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
我看到一个有趣的使用案例在一个名为类用途的包中,它检查是否所有类变量在顶部案例格式(方便有统一逻辑的配置类),并检查是否没有例子级方法在课堂上。
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>})
类型实际上是一类 - 创建另一个类的类型. 大多数类型是类型的子类型. 类型接收新类作为其第一个论点,并提供到类对象的访问,如下所述的细节:
>>> class MetaClass(type):
... def __init__(cls, name, bases, attrs):
... print ('class name: %s' %name )
... print ('Defining class %s' %cls)
... print('Bases %s: ' %bases)
... print('Attributes')
... for (name, value) in attrs.items():
... print ('%s :%r' %(name, value))
...
>>> class NewClass(object, metaclass=MetaClass):
... get_choch='dairy'
...
class name: NewClass
Bases <class 'object'>:
Defining class <class 'NewClass'>
get_choch :'dairy'
__module__ :'builtins'
__qualname__ :'NewClass'
注:
请注意,课堂在任何时候都没有被暂停;创建课堂的简单行为引发了金属课堂的执行。
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
推荐文章
- 证书验证失败:无法获得本地颁发者证书
- 当使用pip3安装包时,“Python中的ssl模块不可用”
- 无法切换Python与pyenv
- Python if not == vs if !=
- 如何从scikit-learn决策树中提取决策规则?
- 为什么在Mac OS X v10.9 (Mavericks)的终端中apt-get功能不起作用?
- 将旋转的xtick标签与各自的xtick对齐
- 为什么元组可以包含可变项?
- 如何合并字典的字典?
- 如何创建类属性?
- 不区分大小写的“in”
- 在Python中获取迭代器中的元素个数
- 解析日期字符串并更改格式
- 使用try和。Python中的if
- 如何在Python中获得所有直接子目录