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Compiled Python Multiprocessing Locks CPU


Compiled Python Multiprocessing Locks CPU

By : user2954667
Date : November 22 2020, 10:31 AM
To fix this issue I cant answer about py2exe ... but pyinstaller this is a known problem with a well documented work around (that has always worked for me)
https://stackoverflow.com/a/27694505/541038
code :


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Python: Locks from `threading` and `multiprocessing` interchangable?

Python: Locks from `threading` and `multiprocessing` interchangable?


By : himanshu pareek
Date : March 29 2020, 07:55 AM
this one helps. You can typically use the two interchangeably, but you need to cognizant of the differences. For example, multiprocessing.Event is backed by a named semaphore, which is sensitive to the platform under the application.
Multiprocessing.Lock is backed by Multiprocessing.SemLock - so it needs named semaphores. In essence, you can use them interchangeably, but using multiprocessing's locks introduces some platform requirements on the application (namely, it doesn't run on BSD :))
Python Multiprocessing Locks

Python Multiprocessing Locks


By : Vijay B Verma
Date : March 29 2020, 07:55 AM
it should still fix some issue This multiprocessing code works as expected. It creates 4 Python processes, and uses them to print the numbers 0 through 39, with a delay after each print. , If you change pool.apply_async to pool.apply, you get this exception:
code :
Traceback (most recent call last):
  File "p.py", line 15, in <module>
    pool.apply(job, [l, i])
  File "/usr/lib/python2.7/multiprocessing/pool.py", line 244, in apply
    return self.apply_async(func, args, kwds).get()
  File "/usr/lib/python2.7/multiprocessing/pool.py", line 558, in get
    raise self._value
RuntimeError: Lock objects should only be shared between processes through inheritance
Why python multiprocessing manager produce threading locks?

Why python multiprocessing manager produce threading locks?


By : Ujjwala.CR
Date : October 28 2020, 11:27 AM
I think the issue was by ths following , Managed objects are always proxies; the goal of the manager is to make non-multiprocessing-aware objects into multiprocessing aware.
There is no point in doing this for multiprocessing.Lock() objects; these are implemented using semaphores and are fully multiprocessing capable without assistance.
Running a process from python module multiprocessing and kivy locks without answer

Running a process from python module multiprocessing and kivy locks without answer


By : Lasse Dalegaard
Date : March 29 2020, 07:55 AM
Hope this helps My problem, in fact, was with Spyder Development Environment and/or some of its components.
I was using the current IPython console to run my code, when I change to execute in an external terminal the problem was solved.
python multiprocessing self-feeding consumer locks forever

python multiprocessing self-feeding consumer locks forever


By : ae dev
Date : March 29 2020, 07:55 AM
may help you . Looks like a good sleep really helps, a refreshed mind can do much more.. Anyway, I found a solution after studying the python documentation.
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