这个问题不是为了讨论单例设计模式是否可取、是否是一种反模式,或者是否用于任何宗教战争,而是为了讨论如何以最Python化的方式在Python中最好地实现这种模式。在这个例子中,我定义“最蟒蛇”是指它遵循“最少惊讶的原则”。

我有多个类将成为单类(我的用例是一个记录器,但这并不重要)。当我可以简单地继承或装饰时,我不希望在几个类中添加口香糖。

最佳方法:


方法1:装饰器

def singleton(class_):
    instances = {}
    def getinstance(*args, **kwargs):
        if class_ not in instances:
            instances[class_] = class_(*args, **kwargs)
        return instances[class_]
    return getinstance

@singleton
class MyClass(BaseClass):
    pass

Pros

装饰符的添加方式通常比多重继承更直观。

Cons

虽然使用MyClass()创建的对象将是真正的单例对象,但MyClass本身是一个函数,而不是类,因此不能从中调用类方法x=MyClass();y=MyClass();t=类型(n)();

则x==y但x!=t&y!=吨


方法2:基类

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

class MyClass(Singleton, BaseClass):
    pass

Pros

这是一门真正的课

Cons

多重继承-嗯__new__是否可以在从第二个基类继承期间被覆盖?一个人必须想得比必要的多。


方法3:元类

class Singleton(type):
    _instances = {}
    def __call__(cls, *args, **kwargs):
        if cls not in cls._instances:
            cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
        return cls._instances[cls]

#Python2
class MyClass(BaseClass):
    __metaclass__ = Singleton

#Python3
class MyClass(BaseClass, metaclass=Singleton):
    pass

Pros

这是一门真正的课自动神奇地覆盖继承为正确的目的使用__metaclass__(并让我意识到)

Cons

有吗?


方法4:decorator返回同名类

def singleton(class_):
    class class_w(class_):
        _instance = None
        def __new__(class_, *args, **kwargs):
            if class_w._instance is None:
                class_w._instance = super(class_w,
                                    class_).__new__(class_,
                                                    *args,
                                                    **kwargs)
                class_w._instance._sealed = False
            return class_w._instance
        def __init__(self, *args, **kwargs):
            if self._sealed:
                return
            super(class_w, self).__init__(*args, **kwargs)
            self._sealed = True
    class_w.__name__ = class_.__name__
    return class_w

@singleton
class MyClass(BaseClass):
    pass

Pros

这是一门真正的课自动神奇地覆盖继承

Cons

创建每个新类是否没有开销?在这里,我们为每个希望成为单例的类创建两个类。虽然这对我来说很好,但我担心这可能无法扩展。当然,对于这种模式的规模是否太容易,还有争议。。。_seled属性的意义是什么无法使用super()在基类上调用同名方法,因为它们将递归。这意味着您不能自定义__new__,也不能对需要调用__init__的类进行子类化。


方法5:模块

模块文件singleton.py

Pros

简单胜于复杂

Cons

未延迟实例化


当前回答

如果要将实例用作属性,可以使用元类。例如

class SingletonMeta(type):
    def __init__(cls, *args, **kwargs):
        super().__init__(*args, **kwargs)
        cls._instance = None
        cls._locker = threading.Lock()

    @property
    def instance(self, *args, **kwargs):
        if self._instance is None:
            with self._locker:
                if self._instance is None:
                    self._instance = self(*args, **kwargs)
        return self._instance


class MyClass(metaclass=SingletonMeta):
    def __init__(self):
        # init here
        pass


# get the instance
my_class_instance = MyClass.instance

其他回答

这是我自己的单线图实现。你所要做的就是装饰课堂;要获得单例,您必须使用Instance方法。下面是一个示例:

@Singleton
class Foo:
    def __init__(self):
        print 'Foo created'

f = Foo() # Error, this isn't how you get the instance of a singleton

f = Foo.Instance() # Good. Being explicit is in line with the Python Zen
g = Foo.Instance() # Returns already created instance

print f is g # True

下面是代码:

class Singleton:
    """
    A non-thread-safe helper class to ease implementing singletons.
    This should be used as a decorator -- not a metaclass -- to the
    class that should be a singleton.

    The decorated class can define one `__init__` function that
    takes only the `self` argument. Other than that, there are
    no restrictions that apply to the decorated class.
 
    To get the singleton instance, use the `Instance` method. Trying
    to use `__call__` will result in a `TypeError` being raised.

    Limitations: The decorated class cannot be inherited from.

    """

    def __init__(self, decorated):
        self._decorated = decorated

    def Instance(self):
        """
        Returns the singleton instance. Upon its first call, it creates a
        new instance of the decorated class and calls its `__init__` method.
        On all subsequent calls, the already created instance is returned.

        """
        try:
            return self._instance
        except AttributeError:
            self._instance = self._decorated()
            return self._instance

    def __call__(self):
        raise TypeError('Singletons must be accessed through `Instance()`.')

    def __instancecheck__(self, inst):
        return isinstance(inst, self._decorated)

我更喜欢这个解决方案,我发现它非常清晰和直接。例如,如果其他线程已经创建了它,它将使用双重检查。需要考虑的另一件事是确保反序列化不会创建任何其他实例。https://gist.github.com/werediver/4396488

import threading


# Based on tornado.ioloop.IOLoop.instance() approach.
# See https://github.com/facebook/tornado
class SingletonMixin(object):
    __singleton_lock = threading.Lock()
    __singleton_instance = None

    @classmethod
    def instance(cls):
        if not cls.__singleton_instance:
            with cls.__singleton_lock:
                if not cls.__singleton_instance:
                    cls.__singleton_instance = cls()
        return cls.__singleton_instance


if __name__ == '__main__':
    class A(SingletonMixin):
        pass

    class B(SingletonMixin):
        pass

    a, a2 = A.instance(), A.instance()
    b, b2 = B.instance(), B.instance()

    assert a is a2
    assert b is b2
    assert a is not b

    print('a:  %s\na2: %s' % (a, a2))
    print('b:  %s\nb2: %s' % (b, b2))

您只需要一个装饰器,具体取决于python版本:


Python 3.2+

实施

from functools import lru_cache

@lru_cache(maxsize=None)
class CustomClass(object):

    def __init__(self, arg):
        print(f"CustomClass initialised with {arg}")
        self.arg = arg

用法

c1 = CustomClass("foo")
c2 = CustomClass("foo")
c3 = CustomClass("bar")

print(c1 == c2)
print(c1 == c3)

输出

>>> CustomClass initialised with foo
>>> CustomClass initialised with bar
>>> True
>>> False

注意foo只打印一次


Python 3.9+

实施:

from functools import cache

@cache
class CustomClass(object):
    ...

好吧,除了同意Pythonic关于模块级全局的一般建议之外,这又如何呢

def singleton(class_):
    class class_w(class_):
        _instance = None
        def __new__(class2, *args, **kwargs):
            if class_w._instance is None:
                class_w._instance = super(class_w, class2).__new__(class2, *args, **kwargs)
                class_w._instance._sealed = False
            return class_w._instance
        def __init__(self, *args, **kwargs):
            if self._sealed:
                return
            super(class_w, self).__init__(*args, **kwargs)
            self._sealed = True
    class_w.__name__ = class_.__name__
    return class_w

@singleton
class MyClass(object):
    def __init__(self, text):
        print text
    @classmethod
    def name(class_):
        print class_.__name__

x = MyClass(111)
x.name()
y = MyClass(222)
print id(x) == id(y)

输出为:

111     # the __init__ is called only on the 1st time
MyClass # the __name__ is preserved
True    # this is actually the same instance

这里是一个结合@agf和@(Siddhesh Suhas Sathe)解决方案的简单实现,它使用元类并考虑构造函数参数,因此如果使用完全相同的参数创建foo类,则可以返回相同的实例


class SingletonMeta(type):
    _instances = {}

    def __call__(cls, *args, **kwargs):
        """
        Possible changes to the value of the `__init__` argument do not affect
        the returned instance.
        """
        cls_instances = cls._instances.get(cls) or []
        matching_instances = list(
            filter(
                lambda x: x["args"] == args and x["kwargs"] == kwargs,
                cls_instances,
            )
        )
        if len(matching_instances) == 1:
            return matching_instances[0]["instance"]
        else:
            instance = super().__call__(*args, **kwargs)
            cls_instances.append({"instance": instance, "args": args, "kwargs": kwargs})
            cls._instances[cls] = cls_instances
            return instance


class foo(metaclass=SingletonMeta):
    def __init__(self, param, k_param=None) -> None:
        print("Creating new instance")
        self.param = param
        self.k_param = k_param
        self._creation_time = time.time()