问题:实例方法的装饰器可以访问该类吗?

我有一些大致如下的内容。基本上,我需要从在其定义中的实例方法上使用的装饰器访问实例方法的类。

def decorator(view):
    # do something that requires view's class
    print view.im_class
    return view

class ModelA(object):
    @decorator
    def a_method(self):
        # do some stuff
        pass

原样的代码给出:

AttributeError:“函数”对象没有属性“ im_class”

我发现了类似的问题/答案-Python装饰器使函数忘记了它属于Python装饰器中的类Get类 -但它们依赖于一种变通方法,该方法通过在运行时抢夺第一个参数来获取实例。就我而言,我将基于从其类收集的信息来调用该方法,因此我不能等待调用进入。

I have something roughly like the following. Basically I need to access the class of an instance method from a decorator used upon the instance method in its definition.

def decorator(view):
    # do something that requires view's class
    print view.im_class
    return view

class ModelA(object):
    @decorator
    def a_method(self):
        # do some stuff
        pass

The code as-is gives:

AttributeError: ‘function’ object has no attribute ‘im_class’

I found similar question/answers – Python decorator makes function forget that it belongs to a class and Get class in Python decorator – but these rely upon a workaround that grabs the instance at run-time by snatching the first parameter. In my case, I will be calling the method based upon the information gleaned from its class, so I can’t wait for a call to come in.


回答 0

如果您使用的是Python 2.6或更高版本,则可以使用类装饰器,也许是这样的(警告:未经测试的代码)。

def class_decorator(cls):
   for name, method in cls.__dict__.iteritems():
        if hasattr(method, "use_class"):
            # do something with the method and class
            print name, cls
   return cls

def method_decorator(view):
    # mark the method as something that requires view's class
    view.use_class = True
    return view

@class_decorator
class ModelA(object):
    @method_decorator
    def a_method(self):
        # do some stuff
        pass

方法装饰器通过添加“ use_class”属性将方法标记为感兴趣的方法-函数和方法也是对象,因此可以向其附加其他元数据。

创建类之后,类装饰器将遍历所有方法并对已标记的方法执行所需的任何操作。

如果您希望所有方法都受影响,则可以省去方法装饰器,而只使用类装饰器。

If you are using Python 2.6 or later you could use a class decorator, perhaps something like this (warning: untested code).

def class_decorator(cls):
   for name, method in cls.__dict__.iteritems():
        if hasattr(method, "use_class"):
            # do something with the method and class
            print name, cls
   return cls

def method_decorator(view):
    # mark the method as something that requires view's class
    view.use_class = True
    return view

@class_decorator
class ModelA(object):
    @method_decorator
    def a_method(self):
        # do some stuff
        pass

The method decorator marks the method as one that is of interest by adding a “use_class” attribute – functions and methods are also objects, so you can attach additional metadata to them.

After the class has been created the class decorator then goes through all the methods and does whatever is needed on the methods that have been marked.

If you want all the methods to be affected then you could leave out the method decorator and just use the class decorator.


回答 1

从python 3.6开始,您可以使用一种非常简单的方法来完成此任务。该文档指出__set_name__“在创建拥有类的所有者时调用”。这是一个例子:

class class_decorator:
    def __init__(self, fn):
        self.fn = fn

    def __set_name__(self, owner, name):
        # do something with owner, i.e.
        print(f"decorating {self.fn} and using {owner}")
        self.fn.class_name = owner.__name__

        # then replace ourself with the original method
        setattr(owner, name, self.fn)

注意,它在类创建时被调用:

>>> class A:
...     @class_decorator
...     def hello(self, x=42):
...         return x
...
decorating <function A.hello at 0x7f9bedf66bf8> and using <class '__main__.A'>
>>> A.hello
<function __main__.A.hello(self, x=42)>
>>> A.hello.class_name
'A'
>>> a = A()
>>> a.hello()
42

如果您想更多地了解如何创建类,尤其是何时__set_name__调用类,可以参考“创建类对象”文档

Since python 3.6 you can use to accomplish this in a very simple way. The doc states that __set_name__ is “called at the time the owning class owner is created”. Here is an example:

class class_decorator:
    def __init__(self, fn):
        self.fn = fn

    def __set_name__(self, owner, name):
        # do something with owner, i.e.
        print(f"decorating {self.fn} and using {owner}")
        self.fn.class_name = owner.__name__

        # then replace ourself with the original method
        setattr(owner, name, self.fn)

Notice that it gets called at class creation time:

>>> class A:
...     @class_decorator
...     def hello(self, x=42):
...         return x
...
decorating <function A.hello at 0x7f9bedf66bf8> and using <class '__main__.A'>
>>> A.hello
<function __main__.A.hello(self, x=42)>
>>> A.hello.class_name
'A'
>>> a = A()
>>> a.hello()
42

If you want to know more about how classes are created and in particular exactly when __set_name__ is called, you can refer to the documentation on “Creating the class object”.


回答 2

正如其他人指出的那样,在调用装饰器时尚未创建该类。但是,可以用装饰器参数注释函数对象,然后在元类的__new__方法中重新装饰函数。__dict__至少对我来说,您将需要直接访问该函数的属性,func.foo = 1从而导致AttributeError。

As others have pointed out, the class hasn’t been created at the time the decorator is called. However, it’s possible to annotate the function object with the decorator parameters, then re-decorate the function in the metaclass’s __new__ method. You’ll need to access the function’s __dict__ attribute directly, as at least for me, func.foo = 1 resulted in an AttributeError.


回答 3

正如马克所说:

  1. 任何称为BEFORE类的装饰器都将被构建,因此装饰器未知。
  2. 我们可以标记这些方法,并在以后进行任何必要的后处理。
  3. 我们有两个后处理选项:在类定义的末尾或在应用程序运行之前的某个位置自动进行。我更喜欢使用基类的第一种方法,但是您也可以遵循第二种方法。

此代码显示了使用自动后处理可能如何工作:

def expose(**kw):
    "Note that using **kw you can tag the function with any parameters"
    def wrap(func):
        name = func.func_name
        assert not name.startswith('_'), "Only public methods can be exposed"

        meta = func.__meta__ = kw
        meta['exposed'] = True
        return func

    return wrap

class Exposable(object):
    "Base class to expose instance methods"
    _exposable_ = None  # Not necessary, just for pylint

    class __metaclass__(type):
        def __new__(cls, name, bases, state):
            methods = state['_exposed_'] = dict()

            # inherit bases exposed methods
            for base in bases:
                methods.update(getattr(base, '_exposed_', {}))

            for name, member in state.items():
                meta = getattr(member, '__meta__', None)
                if meta is not None:
                    print "Found", name, meta
                    methods[name] = member
            return type.__new__(cls, name, bases, state)

class Foo(Exposable):
    @expose(any='parameter will go', inside='__meta__ func attribute')
    def foo(self):
        pass

class Bar(Exposable):
    @expose(hide=True, help='the great bar function')
    def bar(self):
        pass

class Buzz(Bar):
    @expose(hello=False, msg='overriding bar function')
    def bar(self):
        pass

class Fizz(Foo):
    @expose(msg='adding a bar function')
    def bar(self):
        pass

print('-' * 20)
print("showing exposed methods")
print("Foo: %s" % Foo._exposed_)
print("Bar: %s" % Bar._exposed_)
print("Buzz: %s" % Buzz._exposed_)
print("Fizz: %s" % Fizz._exposed_)

print('-' * 20)
print('examine bar functions')
print("Bar.bar: %s" % Bar.bar.__meta__)
print("Buzz.bar: %s" % Buzz.bar.__meta__)
print("Fizz.bar: %s" % Fizz.bar.__meta__)

输出结果:

Found foo {'inside': '__meta__ func attribute', 'any': 'parameter will go', 'exposed': True}
Found bar {'hide': True, 'help': 'the great bar function', 'exposed': True}
Found bar {'msg': 'overriding bar function', 'hello': False, 'exposed': True}
Found bar {'msg': 'adding a bar function', 'exposed': True}
--------------------
showing exposed methods
Foo: {'foo': <function foo at 0x7f7da3abb398>}
Bar: {'bar': <function bar at 0x7f7da3abb140>}
Buzz: {'bar': <function bar at 0x7f7da3abb0c8>}
Fizz: {'foo': <function foo at 0x7f7da3abb398>, 'bar': <function bar at 0x7f7da3abb488>}
--------------------
examine bar functions
Bar.bar: {'hide': True, 'help': 'the great bar function', 'exposed': True}
Buzz.bar: {'msg': 'overriding bar function', 'hello': False, 'exposed': True}
Fizz.bar: {'msg': 'adding a bar function', 'exposed': True}

请注意,在此示例中:

  1. 我们可以用任意参数注释任何函数。
  2. 每个类都有自己的公开方法。
  3. 我们也可以继承暴露的方法。
  4. 方法可以被覆盖,因为暴露功能已更新。

希望这可以帮助

As Mark suggests:

  1. Any decorator is called BEFORE class is built, so is unknown to the decorator.
  2. We can tag these methods and make any necessary post-process later.
  3. We have two options for post-processing: automatically at the end of the class definition or somewhere before the application will run. I prefer the 1st option using a base class, but you can follow the 2nd approach as well.

This code shows how this may works using automatic post-processing:

def expose(**kw):
    "Note that using **kw you can tag the function with any parameters"
    def wrap(func):
        name = func.func_name
        assert not name.startswith('_'), "Only public methods can be exposed"

        meta = func.__meta__ = kw
        meta['exposed'] = True
        return func

    return wrap

class Exposable(object):
    "Base class to expose instance methods"
    _exposable_ = None  # Not necessary, just for pylint

    class __metaclass__(type):
        def __new__(cls, name, bases, state):
            methods = state['_exposed_'] = dict()

            # inherit bases exposed methods
            for base in bases:
                methods.update(getattr(base, '_exposed_', {}))

            for name, member in state.items():
                meta = getattr(member, '__meta__', None)
                if meta is not None:
                    print "Found", name, meta
                    methods[name] = member
            return type.__new__(cls, name, bases, state)

class Foo(Exposable):
    @expose(any='parameter will go', inside='__meta__ func attribute')
    def foo(self):
        pass

class Bar(Exposable):
    @expose(hide=True, help='the great bar function')
    def bar(self):
        pass

class Buzz(Bar):
    @expose(hello=False, msg='overriding bar function')
    def bar(self):
        pass

class Fizz(Foo):
    @expose(msg='adding a bar function')
    def bar(self):
        pass

print('-' * 20)
print("showing exposed methods")
print("Foo: %s" % Foo._exposed_)
print("Bar: %s" % Bar._exposed_)
print("Buzz: %s" % Buzz._exposed_)
print("Fizz: %s" % Fizz._exposed_)

print('-' * 20)
print('examine bar functions')
print("Bar.bar: %s" % Bar.bar.__meta__)
print("Buzz.bar: %s" % Buzz.bar.__meta__)
print("Fizz.bar: %s" % Fizz.bar.__meta__)

The output yields:

Found foo {'inside': '__meta__ func attribute', 'any': 'parameter will go', 'exposed': True}
Found bar {'hide': True, 'help': 'the great bar function', 'exposed': True}
Found bar {'msg': 'overriding bar function', 'hello': False, 'exposed': True}
Found bar {'msg': 'adding a bar function', 'exposed': True}
--------------------
showing exposed methods
Foo: {'foo': <function foo at 0x7f7da3abb398>}
Bar: {'bar': <function bar at 0x7f7da3abb140>}
Buzz: {'bar': <function bar at 0x7f7da3abb0c8>}
Fizz: {'foo': <function foo at 0x7f7da3abb398>, 'bar': <function bar at 0x7f7da3abb488>}
--------------------
examine bar functions
Bar.bar: {'hide': True, 'help': 'the great bar function', 'exposed': True}
Buzz.bar: {'msg': 'overriding bar function', 'hello': False, 'exposed': True}
Fizz.bar: {'msg': 'adding a bar function', 'exposed': True}

Note that in this example:

  1. We can annotate any function with any arbitrary parameters.
  2. Each class has its own exposed methods.
  3. We can inherit exposed methods as well.
  4. methods can be overriding as exposing feature is updated.

Hope this helps


回答 4

正如Ants所指出的,您不能从类内部获得对该类的引用。但是,如果您希望区分不同的类(而不是操作实际的类类型对象),则可以为每个类传递一个字符串。您还可以使用类样式装饰器将所需的任何其他参数传递给装饰器。

class Decorator(object):
    def __init__(self,decoratee_enclosing_class):
        self.decoratee_enclosing_class = decoratee_enclosing_class
    def __call__(self,original_func):
        def new_function(*args,**kwargs):
            print 'decorating function in ',self.decoratee_enclosing_class
            original_func(*args,**kwargs)
        return new_function


class Bar(object):
    @Decorator('Bar')
    def foo(self):
        print 'in foo'

class Baz(object):
    @Decorator('Baz')
    def foo(self):
        print 'in foo'

print 'before instantiating Bar()'
b = Bar()
print 'calling b.foo()'
b.foo()

印刷品:

before instantiating Bar()
calling b.foo()
decorating function in  Bar
in foo

另外,请参见Bruce Eckel关于装饰器的页面。

As Ants indicated, you can’t get a reference to the class from within the class. However, if you’re interested in distinguishing between different classes ( not manipulating the actual class type object), you can pass a string for each class. You can also pass whatever other parameters you like to the decorator using class-style decorators.

class Decorator(object):
    def __init__(self,decoratee_enclosing_class):
        self.decoratee_enclosing_class = decoratee_enclosing_class
    def __call__(self,original_func):
        def new_function(*args,**kwargs):
            print 'decorating function in ',self.decoratee_enclosing_class
            original_func(*args,**kwargs)
        return new_function


class Bar(object):
    @Decorator('Bar')
    def foo(self):
        print 'in foo'

class Baz(object):
    @Decorator('Baz')
    def foo(self):
        print 'in foo'

print 'before instantiating Bar()'
b = Bar()
print 'calling b.foo()'
b.foo()

Prints:

before instantiating Bar()
calling b.foo()
decorating function in  Bar
in foo

Also, see Bruce Eckel’s page on decorators.


回答 5

什么烧瓶优雅确实是创建一个临时的缓存,它存储的方法,那么它使用别的东西(事实上,瓶将使用注册类register类的方法),以实际包装的方法。

您这次可以使用元类重用此模式,以便可以在导入时包装该方法。

def route(rule, **options):
    """A decorator that is used to define custom routes for methods in
    FlaskView subclasses. The format is exactly the same as Flask's
    `@app.route` decorator.
    """

    def decorator(f):
        # Put the rule cache on the method itself instead of globally
        if not hasattr(f, '_rule_cache') or f._rule_cache is None:
            f._rule_cache = {f.__name__: [(rule, options)]}
        elif not f.__name__ in f._rule_cache:
            f._rule_cache[f.__name__] = [(rule, options)]
        else:
            f._rule_cache[f.__name__].append((rule, options))

        return f

    return decorator

在实际的类上(您可以使用元类来做同样的事情):

@classmethod
def register(cls, app, route_base=None, subdomain=None, route_prefix=None,
             trailing_slash=None):

    for name, value in members:
        proxy = cls.make_proxy_method(name)
        route_name = cls.build_route_name(name)
        try:
            if hasattr(value, "_rule_cache") and name in value._rule_cache:
                for idx, cached_rule in enumerate(value._rule_cache[name]):
                    # wrap the method here

来源:https : //github.com/apiguy/flask-classy/blob/master/flask_classy.py

What flask-classy does is create a temporary cache that it stores on the method, then it uses something else (the fact that Flask will register the classes using a register class method) to actually wraps the method.

You can reuse this pattern, this time using a metaclass so that you can wrap the method at import time.

def route(rule, **options):
    """A decorator that is used to define custom routes for methods in
    FlaskView subclasses. The format is exactly the same as Flask's
    `@app.route` decorator.
    """

    def decorator(f):
        # Put the rule cache on the method itself instead of globally
        if not hasattr(f, '_rule_cache') or f._rule_cache is None:
            f._rule_cache = {f.__name__: [(rule, options)]}
        elif not f.__name__ in f._rule_cache:
            f._rule_cache[f.__name__] = [(rule, options)]
        else:
            f._rule_cache[f.__name__].append((rule, options))

        return f

    return decorator

On the actual class (you could do the same using a metaclass):

@classmethod
def register(cls, app, route_base=None, subdomain=None, route_prefix=None,
             trailing_slash=None):

    for name, value in members:
        proxy = cls.make_proxy_method(name)
        route_name = cls.build_route_name(name)
        try:
            if hasattr(value, "_rule_cache") and name in value._rule_cache:
                for idx, cached_rule in enumerate(value._rule_cache[name]):
                    # wrap the method here

Source: https://github.com/apiguy/flask-classy/blob/master/flask_classy.py


回答 6

问题在于,当调用装饰器时,该类尚不存在。试试这个:

def loud_decorator(func):
    print("Now decorating %s" % func)
    def decorated(*args, **kwargs):
        print("Now calling %s with %s,%s" % (func, args, kwargs))
        return func(*args, **kwargs)
    return decorated

class Foo(object):
    class __metaclass__(type):
        def __new__(cls, name, bases, dict_):
            print("Creating class %s%s with attributes %s" % (name, bases, dict_))
            return type.__new__(cls, name, bases, dict_)

    @loud_decorator
    def hello(self, msg):
        print("Hello %s" % msg)

Foo().hello()

该程序将输出:

Now decorating <function hello at 0xb74d35dc>
Creating class Foo(<type 'object'>,) with attributes {'__module__': '__main__', '__metaclass__': <class '__main__.__metaclass__'>, 'hello': <function decorated at 0xb74d356c>}
Now calling <function hello at 0xb74d35dc> with (<__main__.Foo object at 0xb74ea1ac>, 'World'),{}
Hello World

如您所见,您将必须找出一种不同的方式来做自己想要的事情。

The problem is that when the decorator is called the class doesn’t exist yet. Try this:

def loud_decorator(func):
    print("Now decorating %s" % func)
    def decorated(*args, **kwargs):
        print("Now calling %s with %s,%s" % (func, args, kwargs))
        return func(*args, **kwargs)
    return decorated

class Foo(object):
    class __metaclass__(type):
        def __new__(cls, name, bases, dict_):
            print("Creating class %s%s with attributes %s" % (name, bases, dict_))
            return type.__new__(cls, name, bases, dict_)

    @loud_decorator
    def hello(self, msg):
        print("Hello %s" % msg)

Foo().hello()

This program will output:

Now decorating <function hello at 0xb74d35dc>
Creating class Foo(<type 'object'>,) with attributes {'__module__': '__main__', '__metaclass__': <class '__main__.__metaclass__'>, 'hello': <function decorated at 0xb74d356c>}
Now calling <function hello at 0xb74d35dc> with (<__main__.Foo object at 0xb74ea1ac>, 'World'),{}
Hello World

As you see, you are going to have to figure out a different way to do what you want.


回答 7

这是一个简单的例子:

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

Here’s a simple 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

这是一个古老的问题,但遇到了金星。 http://venusian.readthedocs.org/en/latest/

它似乎具有装饰方法的能力,并且可以同时使您访问类和方法。请注意,调用setattr(ob, wrapped.__name__, decorated)不是使用金星的典型方法,并且在一定程度上会破坏目的。

无论哪种方式,下面的示例都是完整的,应该可以运行。

import sys
from functools import wraps
import venusian

def logged(wrapped):
    def callback(scanner, name, ob):
        @wraps(wrapped)
        def decorated(self, *args, **kwargs):
            print 'you called method', wrapped.__name__, 'on class', ob.__name__
            return wrapped(self, *args, **kwargs)
        print 'decorating', '%s.%s' % (ob.__name__, wrapped.__name__)
        setattr(ob, wrapped.__name__, decorated)
    venusian.attach(wrapped, callback)
    return wrapped

class Foo(object):
    @logged
    def bar(self):
        print 'bar'

scanner = venusian.Scanner()
scanner.scan(sys.modules[__name__])

if __name__ == '__main__':
    t = Foo()
    t.bar()

This is an old question but came across venusian. http://venusian.readthedocs.org/en/latest/

It seems to have the ability to decorate methods and give you access to both the class and the method while doing so. Note tht calling setattr(ob, wrapped.__name__, decorated) is not the typical way of using venusian and somewhat defeats the purpose.

Either way… the example below is complete and should run.

import sys
from functools import wraps
import venusian

def logged(wrapped):
    def callback(scanner, name, ob):
        @wraps(wrapped)
        def decorated(self, *args, **kwargs):
            print 'you called method', wrapped.__name__, 'on class', ob.__name__
            return wrapped(self, *args, **kwargs)
        print 'decorating', '%s.%s' % (ob.__name__, wrapped.__name__)
        setattr(ob, wrapped.__name__, decorated)
    venusian.attach(wrapped, callback)
    return wrapped

class Foo(object):
    @logged
    def bar(self):
        print 'bar'

scanner = venusian.Scanner()
scanner.scan(sys.modules[__name__])

if __name__ == '__main__':
    t = Foo()
    t.bar()

回答 9

装饰器代码运行时,函数不知道它是否是定义点的方法。仅当通过类/实例标识符访问它时,它才可以知道其类/实例。为了克服此限制,您可以按描述符对象进行修饰,以将实际修饰代码延迟到访问/调用时间为止:

class decorated(object):
    def __init__(self, func, type_=None):
        self.func = func
        self.type = type_

    def __get__(self, obj, type_=None):
        func = self.func.__get__(obj, type_)
        print('accessed %s.%s' % (type_.__name__, func.__name__))
        return self.__class__(func, type_)

    def __call__(self, *args, **kwargs):
        name = '%s.%s' % (self.type.__name__, self.func.__name__)
        print('called %s with args=%s kwargs=%s' % (name, args, kwargs))
        return self.func(*args, **kwargs)

这使您可以修饰单个(静态|类)方法:

class Foo(object):
    @decorated
    def foo(self, a, b):
        pass

    @decorated
    @staticmethod
    def bar(a, b):
        pass

    @decorated
    @classmethod
    def baz(cls, a, b):
        pass

class Bar(Foo):
    pass

现在您可以使用装饰器代码进行内省…

>>> Foo.foo
accessed Foo.foo
>>> Foo.bar
accessed Foo.bar
>>> Foo.baz
accessed Foo.baz
>>> Bar.foo
accessed Bar.foo
>>> Bar.bar
accessed Bar.bar
>>> Bar.baz
accessed Bar.baz

…以及更改功能行为:

>>> Foo().foo(1, 2)
accessed Foo.foo
called Foo.foo with args=(1, 2) kwargs={}
>>> Foo.bar(1, b='bcd')
accessed Foo.bar
called Foo.bar with args=(1,) kwargs={'b': 'bcd'}
>>> Bar.baz(a='abc', b='bcd')
accessed Bar.baz
called Bar.baz with args=() kwargs={'a': 'abc', 'b': 'bcd'}

Function doesn’t know whether it’s a method at definition point, when the decorator code runs. Only when it’s accessed via class/instance identifier it may know its class/instance. To overcome this limitation, you may decorate by descriptor object to delay actual decorating code until access/call time:

class decorated(object):
    def __init__(self, func, type_=None):
        self.func = func
        self.type = type_

    def __get__(self, obj, type_=None):
        func = self.func.__get__(obj, type_)
        print('accessed %s.%s' % (type_.__name__, func.__name__))
        return self.__class__(func, type_)

    def __call__(self, *args, **kwargs):
        name = '%s.%s' % (self.type.__name__, self.func.__name__)
        print('called %s with args=%s kwargs=%s' % (name, args, kwargs))
        return self.func(*args, **kwargs)

This allows you to decorate individual (static|class) methods:

class Foo(object):
    @decorated
    def foo(self, a, b):
        pass

    @decorated
    @staticmethod
    def bar(a, b):
        pass

    @decorated
    @classmethod
    def baz(cls, a, b):
        pass

class Bar(Foo):
    pass

Now you can use decorator code for introspection…

>>> Foo.foo
accessed Foo.foo
>>> Foo.bar
accessed Foo.bar
>>> Foo.baz
accessed Foo.baz
>>> Bar.foo
accessed Bar.foo
>>> Bar.bar
accessed Bar.bar
>>> Bar.baz
accessed Bar.baz

…and for changing function behavior:

>>> Foo().foo(1, 2)
accessed Foo.foo
called Foo.foo with args=(1, 2) kwargs={}
>>> Foo.bar(1, b='bcd')
accessed Foo.bar
called Foo.bar with args=(1,) kwargs={'b': 'bcd'}
>>> Bar.baz(a='abc', b='bcd')
accessed Bar.baz
called Bar.baz with args=() kwargs={'a': 'abc', 'b': 'bcd'}

回答 10

正如其他答案所指出的那样,decorator是一种函数式的东西,由于尚未创建该类,因此您无法访问此方法所属的类。但是,完全可以使用装饰器“标记”函数,然后再使用元类技术来处理该方法,因为在此__new__阶段,该类已由其元类创建。

这是一个简单的示例:

我们@field用来将方法标记为一个特殊字段,并在元类中对其进行处理。

def field(fn):
    """Mark the method as an extra field"""
    fn.is_field = True
    return fn

class MetaEndpoint(type):
    def __new__(cls, name, bases, attrs):
        fields = {}
        for k, v in attrs.items():
            if inspect.isfunction(v) and getattr(k, "is_field", False):
                fields[k] = v
        for base in bases:
            if hasattr(base, "_fields"):
                fields.update(base._fields)
        attrs["_fields"] = fields

        return type.__new__(cls, name, bases, attrs)

class EndPoint(metaclass=MetaEndpoint):
    pass


# Usage

class MyEndPoint(EndPoint):
    @field
    def foo(self):
        return "bar"

e = MyEndPoint()
e._fields  # {"foo": ...}

As other answers have pointed out, decorator is an function-ish thing, you can not access the class which this method belongs to since the class has not been created yet. However, it’s totally ok to use a decorator to “mark” the function and then use metaclass techniques to deal with the method later, because at the __new__ stage, the class has been created by its metaclass.

Here is a simple example:

We use @field to mark the method as a special field and deal with it in metaclass.

def field(fn):
    """Mark the method as an extra field"""
    fn.is_field = True
    return fn

class MetaEndpoint(type):
    def __new__(cls, name, bases, attrs):
        fields = {}
        for k, v in attrs.items():
            if inspect.isfunction(v) and getattr(k, "is_field", False):
                fields[k] = v
        for base in bases:
            if hasattr(base, "_fields"):
                fields.update(base._fields)
        attrs["_fields"] = fields

        return type.__new__(cls, name, bases, attrs)

class EndPoint(metaclass=MetaEndpoint):
    pass


# Usage

class MyEndPoint(EndPoint):
    @field
    def foo(self):
        return "bar"

e = MyEndPoint()
e._fields  # {"foo": ...}

回答 11

您将可以访问装饰器应返回的装饰方法中在其上调用该方法的对象的类。像这样:

def decorator(method):
    # do something that requires view's class
    def decorated(self, *args, **kwargs):
        print 'My class is %s' % self.__class__
        method(self, *args, **kwargs)
    return decorated

使用您的ModelA类,这是做什么的:

>>> obj = ModelA()
>>> obj.a_method()
My class is <class '__main__.ModelA'>

You will have access to the class of the object on which the method is being called in the decorated method that your decorator should return. Like so:

def decorator(method):
    # do something that requires view's class
    def decorated(self, *args, **kwargs):
        print 'My class is %s' % self.__class__
        method(self, *args, **kwargs)
    return decorated

Using your ModelA class, here is what this does:

>>> obj = ModelA()
>>> obj.a_method()
My class is <class '__main__.ModelA'>

回答 12

我只想添加我的示例,因为它包含了从装饰方法访问类时可以想到的所有内容。它使用@tyrion建议的描述符。装饰器可以接受参数并将其传递给描述符。它可以处理类中的方法,也可以处理没有类的函数。

import datetime as dt
import functools

def dec(arg1):
    class Timed(object):
        local_arg = arg1
        def __init__(self, f):
            functools.update_wrapper(self, f)
            self.func = f

        def __set_name__(self, owner, name):
            # doing something fancy with owner and name
            print('owner type', owner.my_type())
            print('my arg', self.local_arg)

        def __call__(self, *args, **kwargs):
            start = dt.datetime.now()
            ret = self.func(*args, **kwargs)
            time = dt.datetime.now() - start
            ret["time"] = time
            return ret
        
        def __get__(self, instance, owner):
            from functools import partial
            return partial(self.__call__, instance)
    return Timed

class Test(object):
    def __init__(self):
        super(Test, self).__init__()

    @classmethod
    def my_type(cls):
        return 'owner'

    @dec(arg1='a')
    def decorated(self, *args, **kwargs):
        print(self)
        print(args)
        print(kwargs)
        return dict()

    def call_deco(self):
        self.decorated("Hello", world="World")

@dec(arg1='a function')
def another(*args, **kwargs):
    print(args)
    print(kwargs)
    return dict()

if __name__ == "__main__":
    t = Test()
    ret = t.call_deco()
    another('Ni hao', world="shi jie")
    

I just want to add my example since it has all the things I could think of for accessing the class from the decorated method. It uses a descriptor as @tyrion suggests. The decorator can take arguments and passes them to the descriptor. It can deal with both a method in a class or a function without a class.

import datetime as dt
import functools

def dec(arg1):
    class Timed(object):
        local_arg = arg1
        def __init__(self, f):
            functools.update_wrapper(self, f)
            self.func = f

        def __set_name__(self, owner, name):
            # doing something fancy with owner and name
            print('owner type', owner.my_type())
            print('my arg', self.local_arg)

        def __call__(self, *args, **kwargs):
            start = dt.datetime.now()
            ret = self.func(*args, **kwargs)
            time = dt.datetime.now() - start
            ret["time"] = time
            return ret
        
        def __get__(self, instance, owner):
            from functools import partial
            return partial(self.__call__, instance)
    return Timed

class Test(object):
    def __init__(self):
        super(Test, self).__init__()

    @classmethod
    def my_type(cls):
        return 'owner'

    @dec(arg1='a')
    def decorated(self, *args, **kwargs):
        print(self)
        print(args)
        print(kwargs)
        return dict()

    def call_deco(self):
        self.decorated("Hello", world="World")

@dec(arg1='a function')
def another(*args, **kwargs):
    print(args)
    print(kwargs)
    return dict()

if __name__ == "__main__":
    t = Test()
    ret = t.call_deco()
    another('Ni hao', world="shi jie")
    

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