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。

一个用途是自动将新属性和方法添加到一个例子。

例如,如果你看 Django 模型,它们的定义看起来有点困惑。

class Person(models.Model):
    first_name = models.CharField(max_length=30)
    last_name = models.CharField(max_length=30)

然而,在工作时间里,人体对象充满了各种有用的方法。

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()

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'

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。

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。