I’m trying to parallelize my python script by using a process Pool of 4 workers from the multiprocessing module. This error seems to suggest that too many pipes are opening, but I fail to see how this is the case, given that I only spawn 4 workers.

I’m trying to parallelize my python script by using a process Pool of 4 workers from the multiprocessing module. This error seems to suggest that too many pipes are opening, but I fail to see how this is the case, given that I only spawn 4 workers.

This question already has answers here: multiprocessing problem [pyqt, py2exe] (3 answers) Closed last year. I just discovered a bizarre bug in my program related to its use of Python’s multiprocessing module. Everything works fine when I run the program from the source on my machine. But I’ve been building it into an executable using […]

import multiprocessing from PIL import Image name = input(“Enter the file name: “) def decode_file(filename): with open(filename, mode=’rb’) as file: binary_data = file.read() binary_list = [] for byte in binary_data: binary_list.append(format(byte, ’08b’)) return binary_list binary_list = decode_file(name) l = len(binary_list) no_of_bytes = l // 8 def make_row_list(): row_list = [] for i in range(0, l, […]

After using a Pool from Python’s multiprocessing to parallelize some computationally intensive work, I wish to retrieve statistics that were kept local to each spawned process. Specifically, I have no real-time interest in these statistics, so I do not want to bear the overhead that would be involved with using a synchronized data structure in which statistics could be kept.

For each line of a text file I want to do heavy calculations. The amount of lines can be millions so I’m using multiprocessing:

For each line of a text file I want to do heavy calculations. The amount of lines can be millions so I’m using multiprocessing:

I have this code, it generates 2,000,000 points uniformly distributed in a bounding box and does some calculations to partition the points based on some criteria.

I am in the process of processing a list of arrays, and this is a workflow that could be parallelised as multiple points: One thread for each dataset in the list, and multiple threads each to handle the different slices in the array.

I’m encountering an issue with a multiprocessing script in Python. The script processes flights using a function process_one_flight . Individually, each step of the function works as expected, but when executed via multiprocessing workers, the script occasionally gets stuck at random steps of the process_one_flight function.. I have been unable to reproduce the bug in a consistent manner, which complicates troubleshooting.