对象(包括函数对象)的功能,而不是通常取决于实例属性的对象方法的功能。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"

输出为:

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

Decorators seem better suited to modify the functionality of an entire object (including function objects) versus the functionality of an object method which in general will depend on instance attributes. For example:

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"

The output is:

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

回答 8

您可以装饰装饰器:

import decorator

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

    @_decorator
    def bar(self):
        pass

You can decorate the decorator:

import decorator

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

    @_decorator
    def bar(self):
        pass

回答 9

我有一个可以帮助的装饰器实施

    import functools
    import datetime


    class Decorator(object):

        def __init__(self):
            pass


        def execution_time(func):

            @functools.wraps(func)
            def wrap(self, *args, **kwargs):

                """ Wrapper Function """

                start = datetime.datetime.now()
                Tem = func(self, *args, **kwargs)
                end = datetime.datetime.now()
                print("Exection Time:{}".format(end-start))
                return Tem

            return wrap


    class Test(Decorator):

        def __init__(self):
            self._MethodName = Test.funca.__name__

        @Decorator.execution_time
        def funca(self):
            print("Running Function : {}".format(self._MethodName))
            return True


    if __name__ == "__main__":
        obj = Test()
        data = obj.funca()
        print(data)

I have a Implementation of Decorators that Might Help

    import functools
    import datetime


    class Decorator(object):

        def __init__(self):
            pass


        def execution_time(func):

            @functools.wraps(func)
            def wrap(self, *args, **kwargs):

                """ Wrapper Function """

                start = datetime.datetime.now()
                Tem = func(self, *args, **kwargs)
                end = datetime.datetime.now()
                print("Exection Time:{}".format(end-start))
                return Tem

            return wrap


    class Test(Decorator):

        def __init__(self):
            self._MethodName = Test.funca.__name__

        @Decorator.execution_time
        def funca(self):
            print("Running Function : {}".format(self._MethodName))
            return True


    if __name__ == "__main__":
        obj = Test()
        data = obj.funca()
        print(data)

回答 10

在内部阶级中宣布。此解决方案非常可靠,建议使用。

class Test(object):
    class Decorators(object):
    @staticmethod
    def decorator(foo):
        def magic(self, *args, **kwargs) :
            print("start magic")
            foo(self, *args, **kwargs)
            print("end magic")
        return magic

    @Decorators.decorator
    def bar( self ) :
        print("normal call")

test = Test()

test.bar()

结果:

>>> test = Test()
>>> test.bar()
start magic
normal call
end magic
>>> 

Declare in inner class. This solution is pretty solid and recommended.

class Test(object):
    class Decorators(object):
    @staticmethod
    def decorator(foo):
        def magic(self, *args, **kwargs) :
            print("start magic")
            foo(self, *args, **kwargs)
            print("end magic")
        return magic

    @Decorators.decorator
    def bar( self ) :
        print("normal call")

test = Test()

test.bar()

The result:

>>> test = Test()
>>> test.bar()
start magic
normal call
end magic
>>>