Scalene does not seem to work with multiprocessing

[makmanalp]

Describe the bug

Scalene does not seem to collect profiling data from subprocesses forked by multiprocessing.

To Reproduce

Run this:

import multiprocessing as mp

def fun(args):
    return args

if __name__ == "__main__":
    p = mp.Pool(mp.cpu_count())
    r = p.map(fun, range(1000000))
    print(sum(x for x in r))
    print(((1000000-1) * 1000000) / 2)

in scalene via python3 -m scalene scalenetest.py

Expected behavior

Expect to see line profiler show stats from inside the function fun(), gathered from the subprocesses. What happens instead is that I get a profile that shows that the bulk of the time is spent in the main process waiting for the subprocesses to complete.

Screenshots

Desktop (please complete the following information):

• OS: OSX Ventura 13.6.6
• Python: Python 3.12.2
• Scalene: Scalene version 1.5.38 (2024.03.24) - also tried repository version

Additional context
Add any other context about the problem here.