Are there any practical differences between Options 1 and 2?
No. Option 2 looks nicer and might be marginally more efficient, but their net effect is the same.
run_until_completewill run until the future has completed, so since Option 1 is looping in a specific order I suppose it could behave differently if earlier tasks take longer to actually complete.
It seems that way at first, but it’s not actually the case because
loop.run_until_complete runs all tasks submitted to the loop, not just the one passed as argument. It merely stops once the provided awaitable completes – that is what “run until complete” refers to. A loop calling
run_until_complete over already scheduled tasks is like the following async code:
ts = [asyncio.create_task(asyncio.sleep(i)) for i in range(1, 11)] # takes 10s, not 55s for t in ts: await t
which is in turn semantically equivalent to the following threaded code:
ts =  for i in range(1, 11): t = threading.Thread(target=time.sleep, args=(i,)) t.start() ts.append(t) # takes 10s, not 55s for t in ts: t.join()
In other words,
await t and
run_until_complete(t) block until
t has completed, but allow everything else – such as tasks previously scheduled using
asyncio.create_task() to run during that time as well. So the total run time will equal the run time of the longest task, not of their sum. For example, if the first task happens to take a long time, all others will have finished in the meantime, and their awaits won’t sleep at all.
All this only applies to awaiting tasks that have been previously scheduled. If you try to apply that to coroutines, it won’t work:
# runs for 55s, as expected for i in range(1, 11): await asyncio.sleep(i) # also 55s - we didn't call create_task() so it's equivalent to the above ts = [asyncio.sleep(i) for i in range(1, 11)] for t in ts: await t # also 55s for i in range(1, 11): t = threading.Thread(target=time.sleep, args=(i,)) t.start() t.join()
This is often a sticking point for asyncio beginners, who write code equivalent to that last asyncio example and expect it to run in parallel.
I tried looking at the asyncio source code to understand if
asyncio.waitjust effectively does the same thing with its tasks/futures under the hood, but it wasn’t obvious.
asyncio.wait is just a convenience API that does two things:
- converts the input arguments to something that implements
Future. For coroutines that means that it submits them to the event loop, as if with
create_task, which allows them to run independently. If you give it tasks to begin with, as you do, this step is skipped.
add_done_callbackto be notified when the futures are done, at which point it resumes its caller.
So yes, it does the same things, but with a different implementation because it supports many more features.
I assume if one of the tasks is in the middle of a long-running blocking operation it may not actually cancel immediately?
In asyncio there shouldn’t be “blocking” operations, only those that suspend, and they should be cancelled immediately. The exception to this is blocking code tacked onto asyncio with
run_in_executor, where the underlying operation won’t cancel at all, but the asyncio coroutine will immediately get the exception.
Perhaps that just depends on if the underlying operation or library being used will raise the CancelledError right away or not?
The library doesn’t raise
CancelledError, it receives it at the await point where it happened to suspend before cancellation occurred. For the library the effect of the cancellation is
await ... interrupting its wait and immediately raising
CancelledError. Unless caught, the exception will propagate through function and
await calls all the way to the top-level coroutine, whose raising
CancelledError marks the whole task as cancelled. Well-behaved asyncio code will do just that, possibly using
finally to release OS-level resources they hold. When
CancelledError is caught, the code can choose not to re-raise it, in which case cancellation is effectively ignored.
Is it possible loop.run_until_complete (or really, the underlying call to
async.wait) returns values in unfinished for a reason other than a timeout?
If you’re using
return_when=asyncio.ALL_COMPLETE (the default), that shouldn’t be possible. It is quite possible with
return_when=FIRST_COMPLETED, then it is obviously possible independently of timeout.