Category : python-multiprocessing

I want to perform a parallel get_item dynamodb operation to save processing time. def get_carrier(segments, slice_id): segments = get_slice_segments(segments, slice_id) with Pool(processes=len(segments)) as pool: distances = pool.map(getDistanceDynamodb, segments) return distances My problem is that i want to cache the dynamoDB item because I am expecting a lot of requests so it would also help to ..

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I’m trying to parallelize a piece of code given below using the mupltiprocessing module. Everything I try leads to each child process being run one after the other even though they all have different PIDs. I have tried: CentOS and MacOS Context as spawn and as fork Using Queues and using pools Using Apply and ..

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