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

# 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

在以对象为导向的编程中,一个代码类是一种类,其例子是类。 正如普通类定义某些对象的行为一样,一个代码类定义某些类的行为和其例子 这个术语的代码类简单地意味着用于创建类的东西。

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。

在Python中,一类是指一个子类的子类,它决定一个子类的行为方式;在Python中,一类是另一个子类的例子;在Python中,一类是指一个子类的例子将如何行事。

由于甲基层负责类型,所以你可以写自己的自定义甲基层来改变类型是通过执行额外的操作或注射代码创建的方式。

此分類上一篇: tl;dr version

类型(obj)函数会给你一个对象的类型。

一个阶级的类型( )是它的甲型阶级。

使用甲状腺:

class Foo(object):
    __metaclass__ = MyMetaClass

一个类的类是一个类的类 - 一个类的身体是转移到一个类的论点,它被用来构建一个类。

在这里,你可以阅读如何使用金属玻璃来自定义课堂建筑。