经过一段时间的努力，我终于想出了以下方法，这样当从单独的模块调用时，配置对象只能加载一次。元类允许将全局类实例存储在内置dict中，目前看来这是存储适当程序全局的最整洁的方式。

import builtins

# -----------------------------------------------------------------------------
# So..... you would expect that a class would be "global" in scope, however
#   when different modules use this,
#   EACH ONE effectively has its own class namespace.  
#   In order to get around this, we use a metaclass to intercept
#   "new" and provide the "truly global metaclass instance" if it already exists

class MetaConfig(type):
    def __new__(cls, name, bases, dct):
        try:
            class_inst = builtins.CONFIG_singleton

        except AttributeError:
            class_inst = super().__new__(cls, name, bases, dct)
            builtins.CONFIG_singleton = class_inst
            class_inst.do_load()

        return class_inst

# -----------------------------------------------------------------------------

class Config(metaclass=MetaConfig):

    config_attr = None

    @classmethod
    def do_load(cls):
        ...<load-cfg-from-file>...

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

也许我误解了单例模式，但我的解决方案是简单实用的（Python？）。这段代码实现了两个目标

使Foo的实例可以在任何地方访问（全局）。Foo只能存在一个实例。

这就是代码。

#!/usr/bin/env python3

class Foo:
    me = None

    def __init__(self):
        if Foo.me != None:
            raise Exception('Instance of Foo still exists!')

        Foo.me = self


if __name__ == '__main__':
    Foo()
    Foo()

输出

Traceback (most recent call last):
  File "./x.py", line 15, in <module>
    Foo()
  File "./x.py", line 8, in __init__
    raise Exception('Instance of Foo still exists!')
Exception: Instance of Foo still exists!

赞成的意见这是一个真正的类Auto神奇地覆盖继承使用元类出于正当目的（并使我意识到）有吗？

这将是串行化的问题。如果您尝试从文件（pickle）反序列化对象，它将不使用__call__，因此将创建新文件，您可以使用__new__的基类继承来防止这种情况。

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()

这个解决方案在模块级别造成了一些命名空间污染（三个定义而不是一个），但我发现很容易理解。

我希望能够编写这样的东西（惰性初始化），但不幸的是，类在它们自己的定义体中不可用。

# wouldn't it be nice if we could do this?
class Foo(object):
    instance = None

    def __new__(cls):
        if cls.instance is None:
            cls.instance = object()
            cls.instance.__class__ = Foo
        return cls.instance

由于这是不可能的，我们可以在

Eagle初始化：

import random


class FooMaker(object):
    def __init__(self, *args):
        self._count = random.random()
        self._args = args


class Foo(object):
    def __new__(self):
        return foo_instance


foo_instance = FooMaker()
foo_instance.__class__ = Foo

延迟初始化：

Eagle初始化：

import random


class FooMaker(object):
    def __init__(self, *args):
        self._count = random.random()
        self._args = args


class Foo(object):
    def __new__(self):
        global foo_instance
        if foo_instance is None:
            foo_instance = FooMaker()
        return foo_instance


foo_instance = None