CODEWITHSUNDEEP
pythonmultiprocessingconcurrent.futures
James
James

Reputation: 3231

Deadlock in concurrent.futures code

I've been trying to parallelise some code using concurrent.futures.ProcessPoolExecutor but have kept having strange deadlocks that don't occur with ThreadPoolExecutor. A minimal example:

from concurrent import futures

def test():
    pass

with futures.ProcessPoolExecutor(4) as executor:
    for i in range(100):
        print('submitting {}'.format(i))
        executor.submit(test)

In python 3.2.2 (on 64-bit Ubuntu), this seems to hang consistently after submitting all the jobs - and this seems to happen whenever the number of jobs submitted is greater than the number of workers. If I replace ProcessPoolExecutor with ThreadPoolExecutor it works flawlessly.

As an attempt to investigate, I gave each future a callback to print the value of i:

from concurrent import futures

def test():
    pass

with futures.ProcessPoolExecutor(4) as executor:
    for i in range(100):
        print('submitting {}'.format(i))
        future = executor.submit(test)

        def callback(f):
            print('callback {}'.format(i))
        future.add_done_callback(callback)

This just confused me even more - the value of i printed out by callback is the value at the time it is called, rather than at the time it was defined (so I never see callback 0 but I get lots of callback 99s). Again, ThreadPoolExecutor prints out the expected value.

Wondering if this might be a bug, I tried a recent development version of python. Now, the code at least seems to terminate, but I still get the wrong value of i printed out.

So can anyone explain:

EDIT: as jukiewicz pointed out below, of course printing i will print the value at the time the callback is called, I don't know what I was thinking... if I pass a callable object with the value of i as one of its attributes, that works as expected.

EDIT: a little bit more information: all of the callbacks are executed, so it looks like it is executor.shutdown (called by executor.__exit__) that is unable to tell that the processes have completed. This does seem to be completely fixed in the current python 3.3, but there seem to have been a lot of changes to multiprocessing and concurrent.futures, so I don't know what fixed this. Since I can't use 3.3 (it doesn't seem to be compatible with either the release or dev versions of numpy), I tried simply copying its multiprocessing and concurrent packages across to my 3.2 installation, which seems to work fine. Still, it seems a little weird that - as far as I can see - ProcessPoolExecutor is completely broken in the latest release version but nobody else is affected.

Upvotes: 6

Views: 6428

Answers (1)

bereal
bereal

Reputation: 34281

I modified the code as follows, that solved both problems. callback function was defined as a closure, thus would use the updated value of i every time. As for deadlock, that's likely to be a cause of shutting down the Executor before all the task are complete. Waiting for the futures to complete solves that, too. 

from concurrent import futures

def test(i):
    return i

def callback(f):
    print('callback {}'.format(f.result()))


with futures.ProcessPoolExecutor(4) as executor:
    fs = []
    for i in range(100):
        print('submitting {}'.format(i))
        future = executor.submit(test, i)
        future.add_done_callback(callback)
        fs.append(future)

    for _ in futures.as_completed(fs): pass

UPDATE: oh, sorry, I haven't read your updates, this seems have been solved already.

Upvotes: 3

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