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()

当班级声明执行时,Python 首先将班级声明的身体作为一个正常的代码块执行。 结果的名称空间(dict)保留了班级的属性. 金属阶级通过观察班级的基层(金属阶级继承),在 __金属阶级__属性的班级(如果有)或 __金属阶级__全球变量来确定。

def make_hook(f):
    """Decorator to turn 'foo' method into '__foo__'"""
    f.is_hook = 1
    return f

class MyType(type):
    def __new__(mcls, name, bases, attrs):

        if name.startswith('None'):
            return None

        # Go over attributes and see if they should be renamed.
        newattrs = {}
        for attrname, attrvalue in attrs.iteritems():
            if getattr(attrvalue, 'is_hook', 0):
                newattrs['__%s__' % attrname] = attrvalue
            else:
                newattrs[attrname] = attrvalue

        return super(MyType, mcls).__new__(mcls, name, bases, newattrs)

    def __init__(self, name, bases, attrs):
        super(MyType, self).__init__(name, bases, attrs)

        # classregistry.register(self, self.interfaces)
        print "Would register class %s now." % self

    def __add__(self, other):
        class AutoClass(self, other):
            pass
        return AutoClass
        # Alternatively, to autogenerate the classname as well as the class:
        # return type(self.__name__ + other.__name__, (self, other), {})

    def unregister(self):
        # classregistry.unregister(self)
        print "Would unregister class %s now." % self

class MyObject:
    __metaclass__ = MyType


class NoneSample(MyObject):
    pass

# Will print "NoneType None"
print type(NoneSample), repr(NoneSample)

class Example(MyObject):
    def __init__(self, value):
        self.value = value
    @make_hook
    def add(self, other):
        return self.__class__(self.value + other.value)

# Will unregister the class
Example.unregister()

inst = Example(10)
# Will fail with an AttributeError
#inst.unregister()

print inst + inst
class Sibling(MyObject):
    pass

ExampleSibling = Example + Sibling
# ExampleSibling is now a subclass of both Example and Sibling (with no
# content of its own) although it will believe it's called 'AutoClass'
print ExampleSibling
print ExampleSibling.__mro__

类,在Python,是一个对象,和任何其他对象一样,它是一个例子“什么”。这个“什么”是所谓的MetaClass。这个MetaClass是一个特殊类型的类,创造了其他类的对象。因此,MetaClass负责创造新的类。

Class Name Tuple 具有由 Class A 继承的基类 词典具有所有类方法和类变量

另一种方式创建一个金属类是“金属类”的关键词,将金属类定义为一个简单的类,在继承类的参数中,通过金属类=金属类_名称。

Metaclass 可以在以下情况下具体使用:

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

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。

请注意,在Python 3.6中,引入了一个新的Dunder方法 __init_subclass__(cls, **kwargs),以取代许多常见的使用案例为MetaClass。