On Nov 2, 2013, at 11:44 AM, Sherard Hall <smhal...@gmail.com> wrote:
> Thank you for the response. Processing time is very important so I suspect
> having to write to disk will take more time than letting the other processes
> complete without finding the answer. So I did some profiling one process
> finds the answer in about 250ms, but since I can't stop the other processes,
> it takes about 800ms before I can use the answer. Do you recommend a global
> variable flag? Any other suggestions?
>
> On Nov 2, 2013 8:17 AM, "William Ray Wing" <w...@mac.com> wrote:
> On Nov 2, 2013, at 1:03 AM, smhall05 <smhal...@gmail.com> wrote:
>
> > On Friday, November 1, 2013 10:52:40 PM UTC-4, MRAB wrote:
> >> On 02/11/2013 02:35, smhall05 wrote:
> >>
> >>> I am using a basic multiprocessing snippet I found:
> >>>
> >>> #-----------------------------------------------------
> >>> from multiprocessing import Pool
> >>>
> >>> def f(x):
> >>> return x*x
> >>>
> >>> if __name__ == '__main__':
> >>> pool = Pool(processes=4) # start 4 worker processes
> >>> result = pool.apply_async(f, [10]) # evaluate "f(10)"
> >>> asynchronously
> >>> print result.get(timeout=1)
> >>> print pool.map(f, range(10)) # prints "[0, 1, 4,..., 81]"
> >>> #---------------------------------------------------------
> >>>
> >>> I am using this code to have each process go off and solve the same
> >>> problem, just with different inputs to the problem. I need to be able to
> >>> kill all processes once 1 of n processes has come up with the solution.
> >>> There will only be one answer.
> >>>
> >>> I have tried:
> >>>
> >>> sys.exit(0) #this causes the program to hang
> >>> pool.close()
> >>> pool.terminate
> >>>
> >>
> >> Did you actually mean "pool.terminate", or is that a typo for
> >>
> >> "pool.terminate()"?
> >>
> >>> These still allow further processing before the program terminates. What
> >>> else can I try? I am not able to share the exact code at this time. I can
> >>> provide more detail if I am unclear. Thank you
> >>>
> >
> > I am not sure to be honest, however it turns out that I can't use
> > pool.terminate() because pool is defined in main and not accessible under
> > my def in which I check for the correct answer.
> > --
> > https://mail.python.org/mailman/listinfo/python-list
>
> So, the simplest solution to that situation is to have whichever subprocess
> that finds the correct answer set a flag which the calling process can check.
> Depending on your OS, that flag can be anything from setting a lock to
> something as simple as creating a file which the calling process periodically
> wakes up and looks for, maybe just a file in which the subprocess has written
> the answer.
>
> Bill
>
> --
> https://mail.python.org/mailman/listinfo/python-list
Well, the multiprocessing library provides listeners and clients that wrap BSD
style sockets and allow you to send (push) arbitrary python objects to a
listener, i.e., the master. There might be something better that was OS
specific, but this will keep it pure python. I've not tested it, but there is
a simple example here on Stackoverflow:
http://stackoverflow.com/questions/6920858/interprocess-communication-in-python
-Bill
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