我一直是这样做的:

class Event(list):
    """Event subscription.

    A list of callable objects. Calling an instance of this will cause a
    call to each item in the list in ascending order by index.

    Example Usage:
    >>> def f(x):
    ...     print 'f(%s)' % x
    >>> def g(x):
    ...     print 'g(%s)' % x
    >>> e = Event()
    >>> e()
    >>> e.append(f)
    >>> e(123)
    f(123)
    >>> e.remove(f)
    >>> e()
    >>> e += (f, g)
    >>> e(10)
    f(10)
    g(10)
    >>> del e[0]
    >>> e(2)
    g(2)

    """
    def __call__(self, *args, **kwargs):
        for f in self:
            f(*args, **kwargs)

    def __repr__(self):
        return "Event(%s)" % list.__repr__(self)

然而，就像我看到的其他东西一样，没有自动生成的pydoc，也没有签名，这真的很糟糕。

我一直是这样做的:

class Event(list):
    """Event subscription.

    A list of callable objects. Calling an instance of this will cause a
    call to each item in the list in ascending order by index.

    Example Usage:
    >>> def f(x):
    ...     print 'f(%s)' % x
    >>> def g(x):
    ...     print 'g(%s)' % x
    >>> e = Event()
    >>> e()
    >>> e.append(f)
    >>> e(123)
    f(123)
    >>> e.remove(f)
    >>> e()
    >>> e += (f, g)
    >>> e(10)
    f(10)
    g(10)
    >>> del e[0]
    >>> e(2)
    g(2)

    """
    def __call__(self, *args, **kwargs):
        for f in self:
            f(*args, **kwargs)

    def __repr__(self):
        return "Event(%s)" % list.__repr__(self)

然而，就像我看到的其他东西一样，没有自动生成的pydoc，也没有签名，这真的很糟糕。

下面是另一个需要考虑的模块。对于要求更高的应用程序，这似乎是一个可行的选择。

Py-notify is a Python package providing tools for implementing Observer programming pattern. These tools include signals, conditions and variables. Signals are lists of handlers that are called when signal is emitted. Conditions are basically boolean variables coupled with a signal that is emitted when condition state changes. They can be combined using standard logical operators (not, and, etc.) into compound conditions. Variables, unlike conditions, can hold any Python object, not just booleans, but they cannot be combined.

如果你想做更复杂的事情，比如合并事件或重试，你可以使用Observable模式和一个成熟的库来实现它。https://github.com/ReactiveX/RxPY。可观察对象在Javascript和Java中非常常见，在一些异步任务中使用非常方便。

from rx import Observable, Observer


def push_five_strings(observer):
        observer.on_next("Alpha")
        observer.on_next("Beta")
        observer.on_next("Gamma")
        observer.on_next("Delta")
        observer.on_next("Epsilon")
        observer.on_completed()


class PrintObserver(Observer):

    def on_next(self, value):
        print("Received {0}".format(value))

    def on_completed(self):
        print("Done!")

    def on_error(self, error):
        print("Error Occurred: {0}".format(error))

source = Observable.create(push_five_strings)

source.subscribe(PrintObserver())

输出:

Received Alpha
Received Beta
Received Gamma
Received Delta
Received Epsilon
Done!

我对Longpoke的极简主义方法做了一个变化，也确保了呼叫者和呼叫者的签名:

class EventHook(object):
    '''
    A simple implementation of the Observer-Pattern.
    The user can specify an event signature upon inizializazion,
    defined by kwargs in the form of argumentname=class (e.g. id=int).
    The arguments' types are not checked in this implementation though.
    Callables with a fitting signature can be added with += or removed with -=.
    All listeners can be notified by calling the EventHook class with fitting
    arguments.

    >>> event = EventHook(id=int, data=dict)
    >>> event += lambda id, data: print("%d %s" % (id, data))
    >>> event(id=5, data={"foo": "bar"})
    5 {'foo': 'bar'}

    >>> event = EventHook(id=int)
    >>> event += lambda wrong_name: None
    Traceback (most recent call last):
        ...
    ValueError: Listener must have these arguments: (id=int)

    >>> event = EventHook(id=int)
    >>> event += lambda id: None
    >>> event(wrong_name=0)
    Traceback (most recent call last):
        ...
    ValueError: This EventHook must be called with these arguments: (id=int)
    '''
    def __init__(self, **signature):
        self._signature = signature
        self._argnames = set(signature.keys())
        self._handlers = []

    def _kwargs_str(self):
        return ", ".join(k+"="+v.__name__ for k, v in self._signature.items())

    def __iadd__(self, handler):
        params = inspect.signature(handler).parameters
        valid = True
        argnames = set(n for n in params.keys())
        if argnames != self._argnames:
            valid = False
        for p in params.values():
            if p.kind == p.VAR_KEYWORD:
                valid = True
                break
            if p.kind not in (p.POSITIONAL_OR_KEYWORD, p.KEYWORD_ONLY):
                valid = False
                break
        if not valid:
            raise ValueError("Listener must have these arguments: (%s)"
                             % self._kwargs_str())
        self._handlers.append(handler)
        return self

    def __isub__(self, handler):
        self._handlers.remove(handler)
        return self

    def __call__(self, *args, **kwargs):
        if args or set(kwargs.keys()) != self._argnames:
            raise ValueError("This EventHook must be called with these " +
                             "keyword arguments: (%s)" % self._kwargs_str())
        for handler in self._handlers[:]:
            handler(**kwargs)

    def __repr__(self):
        return "EventHook(%s)" % self._kwargs_str()

如果你需要一个跨进程或网络边界的事件总线，你可以尝试PyMQ。它目前支持发布/订阅、消息队列和同步RPC。默认版本工作在一个Redis后端，所以你需要一个运行的Redis服务器。还有一个用于测试的内存后端。您还可以编写自己的后端。

import pymq

# common code
class MyEvent:
    pass

# subscribe code
@pymq.subscriber
def on_event(event: MyEvent):
    print('event received')

# publisher code
pymq.publish(MyEvent())

# you can also customize channels
pymq.subscribe(on_event, channel='my_channel')
pymq.publish(MyEvent(), channel='my_channel')

初始化系统。

from pymq.provider.redis import RedisConfig

# starts a new thread with a Redis event loop
pymq.init(RedisConfig())

# main application control loop

pymq.shutdown()

声明:我是这个库的作者