Python协同程序

Question

I have a little bit of experience with promises in Javascript. I am quite experienced with Python, but new to its coroutines, and there is a bit that I just fail to understand: where does the asynchronicity kick in?

Let's consider the following minimal example:

async def gen():
    await something
    return 42

As I understand it, await something puts execution of our function aside and lets the main program run other bits. At some point something has a new result and gen will have a result soon after.

If gen and something are coroutines, then by all internet wisdom they are generators. And the only way to know when a generator has a new item available, afaik, is by polling it: x=gen(); next(x) x=gen(); next(x) . But this is blocking! How does the scheduler "know" when x has a result? The answer can't be "when something has a result" because something must be a generator, too (for it is a coroutine). And this argument applies recursively.

I can't get past this idea that at some point the process will just have to sit and wait synchronously.

Answer 1

The secret sauce here is the asyncio module . Your something object has to be an awaitable object itself, and either depend on more awaitable objects, or must yield from a Future object .

For example, the asyncio.sleep() coroutine yields a Future :

@coroutine
def sleep(delay, result=None, *, loop=None):
    """Coroutine that completes after a given time (in seconds)."""
    if delay == 0:
        yield
        return result

    if loop is None:
        loop = events.get_event_loop()
    future = loop.create_future()
    h = future._loop.call_later(delay,
                                futures._set_result_unless_cancelled,
                                future, result)
    try:
        return (yield from future)
    finally:
        h.cancel()

(The syntax here uses the older generator syntax, to remain backwards compatible with older Python 3 releases).

Note that a future doesn't use await or yield from ; they simply use yield self until some condition is met . In the above async.sleep() coroutine, that condition is met when a result has been produced (in the async.sleep() code above, via the futures._set_result_unless_cancelled() function called after a delay).

An event loop then keeps pulling in the next 'result' from each pending future it manages (polling them efficiently) until the future signals it is done (by raising a StopIteration exception holding the results; return from a co-routine would do that, for example). At that point the coroutine that yielded the future can be signalled to continue (either by sending the future result, or by throwing an exception if the future raised anything other than StopIteration ).

So for your example, the loop will kick off your gen() coroutine, and await something then (directly or indirectly) yields a future. That future is polled until it raises StopIteration (signalling it is done) or raises some other exception. If the future is done, coroutine.send(result) is executed, allowing it to then advance to the return 42 line, triggering a new StopIteration exception with that value, allowing a calling coroutine awaiting on gen() to continue, etc.