实例方法的python装饰器可以访问该类吗?

如果您使用的是Python2.6或更高版本,则可以使用类装饰器,可能类似于这样(警告:未测试的代码)。

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decorator通过添加一个“use_class”属性将该方法标记为感兴趣的方法-函数和方法也是对象,因此可以将其他元数据附加到它们。

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。

如果您希望所有的方法都受到影响,那么您可以省略方法decorator,而只使用类decorator。

正如其他人指出的,在调用decorator时还没有创建类。 然而 ,可以用decorator参数注释函数对象,然后在元类的 __new__ 方法。您需要访问函数的 __dict__ 直接的属性,至少对我来说, func.foo = 1 导致属性错误。

正如ants所指出的,不能从类中获取对类的引用。但是,如果您有兴趣区分不同的类(不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的decorators将您喜欢的任何其他参数传递给decorator。

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

也, see Bruce Eckel's page on decorators.

问题是,当调用decorator时,类还不存在。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()

此程序将输出:

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

如你所见,你必须想出一种不同的方法来做你想做的事。

下面是一个简单的例子:

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

什么 flask-classy 创建一个存储在方法上的临时缓存,然后使用其他东西(flask将使用 register 类方法)来实际包装方法。

您可以重用此模式,这次使用元类,以便在导入时包装方法。

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(可以使用元类执行相同的操作):

@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

正如马克所说:

1. 在生成类之前调用任何decorator,因此decorator不知道。
2. 我们可以 标签 这些方法和任何必要的后期处理。
3. 对于后处理,我们有两个选项:在类定义的末尾或应用程序运行之前的某个地方自动执行。我更喜欢使用基类的第一个选项,但是您也可以遵循第二个方法。

此代码显示了使用自动后处理时的工作原理:

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__)

产量:

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}

注意,在本例中:

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. 我们也可以继承公开的方法。
4. 方法可以在公开功能更新时重写。

希望这有帮助

这是一个老问题,但遇到了金星。 http://venusian.readthedocs.org/en/latest/

它似乎能够修饰方法,并在这样做的同时让您访问类和方法。 通知电话 setattr(ob, wrapped.__name__, decorated) 不是典型的使用金星的方法,有点违背了目的。

不管怎样…下面的示例已完成并应运行。

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()

自python 3.6以来,您可以使用 object.__set_name__ 以一种非常简单的方式来完成这个任务。医生说 __set_name__ 是“在拥有类的时候调用的 主人 “创造”。 下面是一个例子:

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

如果你想知道更多关于类是如何创建的,特别是什么时候 第二章 是的,你可以参考 documentation on "Creating the class object" .

您将有权访问在装饰方法中调用该方法的对象的类,装饰器应返回该类。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modela类,可以执行以下操作:

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

函数不知道在decorator代码运行时,它在定义点是否是一个方法。只有通过类/实例标识符访问它时,它才可能知道它的类/实例。要克服此限制,可以通过描述符对象进行修饰,以将实际的修饰代码延迟到访问/调用时间:

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)

这允许您装饰单个(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decorator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

…对于改变函数行为:

>>> 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'}