你可以像这样重写__new__方法:

class Singleton(object):
    _instance = None
    def __new__(cls, *args, **kwargs):
        if not cls._instance:
            cls._instance = super(Singleton, cls).__new__(
                                cls, *args, **kwargs)
        return cls._instance


if __name__ == '__main__':
    s1 = Singleton()
    s2 = Singleton()
    if (id(s1) == id(s2)):
        print "Same"
    else:
        print "Different"

好吧，我知道，单胞胎可能是好的，也可能是坏的。这是我的实现，我只是扩展了一个经典的方法，在里面引入一个缓存，并产生许多不同类型的实例，或者许多相同类型的实例，但具有不同的参数。

我称它为Singleton_group，因为它将相似的实例分组在一起，并防止创建具有相同参数的相同类的对象:

# Peppelinux's cached singleton
class Singleton_group(object):
    __instances_args_dict = {}
    def __new__(cls, *args, **kwargs):
        if not cls.__instances_args_dict.get((cls.__name__, args, str(kwargs))):
            cls.__instances_args_dict[(cls.__name__, args, str(kwargs))] = super(Singleton_group, cls).__new__(cls, *args, **kwargs)
        return cls.__instances_args_dict.get((cls.__name__, args, str(kwargs)))


# It's a dummy real world use example:
class test(Singleton_group):
    def __init__(self, salute):
        self.salute = salute

a = test('bye')
b = test('hi')
c = test('bye')
d = test('hi')
e = test('goodbye')
f = test('goodbye')

id(a)
3070148780L

id(b)
3070148908L

id(c)
3070148780L

b == d
True


b._Singleton_group__instances_args_dict

{('test', ('bye',), '{}'): <__main__.test object at 0xb6fec0ac>,
 ('test', ('goodbye',), '{}'): <__main__.test object at 0xb6fec32c>,
 ('test', ('hi',), '{}'): <__main__.test object at 0xb6fec12c>}

每个对象都携带单例缓存…这可能是邪恶的，但对一些人来说很有用:)

Python文档涵盖了这些内容:

class Singleton(object):
    def __new__(cls, *args, **kwds):
        it = cls.__dict__.get("__it__")
        if it is not None:
            return it
        cls.__it__ = it = object.__new__(cls)
        it.init(*args, **kwds)
        return it
    def init(self, *args, **kwds):
        pass

我可能会重写成这样:

class Singleton(object):
    """Use to create a singleton"""
    def __new__(cls, *args, **kwds):
        """
        >>> s = Singleton()
        >>> p = Singleton()
        >>> id(s) == id(p)
        True
        """
        it_id = "__it__"
        # getattr will dip into base classes, so __dict__ must be used
        it = cls.__dict__.get(it_id, None)
        if it is not None:
            return it
        it = object.__new__(cls)
        setattr(cls, it_id, it)
        it.init(*args, **kwds)
        return it

    def init(self, *args, **kwds):
        pass


class A(Singleton):
    pass


class B(Singleton):
    pass


class C(A):
    pass


assert A() is A()
assert B() is B()
assert C() is C()
assert A() is not B()
assert C() is not B()
assert C() is not A()

它应该是相对干净的扩展:

class Bus(Singleton):
    def init(self, label=None, *args, **kwds):
        self.label = label
        self.channels = [Channel("system"), Channel("app")]
        ...

你可以像这样重写__new__方法:

class Singleton(object):
    _instance = None
    def __new__(cls, *args, **kwargs):
        if not cls._instance:
            cls._instance = super(Singleton, cls).__new__(
                                cls, *args, **kwargs)
        return cls._instance


if __name__ == '__main__':
    s1 = Singleton()
    s2 = Singleton()
    if (id(s1) == id(s2)):
        print "Same"
    else:
        print "Different"

class Singleton(object[,...]):

    staticVar1 = None
    staticVar2 = None

    def __init__(self):
        if self.__class__.staticVar1==None :
            # create class instance variable for instantiation of class
            # assign class instance variable values to class static variables
        else:
            # assign class static variable values to class instance variables

我真的不认为有这个需要，因为一个带有函数(而不是类)的模块可以很好地作为一个单例。它的所有变量都将绑定到模块，无论如何都不能重复实例化。

如果你确实希望使用一个类，在Python中没有办法创建私有类或私有构造函数，所以你不能防止多个实例化，只能通过使用API中的约定。我仍然会将方法放在模块中，并将模块视为单例模块。