Shared queue contents not visible in Python multiprocessing

I have a few coroutines running on one process (A) and one heavier unbounded job running on a separate process(B). I would like that heavier job to dispatch its results into a queue which is consumed by the original process (A). Similar to this: import asyncio import time from concurrent.futures import ProcessPoolExecutor def process__heavy(pipe): print("[B]… Read More Shared queue contents not visible in Python multiprocessing

Returning results is very slow in multiprocess code. What should I do?

No multiprocessing code: from time import time func1Results = [] def func1(valList): num = 0 for val in valList: num += val func1Results.append(num) if __name__ == ‘__main__’: st = time() for valList in [range(40000000), range(40000000), range(40000000), range(40000000)]: func1(valList) ed = time() for r in func1Results: print(r) print(ed – st) Output: 799999980000000 799999980000000 799999980000000 799999980000000 13.679119348526001… Read More Returning results is very slow in multiprocess code. What should I do?

Python Multiprocessing not running simultaneously

Let’s say I have this simple function: def print_name(name): print(name) time.sleep(10) print(‘finished sleeping @ ‘, str(dt.datetime.now())) I’m trying to use multiprocessing to run this in a loop for several names all at once, like in the below: from multiprocessing.pool import ThreadPool as Pool names = [‘A’,’B’,’C’,’D’,’E’] with Pool() as pool: for name in names: pool.map(print_name,[name])… Read More Python Multiprocessing not running simultaneously