`fork` is a bad option for multiprocessing

C.f. https://pythonspeed.com/articles/faster-multiprocessing-pickle/

Python’s multiprocessing default option has been fork() when it is available. This might be the reason why I’ve had random crashes for different python version: If you have code which launches threads, then use a fork() operation, the code can freeze, deadlock or cause corrupted memory.

The child process resulting from fork() has all the data that was in memory for the parent, but it doesn’t copy any threads. You can see this by running

import threading
from os import fork
from time import sleep

# Start a thread:
threading.Thread(target=lambda: sleep(60)).start()

if fork():
    print("The parent process has {} threads".format(
    print("The child process has {} threads".format(

which will show 2 theads for the parent and 1 threads for the child.

The alternative is to use spawn, which doesn’t copy anything over (and is described as “slower”, but that seems like it shouldn’t be an issue if your problem is large).

import multiprocessing
from concurrent.futures import ProcessPoolExecutor
# 1. 
ProcessPoolExecutor(max_workers=n, mp_context=multiprocessing.get_context("spawn"))
# 2. with Pool
with multiprocessing.get_context("spawn").Pool() as pool:

The downside is you’ll need to make sure you copy everything you need to the other processes… but that should be explicit anyway.