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%。

甲特克拉斯(甲特克拉斯)是一类,讲述了(某些)其他类应该是如何形成的。

这是一个案例,我看到甲状腺作为解决我的问题:我有一个真正复杂的问题,可能可以是不同的解决,但我选择用甲状腺解决它。 由于复杂性,这是我写的几个模块之一,在模块上的评论超过了编写的代码的数量。

#!/usr/bin/env python

# Copyright (C) 2013-2014 Craig Phillips.  All rights reserved.

# This requires some explaining.  The point of this metaclass excercise is to
# create a static abstract class that is in one way or another, dormant until
# queried.  I experimented with creating a singlton on import, but that did
# not quite behave how I wanted it to.  See now here, we are creating a class
# called GsyncOptions, that on import, will do nothing except state that its
# class creator is GsyncOptionsType.  This means, docopt doesn't parse any
# of the help document, nor does it start processing command line options.
# So importing this module becomes really efficient.  The complicated bit
# comes from requiring the GsyncOptions class to be static.  By that, I mean
# any property on it, may or may not exist, since they are not statically
# defined; so I can't simply just define the class with a whole bunch of
# properties that are @property @staticmethods.
#
# So here's how it works:
#
# Executing 'from libgsync.options import GsyncOptions' does nothing more
# than load up this module, define the Type and the Class and import them
# into the callers namespace.  Simple.
#
# Invoking 'GsyncOptions.debug' for the first time, or any other property
# causes the __metaclass__ __getattr__ method to be called, since the class
# is not instantiated as a class instance yet.  The __getattr__ method on
# the type then initialises the class (GsyncOptions) via the __initialiseClass
# method.  This is the first and only time the class will actually have its
# dictionary statically populated.  The docopt module is invoked to parse the
# usage document and generate command line options from it.  These are then
# paired with their defaults and what's in sys.argv.  After all that, we
# setup some dynamic properties that could not be defined by their name in
# the usage, before everything is then transplanted onto the actual class
# object (or static class GsyncOptions).
#
# Another piece of magic, is to allow command line options to be set in
# in their native form and be translated into argparse style properties.
#
# Finally, the GsyncListOptions class is actually where the options are
# stored.  This only acts as a mechanism for storing options as lists, to
# allow aggregation of duplicate options or options that can be specified
# multiple times.  The __getattr__ call hides this by default, returning the
# last item in a property's list.  However, if the entire list is required,
# calling the 'list()' method on the GsyncOptions class, returns a reference
# to the GsyncListOptions class, which contains all of the same properties
# but as lists and without the duplication of having them as both lists and
# static singlton values.
#
# So this actually means that GsyncOptions is actually a static proxy class...
#
# ...And all this is neatly hidden within a closure for safe keeping.
def GetGsyncOptionsType():
    class GsyncListOptions(object):
        __initialised = False

    class GsyncOptionsType(type):
        def __initialiseClass(cls):
            if GsyncListOptions._GsyncListOptions__initialised: return

            from docopt import docopt
            from libgsync.options import doc
            from libgsync import __version__

            options = docopt(
                doc.__doc__ % __version__,
                version = __version__,
                options_first = True
            )

            paths = options.pop('<path>', None)
            setattr(cls, "destination_path", paths.pop() if paths else None)
            setattr(cls, "source_paths", paths)
            setattr(cls, "options", options)

            for k, v in options.iteritems():
                setattr(cls, k, v)

            GsyncListOptions._GsyncListOptions__initialised = True

        def list(cls):
            return GsyncListOptions

        def __getattr__(cls, name):
            cls.__initialiseClass()
            return getattr(GsyncListOptions, name)[-1]

        def __setattr__(cls, name, value):
            # Substitut option names: --an-option-name for an_option_name
            import re
            name = re.sub(r'^__', "", re.sub(r'-', "_", name))
            listvalue = []

            # Ensure value is converted to a list type for GsyncListOptions
            if isinstance(value, list):
                if value:
                    listvalue = [] + value
                else:
                    listvalue = [ None ]
            else:
                listvalue = [ value ]

            type.__setattr__(GsyncListOptions, name, listvalue)

    # Cleanup this module to prevent tinkering.
    import sys
    module = sys.modules[__name__]
    del module.__dict__['GetGsyncOptionsType']

    return GsyncOptionsType

# Our singlton abstract proxy class.
class GsyncOptions(object):
    __metaclass__ = GetGsyncOptionsType()

下面是另一个例子,它可以用于什么:

您可以使用甲状腺来改变其例子(类)的功能。

class MetaMemberControl(type):
    __slots__ = ()

    @classmethod
    def __prepare__(mcs, f_cls_name, f_cls_parents,  # f_cls means: future class
                    meta_args=None, meta_options=None):  # meta_args and meta_options is not necessarily needed, just so you know.
        f_cls_attr = dict()
        if not "do something or if you want to define your cool stuff of dict...":
            return dict(make_your_special_dict=None)
        else:
            return f_cls_attr

    def __new__(mcs, f_cls_name, f_cls_parents, f_cls_attr,
                meta_args=None, meta_options=None):

        original_getattr = f_cls_attr.get('__getattribute__')
        original_setattr = f_cls_attr.get('__setattr__')

        def init_getattr(self, item):
            if not item.startswith('_'):  # you can set break points at here
                alias_name = '_' + item
                if alias_name in f_cls_attr['__slots__']:
                    item = alias_name
            if original_getattr is not None:
                return original_getattr(self, item)
            else:
                return super(eval(f_cls_name), self).__getattribute__(item)

        def init_setattr(self, key, value):
            if not key.startswith('_') and ('_' + key) in f_cls_attr['__slots__']:
                raise AttributeError(f"you can't modify private members:_{key}")
            if original_setattr is not None:
                original_setattr(self, key, value)
            else:
                super(eval(f_cls_name), self).__setattr__(key, value)

        f_cls_attr['__getattribute__'] = init_getattr
        f_cls_attr['__setattr__'] = init_setattr

        cls = super().__new__(mcs, f_cls_name, f_cls_parents, f_cls_attr)
        return cls


class Human(metaclass=MetaMemberControl):
    __slots__ = ('_age', '_name')

    def __init__(self, name, age):
        self._name = name
        self._age = age

    def __getattribute__(self, item):
        """
        is just for IDE recognize.
        """
        return super().__getattribute__(item)

    """ with MetaMemberControl then you don't have to write as following
    @property
    def name(self):
        return self._name

    @property
    def age(self):
        return self._age
    """


def test_demo():
    human = Human('Carson', 27)
    # human.age = 18  # you can't modify private members:_age  <-- this is defined by yourself.
    # human.k = 18  # 'Human' object has no attribute 'k'  <-- system error.
    age1 = human._age  # It's OK, although the IDE will show some warnings. (Access to a protected member _age of a class)

    age2 = human.age  # It's OK! see below:
    """
    if you do not define `__getattribute__` at the class of Human,
    the IDE will show you: Unresolved attribute reference 'age' for class 'Human'
    but it's ok on running since the MetaMemberControl will help you.
    """


if __name__ == '__main__':
    test_demo()

金星是强大的,有很多事情(如猴子魔法)你可以用它,但要小心,这可能只是你知道的。

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。

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。

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。