>>> class ObjectCreator(object):
...       pass

>>> my_object = ObjectCreator()
>>> print(my_object)
<__main__.ObjectCreator object at 0x8974f2c>

>>> class ObjectCreator(object):
...       pass

>>> print(JustAnotherVariable)
<class '__main__.ObjectCreator'>

>>> print(JustAnotherVariable())
<__main__.ObjectCreator object at 0x8997b4c>

>>> def choose_class(name):
...     if name == 'foo':
...         class Foo(object):
...             pass
...         return Foo # return the class, not an instance
...     else:
...         class Bar(object):
...             pass
...         return Bar
...
>>> MyClass = choose_class('foo')
>>> print(MyClass) # the function returns a class, not an instance
<class '__main__.Foo'>
>>> print(MyClass()) # you can create an object from this class
<__main__.Foo object at 0x89c6d4c>

>>> print(type(1))
<type 'int'>
>>> print(type("1"))
<type 'str'>
>>> print(type(ObjectCreator))
<type 'type'>
>>> print(type(ObjectCreator()))
<class '__main__.ObjectCreator'>

type(name, bases, attrs)

>>> class MyShinyClass(object):
...       pass

>>> MyShinyClass = type('MyShinyClass', (), {}) # returns a class object
>>> print(MyShinyClass)
<class '__main__.MyShinyClass'>
>>> print(MyShinyClass()) # create an instance with the class
<__main__.MyShinyClass object at 0x8997cec>

>>> class Foo(object):
...       bar = True

>>> Foo = type('Foo', (), {'bar':True})

>>> print(Foo)
<class '__main__.Foo'>
>>> print(Foo.bar)
True
>>> f = Foo()
>>> print(f)
<__main__.Foo object at 0x8a9b84c>
>>> print(f.bar)
True

>>>   class FooChild(Foo):
...         pass

>>> FooChild = type('FooChild', (Foo,), {})
>>> print(FooChild)
<class '__main__.FooChild'>
>>> print(FooChild.bar) # bar is inherited from Foo
True

>>> def echo_bar(self):
...       print(self.bar)
...
>>> FooChild = type('FooChild', (Foo,), {'echo_bar': echo_bar})
>>> hasattr(Foo, 'echo_bar')
False
>>> hasattr(FooChild, 'echo_bar')
True
>>> my_foo = FooChild()
>>> my_foo.echo_bar()
True

>>> def echo_bar_more(self):
...       print('yet another method')
...
>>> FooChild.echo_bar_more = echo_bar_more
>>> hasattr(FooChild, 'echo_bar_more')
True

MyClass = MetaClass()
my_object = MyClass()

MyClass = type('MyClass', (), {})

>>> age = 35
>>> age.__class__
<type 'int'>
>>> name = 'bob'
>>> name.__class__
<type 'str'>
>>> def foo(): pass
>>> foo.__class__
<type 'function'>
>>> class Bar(object): pass
>>> b = Bar()
>>> b.__class__
<class '__main__.Bar'>

>>> age.__class__.__class__
<type 'type'>
>>> name.__class__.__class__
<type 'type'>
>>> foo.__class__.__class__
<type 'type'>
>>> b.__class__.__class__
<type 'type'>

class Foo(object):
    __metaclass__ = something...
    [...]

class Foo(Bar):
    pass

设置 meta 类的合成已在 Python 3 中更改:

class Foo(object, metaclass=something):
    ...

class Foo(object, metaclass=something, kwarg1=value1, kwarg2=value2):
    ...

# the metaclass will automatically get passed the same argument
# that you usually pass to `type`
def upper_attr(future_class_name, future_class_parents, future_class_attrs):
    """
      Return a class object, with the list of its attribute turned
      into uppercase.
    """
    # pick up any attribute that doesn't start with '__' and uppercase it
    uppercase_attrs = {
        attr if attr.startswith("__") else attr.upper(): v
        for attr, v in future_class_attrs.items()
    }

    # let `type` do the class creation
    return type(future_class_name, future_class_parents, uppercase_attrs)

__metaclass__ = upper_attr # this will affect all classes in the module

class Foo(): # global __metaclass__ won't work with "object" though
    # but we can define __metaclass__ here instead to affect only this class
    # and this will work with "object" children
    bar = 'bip'

>>> hasattr(Foo, 'bar')
False
>>> hasattr(Foo, 'BAR')
True
>>> Foo.BAR
'bip'

# remember that `type` is actually a class like `str` and `int`
# so you can inherit from it
class UpperAttrMetaclass(type):
    # __new__ is the method called before __init__
    # it's the method that creates the object and returns it
    # while __init__ just initializes the object passed as parameter
    # you rarely use __new__, except when you want to control how the object
    # is created.
    # here the created object is the class, and we want to customize it
    # so we override __new__
    # you can do some stuff in __init__ too if you wish
    # some advanced use involves overriding __call__ as well, but we won't
    # see this
    def __new__(upperattr_metaclass, future_class_name,
                future_class_parents, future_class_attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in future_class_attrs.items()
        }
        return type(future_class_name, future_class_parents, uppercase_attrs)

class UpperAttrMetaclass(type):
    def __new__(cls, clsname, bases, attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in attrs.items()
        }
        return type(clsname, bases, uppercase_attrs)

class UpperAttrMetaclass(type):
    def __new__(cls, clsname, bases, attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in attrs.items()
        }
        return type.__new__(cls, clsname, bases, uppercase_attrs)

class UpperAttrMetaclass(type):
    def __new__(cls, clsname, bases, attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in attrs.items()
        }

        # Python 2 requires passing arguments to super:
        return super(UpperAttrMetaclass, cls).__new__(
            cls, clsname, bases, uppercase_attrs)

        # Python 3 can use no-arg super() which infers them:
        return super().__new__(cls, clsname, bases, uppercase_attrs)

class Foo(object, metaclass=MyMetaclass, kwarg1=value1):
    ...

class MyMetaclass(type):
    def __new__(cls, clsname, bases, dct, kwargs1=default):
        ...

使用金属玻璃代码的复杂性背后的原因不是由于金属玻璃,而是因为你通常使用金属玻璃来制作依赖于入观、操纵遗产、如 __dict__ 等的旋转物品。

有几个理由这样做:

為什麼要使用MetaClass?

现在,大问题:为什么你会使用一些模糊的错误漏洞功能?

如果你想知道你是否需要它们,你不会(真正需要它们的人肯定知道他们需要它们,不需要解释为什么)。

Python Guru 蒂姆·彼得斯

class Person(models.Model):
    name = models.CharField(max_length=30)
    age = models.IntegerField()

person = Person(name='bob', age='35')
print(person.age)

最后一句话

首先,你知道,类是可以创造例子的物体。

>>> class Foo(object): pass
>>> id(Foo)
142630324

99%的时间你需要课堂变化,你更好地使用这些。

但98%的时间,你根本不需要课堂变化。

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

Python 3 更新

在一个甲状腺中,有(目前)两个关键方法:

__prepare__ 允许您提供自定义地图(如 OrderedDict)作为名称空间使用,而类正在创建。

__new__ 负责最终类的实际创建/修改。

一个色彩色彩,不做任何东西 - 额外的金属类会喜欢:

class Meta(type):

    def __prepare__(metaclass, cls, bases):
        return dict()

    def __new__(metacls, cls, bases, clsdict):
        return super().__new__(metacls, cls, bases, clsdict)

一个简单的例子:

说你想要一些简单的验证代码在你的属性上运行 - 因为它必须总是一个 int 或 str. 没有一个 metaclass,你的类会看起来像:

class Person:
    weight = ValidateType('weight', int)
    age = ValidateType('age', int)
    name = ValidateType('name', str)

正如你可以看到的那样,你必须重复属性的名称两次,这使得类型与刺激的错误一起可能。

一个简单的甲状腺可以解决这个问题:

class Person(metaclass=Validator):
    weight = ValidateType(int)
    age = ValidateType(int)
    name = ValidateType(str)

class Validator(type):
    def __new__(metacls, cls, bases, clsdict):
        # search clsdict looking for ValidateType descriptors
        for name, attr in clsdict.items():
            if isinstance(attr, ValidateType):
                attr.name = name
                attr.attr = '_' + name
        # create final class and return it
        return super().__new__(metacls, cls, bases, clsdict)

一个样本运行:

p = Person()
p.weight = 9
print(p.weight)
p.weight = '9'

生产:

9
Traceback (most recent call last):
  File "simple_meta.py", line 36, in <module>
    p.weight = '9'
  File "simple_meta.py", line 24, in __set__
    (self.name, self.type, value))
TypeError: weight must be of type(s) <class 'int'> (got '9')

---

注意:这个例子是简单的,它也可能已经完成了一个类装饰师,但假设一个真正的金属玻璃会做得更多。

class ValidateType:
    def __init__(self, type):
        self.name = None  # will be set by metaclass
        self.attr = None  # will be set by metaclass
        self.type = type
    def __get__(self, inst, cls):
        if inst is None:
            return self
        else:
            return inst.__dict__[self.attr]
    def __set__(self, inst, value):
        if not isinstance(value, self.type):
            raise TypeError('%s must be of type(s) %s (got %r)' %
                    (self.name, self.type, value))
        else:
            inst.__dict__[self.attr] = value

型()函数可以返回对象的类型或创建一个新的类型,

例如,我们可以使用类()函数创建一个 Hi 类,并且不需要使用类 Hi(对象):

def func(self, name='mike'):
    print('Hi, %s.' % name)

Hi = type('Hi', (object,), dict(hi=func))
h = Hi()
h.hi()
Hi, mike.

type(Hi)
type

type(h)
__main__.Hi

除了使用类()以动态创建类,您还可以控制类的创建行为,并使用甲塔克拉斯。

根据 Python 对象模型,类是对象,所以类必须是另一个特定的类的例子. 默认情况下, Python 类是类类类的例子. 也就是说,类是大多数内置类的甲型类和用户定义类的甲型类。

class ListMetaclass(type):
    def __new__(cls, name, bases, attrs):
        attrs['add'] = lambda self, value: self.append(value)
        return type.__new__(cls, name, bases, attrs)

class CustomList(list, metaclass=ListMetaclass):
    pass

lst = CustomList()
lst.add('custom_list_1')
lst.add('custom_list_2')

lst
['custom_list_1', 'custom_list_2']

魔法将有效,当我们通过关键词论点在Metaclass,它指示Python翻译器通过ListMetaclass创建CustomList。新(),在此时,我们可以修改类定义,例如,并添加一个新的方法,然后返回修订的定义。

简而言之:一类是创建一个例子的图标,一类是创建一个类的图标,可以很容易地看到,在Python类中,也需要第一类对象才能实现这种行为。

我从来没有自己写过一个,但我认为在Django框架中可以看到最可爱的用途之一。模型类使用一个模型类的方法,以允许写新的模型或形式类的宣言风格。

剩下的就是:如果你不知道什么是金属玻璃,那么你不需要它们的可能性是99%。

看这:

Python 3.10.0rc2 (tags/v3.10.0rc2:839d789, Sep  7 2021, 18:51:45) [MSC v.1929 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> class Object:
...     pass
... 
>>> class Meta(type):
...     test = 'Worked!!!'
...     def __repr__(self):
...             return 'This is "Meta" metaclass'
... 
>>> class ObjectWithMetaClass(metaclass=Meta):
...     pass
... 
>>> Object or type(Object())
<class '__main__.Object'>
>>> ObjectWithMetaClass or type(ObjectWithMetaClass())
This is "Meta" metaclass
>>> Object.test
AttributeError: ...
>>> ObjectWithMetaClass.test
'Worked!!!'
>>> type(Object)
<class 'type'>
>>> type(ObjectWithMetaClass)
<class '__main__.Meta'>
>>> type(type(ObjectWithMetaClass))
<class 'type'>
>>> Object.__bases__
(<class 'object'>,)
>>> ObjectWithMetaClass.__bases__
(<class 'object'>,)
>>> type(ObjectWithMetaClass).__bases__
(<class 'type'>,)
>>> Object.__mro__
(<class '__main__.Object'>, <class 'object'>)
>>> ObjectWithMetaClass.__mro__
(This is "Meta" metaclass, <class 'object'>)
>>> 

换句话说,当一个对象没有创建(对象类型),我们正在寻找MetaClass。