Python 2.6's multiprocessing lock not working on second use?

[Frédéric Sagnes]

On Jan 19, 11:53 am, Frédéric Sagnes <spee... at gmail.com> wrote:
> On Jan 17, 11:32 am, "Gabriel Genellina" <gagsl-... at yahoo.com.ar>
> wrote:
>
>
>
> > En Fri, 16 Jan 2009 14:41:21 -0200, escribiste en el grupo
> > gmane.comp.python.general
>
> > > I ran a few tests on the new Python 2.6multiprocessingmodule before
> > > migrating a threading code, and found out the locking code is not
> > > working well. In this case, a pool of 5 processes is running, each
> > > trying to get the lock and releasing it after waiting 0.2 seconds
> > > (action is repeated twice). It looks like themultiprocessinglock
> > > allows multiple locking after the second pass. Running the exact same
> > > code with threads works correctly.
>
> > I've tested your code on Windows and I think the problem is on the Queue
> > class. If you replace the Queue with some print statements or write to a
> > log file, the sequence lock/release is OK.
> > You should file a bug report onhttp://bugs.python.org/
>
> > --
> > Gabriel Genellina
>
> Thanks for your help gabriel, I just tested it without the queue and
> it works! I'll file a bug about the queues.
>
> Fred
>
> For those interested, the code that works (well, it always did, but
> this shows the real result):
>
> class test_lock_process(object):
>     def __init__(self, lock):
>         self.lock = lock
>         self.read_lock()
>
>     def read_lock(self):
>         for i in xrange(5):
>             self.lock.acquire()
>             logging.info('Got lock')
>             time.sleep(.2)
>             logging.info('Released lock')
>             self.lock.release()
>
> if __name__ == "__main__":
>     logging.basicConfig(format='[%(process)04d@%(relativeCreated)04d] %
> (message)s', level=logging.DEBUG)
>
>     lock = Lock()
>
>     processes = []
>     for i in xrange(2):
>         processes.append(Process(target=test_lock_process, args=
> (lock,)))
>
>     for t in processes:
>         t.start()
>
>     for t in processes:
>         t.join()

Opened issue #4999 [http://bugs.python.org/issue4999] on the matter,
referencing this thread.

--
Frédéric Sagnes