什么是甲状腺?它们用于什么?


当前回答

除了发布的答案,我可以说,一个甲状腺可以定义一个类的行为,所以,你可以明确设置你的甲状腺,每当Python获得一个关键词类,然后它开始搜索甲状腺,如果它没有找到 - 默认甲状腺类型用于创建一个类的对象,使用 __metaclass__属性,你可以设置你的甲状腺类:

class MyClass:
   __metaclass__ = type
   # write here other method
   # write here one more method

print(MyClass.__metaclass__)

它将产生这样的产量:

class 'type'

当然,你可以创建自己的金属类来定义使用你的类创建的任何类的行为。

要做到这一点,您的默认金属类型类必须继承,因为这是主要金属类:

class MyMetaClass(type):
   __metaclass__ = type
   # you can write here any behaviour you want

class MyTestClass:
   __metaclass__ = MyMetaClass

Obj = MyTestClass()
print(Obj.__metaclass__)
print(MyMetaClass.__metaclass__)

产量将是:

class '__main__.MyMetaClass'
class 'type'

其他回答

# define a class
class SomeClass(object):
    # ...
    # some definition here ...
    # ...

# create an instance of it
instance = SomeClass()

# then call the object as if it's a function
result = instance('foo', 'bar')

class SomeClass(object):
    # ...
    # some definition here ...
    # ...

    def __call__(self, foo, bar):
        return bar + foo

但是,正如我们从以前的答案中看到的那样,一个类本身就是一个金属类的例子,所以当我们使用这个类作为一个金属类(即当我们创建一个例子时),我们实际上称它为金属类的 __call__() 方法。

class Meta_1(type):
    def __call__(cls):
        print "Meta_1.__call__() before creating an instance of ", cls
        instance = super(Meta_1, cls).__call__()
        print "Meta_1.__call__() about to return instance."
        return instance

这是一个使用这个MetaClass的班级。

class Class_1(object):

    __metaclass__ = Meta_1

    def __new__(cls):
        print "Class_1.__new__() before creating an instance."
        instance = super(Class_1, cls).__new__(cls)
        print "Class_1.__new__() about to return instance."
        return instance

    def __init__(self):
        print "entering Class_1.__init__() for instance initialization."
        super(Class_1,self).__init__()
        print "exiting Class_1.__init__()."

现在,让我们创建一个类_1的例子。

instance = Class_1()
# Meta_1.__call__() before creating an instance of <class '__main__.Class_1'>.
# Class_1.__new__() before creating an instance.
# Class_1.__new__() about to return instance.
# entering Class_1.__init__() for instance initialization.
# exiting Class_1.__init__().
# Meta_1.__call__() about to return instance.

class type:
    def __call__(cls, *args, **kwarg):

        # ... maybe a few things done to cls here

        # then we call __new__() on the class to create an instance
        instance = cls.__new__(cls, *args, **kwargs)

        # ... maybe a few things done to the instance here

        # then we initialize the instance with its __init__() method
        instance.__init__(*args, **kwargs)

        # ... maybe a few more things done to instance here

        # then we return it
        return instance

从上述情况下,它表明,MetaClass的 __call__() 还有机会决定是否会最终对 Class_1.__new__() 或 Class_1.__init__() 进行呼叫。在执行过程中,它实际上可以返回没有被这些方法触摸的对象。

class Meta_2(type):
    singletons = {}

    def __call__(cls, *args, **kwargs):
        if cls in Meta_2.singletons:
            # we return the only instance and skip a call to __new__()
            # and __init__()
            print ("{} singleton returning from Meta_2.__call__(), "
                   "skipping creation of new instance.".format(cls))
            return Meta_2.singletons[cls]

        # else if the singleton isn't present we proceed as usual
        print "Meta_2.__call__() before creating an instance."
        instance = super(Meta_2, cls).__call__(*args, **kwargs)
        Meta_2.singletons[cls] = instance
        print "Meta_2.__call__() returning new instance."
        return instance

class Class_2(object):

    __metaclass__ = Meta_2

    def __new__(cls, *args, **kwargs):
        print "Class_2.__new__() before creating instance."
        instance = super(Class_2, cls).__new__(cls)
        print "Class_2.__new__() returning instance."
        return instance

    def __init__(self, *args, **kwargs):
        print "entering Class_2.__init__() for initialization."
        super(Class_2, self).__init__()
        print "exiting Class_2.__init__()."

让我们来看看在重复试图创建类型Class_2的对象时会发生什么。

a = Class_2()
# Meta_2.__call__() before creating an instance.
# Class_2.__new__() before creating instance.
# Class_2.__new__() returning instance.
# entering Class_2.__init__() for initialization.
# exiting Class_2.__init__().
# Meta_2.__call__() returning new instance.

b = Class_2()
# <class '__main__.Class_2'> singleton returning from Meta_2.__call__(), skipping creation of new instance.

c = Class_2()
# <class '__main__.Class_2'> singleton returning from Meta_2.__call__(), skipping creation of new instance.

a is b is c # True

什么是Metaclasses?你用它们用于什么?

>>> Class(...)
instance

>>> Metaclass(...)
Class

>>> type('Foo', (object,), {}) # requires a name, bases, and a namespace
<class '__main__.Foo'>

每当你创建一个类时,你都会使用一个类型:

class Foo(object): 
    'demo'

>>> Foo
<class '__main__.Foo'>
>>> isinstance(Foo, type), isinstance(Foo, object)
(True, True)

name = 'Foo'
bases = (object,)
namespace = {'__doc__': 'demo'}
Foo = type(name, bases, namespace)

>>> Foo.__dict__
dict_proxy({'__dict__': <attribute '__dict__' of 'Foo' objects>, 
'__module__': '__main__', '__weakref__': <attribute '__weakref__' 
of 'Foo' objects>, '__doc__': 'demo'})

(在 __dict__: __module__ 类的内容上有一个侧笔记,因为类必须知道它们在哪里定义,而 __dict__ 和 __weakref__ 是因为我们不定义 __slots__ - 如果我们定义 __slots__ 我们会在例子中节省一些空间,因为我们可以通过排除它们来排除 __dict__ 和 __weakref__。

>>> Baz = type('Bar', (object,), {'__doc__': 'demo', '__slots__': ()})
>>> Baz.__dict__
mappingproxy({'__doc__': 'demo', '__slots__': (), '__module__': '__main__'})

我们可以像任何其他类定义一样扩展类型:

>>> Foo
<class '__main__.Foo'>

class Type(type):
    def __repr__(cls):
        """
        >>> Baz
        Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})
        >>> eval(repr(Baz))
        Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})
        """
        metaname = type(cls).__name__
        name = cls.__name__
        parents = ', '.join(b.__name__ for b in cls.__bases__)
        if parents:
            parents += ','
        namespace = ', '.join(': '.join(
          (repr(k), repr(v) if not isinstance(v, type) else v.__name__))
               for k, v in cls.__dict__.items())
        return '{0}(\'{1}\', ({2}), {{{3}}})'.format(metaname, name, parents, namespace)
    def __eq__(cls, other):
        """
        >>> Baz == eval(repr(Baz))
        True            
        """
        return (cls.__name__, cls.__bases__, cls.__dict__) == (
                other.__name__, other.__bases__, other.__dict__)

>>> class Bar(object): pass
>>> Baz = Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})
>>> Baz
Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})

但是,与 eval(repr(Class))的进一步检查是不可能的(因为函数将是相当不可能从他们的默认 __repr__ 的 eval 。

from collections import OrderedDict

class OrderedType(Type):
    @classmethod
    def __prepare__(metacls, name, bases, **kwargs):
        return OrderedDict()
    def __new__(cls, name, bases, namespace, **kwargs):
        result = Type.__new__(cls, name, bases, dict(namespace))
        result.members = tuple(namespace)
        return result

class OrderedMethodsObject(object, metaclass=OrderedType):
    def method1(self): pass
    def method2(self): pass
    def method3(self): pass
    def method4(self): pass

>>> OrderedMethodsObject.members
('__module__', '__qualname__', 'method1', 'method2', 'method3', 'method4')

>>> inspect.getmro(OrderedType)
(<class '__main__.OrderedType'>, <class '__main__.Type'>, <class 'type'>, <class 'object'>)

而且它大约有正确的回报(除非我们能找到代表我们的功能的方式,否则我们就不能再评估):

>>> OrderedMethodsObject
OrderedType('OrderedMethodsObject', (object,), {'method1': <function OrderedMethodsObject.method1 at 0x0000000002DB01E0>, 'members': ('__module__', '__qualname__', 'method1', 'method2', 'method3', 'method4'), 'method3': <function OrderedMet
hodsObject.method3 at 0x0000000002DB02F0>, 'method2': <function OrderedMethodsObject.method2 at 0x0000000002DB0268>, '__module__': '__main__', '__weakref__': <attribute '__weakref__' of 'OrderedMethodsObject' objects>, '__doc__': None, '__d
ict__': <attribute '__dict__' of 'OrderedMethodsObject' objects>, 'method4': <function OrderedMethodsObject.method4 at 0x0000000002DB0378>})

上面的答案是正确的。

但读者可能来到这里寻找关于类似名称的内部课程的答案,他们在受欢迎的图书馆,如Django和WTForms。

相反,这些是班级的命令之内的名称空间,它们是用内部班级为可读性而建造的。

在这个特殊的例子领域,抽象是显而易见地与作者模型的领域分开。

from django.db import models

class Author(models.Model):
    name = models.CharField(max_length=50)
    email = models.EmailField()

    class Meta:
        abstract = True

另一个例子是WTForms的文档:

from wtforms.form import Form
from wtforms.csrf.session import SessionCSRF
from wtforms.fields import StringField

class MyBaseForm(Form):
    class Meta:
        csrf = True
        csrf_class = SessionCSRF

    name = StringField("name")

这个合成不会在Python编程语言中得到特别的处理. Meta 不是这里的一个关键词,也不会引发 meta 类行为. 相反,第三方图书馆代码在 Django 和 WTForms 等包中,在某些类的构建者和其他地方读到这个属性。

这些声明的存在改变了具有这些声明的类别的行为. 例如,WTForms 阅读 self.Meta.csrf 以确定表格是否需要一个 csrf 字段。

类,在Python,是一个对象,和任何其他对象一样,它是一个例子“什么”。这个“什么”是所谓的MetaClass。这个MetaClass是一个特殊类型的类,创造了其他类的对象。因此,MetaClass负责创造新的类。

Class Name Tuple 具有由 Class A 继承的基类 词典具有所有类方法和类变量

另一种方式创建一个金属类是“金属类”的关键词,将金属类定义为一个简单的类,在继承类的参数中,通过金属类=金属类_名称。

Metaclass 可以在以下情况下具体使用:

Metaclasses 是做“类”的工作的秘密酱油,新风格对象的默认 metaclass 被称为“类型”。

class type(object)
  |  type(object) -> the object's type
  |  type(name, bases, dict) -> a new type

Metaclasses 取 3 args. 'name', 'bases' 和 'dict'

查找这个例子类定义中的名称、基础和字符号来源于哪里。

class ThisIsTheName(Bases, Are, Here):
    All_the_code_here
    def doesIs(create, a):
        dict

def test_metaclass(name, bases, dict):
    print 'The Class Name is', name
    print 'The Class Bases are', bases
    print 'The dict has', len(dict), 'elems, the keys are', dict.keys()

    return "yellow"

class TestName(object, None, int, 1):
    __metaclass__ = test_metaclass
    foo = 1
    def baz(self, arr):
        pass

print 'TestName = ', repr(TestName)

# output => 
The Class Name is TestName
The Class Bases are (<type 'object'>, None, <type 'int'>, 1)
The dict has 4 elems, the keys are ['baz', '__module__', 'foo', '__metaclass__']
TestName =  'yellow'

现在,一个实际上意味着什么的例子,这将自动使列表中的变量“属性”设置在课堂上,并设置为无。

def init_attributes(name, bases, dict):
    if 'attributes' in dict:
        for attr in dict['attributes']:
            dict[attr] = None

    return type(name, bases, dict)

class Initialised(object):
    __metaclass__ = init_attributes
    attributes = ['foo', 'bar', 'baz']

print 'foo =>', Initialised.foo
# output=>
foo => None

请注意,启动者获得的魔法行为是通过拥有金属类的 init_属性而没有转移到启动者的子类。

这里是一个更具体的例子,显示如何可以创建一个在创建一个类时执行一个行动的甲型类的“类型”。

class MetaSingleton(type):
    instance = None
    def __call__(cls, *args, **kw):
        if cls.instance is None:
            cls.instance = super(MetaSingleton, cls).__call__(*args, **kw)
        return cls.instance

class Foo(object):
    __metaclass__ = MetaSingleton

a = Foo()
b = Foo()
assert a is b