什么是甲状腺?它们用于什么?
当前回答
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
其他回答
Python 类本身是它们的 meta 类的对象 - 例如。
默认的金属类,当您确定类时应用于:
class foo:
...
例如,假设您正在构建一个ORM访问数据库,并且您希望每个表中的记录来自一个类地图到该表(基于字段,业务规则等),一个可能的使用MetaClass是例如,连接池逻辑,由所有表中的记录的所有类共享。
当你定义甲型时,你可以分类类型,并且可以超越下列魔法方法来插入你的逻辑。
class somemeta(type):
__new__(mcs, name, bases, clsdict):
"""
mcs: is the base metaclass, in this case type.
name: name of the new class, as provided by the user.
bases: tuple of base classes
clsdict: a dictionary containing all methods and attributes defined on class
you must return a class object by invoking the __new__ constructor on the base metaclass.
ie:
return type.__call__(mcs, name, bases, clsdict).
in the following case:
class foo(baseclass):
__metaclass__ = somemeta
an_attr = 12
def bar(self):
...
@classmethod
def foo(cls):
...
arguments would be : ( somemeta, "foo", (baseclass, baseofbase,..., object), {"an_attr":12, "bar": <function>, "foo": <bound class method>}
you can modify any of these values before passing on to type
"""
return type.__call__(mcs, name, bases, clsdict)
def __init__(self, name, bases, clsdict):
"""
called after type has been created. unlike in standard classes, __init__ method cannot modify the instance (cls) - and should be used for class validaton.
"""
pass
def __prepare__():
"""
returns a dict or something that can be used as a namespace.
the type will then attach methods and attributes from class definition to it.
call order :
somemeta.__new__ -> type.__new__ -> type.__init__ -> somemeta.__init__
"""
return dict()
def mymethod(cls):
""" works like a classmethod, but for class objects. Also, my method will not be visible to instances of cls.
"""
pass
无论如何,这两种是最常用的<unk>子,甲板是强大的,上面没有附近和完整的用途列表用于甲板。
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
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>})
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
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。
推荐文章
- 如何在一行中连接两个集而不使用“|”
- 从字符串中移除前缀
- 代码结束时发出警报
- 如何在Python中按字母顺序排序字符串中的字母
- 在matplotlib中将y轴标签添加到次要y轴
- 如何消除数独方块的凹凸缺陷?
- 为什么出现这个UnboundLocalError(闭包)?
- 使用Python请求的异步请求
- 如何检查一个对象是否是python中的生成器对象?
- 如何从Python包内读取(静态)文件?
- 如何计算一个逻辑sigmoid函数在Python?
- python: SyntaxError: EOL扫描字符串文字
- Pipenv:命令未找到
- 根据Pandas中的另一列提取列值
- virtualenv和pyenv是什么关系?