python joblib Parallel on Windows not working even "if __name__ == '__main__':" is added

According to this site the problem is Windows specific:

Yes: under linux we are forking, thus their is no need to pickle the function, and it works fine. Under windows, the function needs to be pickleable, ie it needs to be imported from another file. This is actually good practice: making modules pushes for reuse.

I've tried your code and it works flawlessly under Linux.Under Windows it runs OK if it is run from a script, like python script_with_your_code.py. But it fails when ran in an interactive python session. It worked for me when I saved the f function in separate module and imported it into my interactive session.

NOT WORKING:
Interactive session:

>>> from math import sqrt>>> from joblib import Parallel, delayed>>> def f(x):...     return sqrt(x)>>> if __name__ == '__main__':...     a = Parallel(n_jobs=2)(delayed(f)(i) for i in range(10))...Process PoolWorker-1:Traceback (most recent call last):  File "C:\Python27\lib\multiprocessing\process.py", line 258, in _bootstrap    self.run()  File "C:\Python27\lib\multiprocessing\process.py", line 114, in run    self._target(*self._args, **self._kwargs)  File "C:\Python27\lib\multiprocessing\pool.py", line 102, in worker    task = get()  File "C:\Python27\lib\site-packages\joblib\pool.py", line 359, in get    return recv()AttributeError: 'module' object has no attribute 'f'

WORKING:
fun.py

from math import sqrtdef f(x):    return sqrt(x)

Interactive session:

>>> from joblib import Parallel, delayed>>> from fun import f>>> if __name__ == '__main__':...     a = Parallel(n_jobs=2)(delayed(f)(i) for i in range(10))...>>> a[0.0, 1.0, 1.4142135623730951, 1.7320508075688772, 2.0, 2.23606797749979, 2.449489742783178, 2.6457513110645907, 2.8284271247461903, 3.0]

Joblib is working on my Windows 10 when I am using the version 1.19.5 of numpy. I upgraded all outdated package; to do that you can run the following command:

pip list --outdatedpip install --upgrade

or you use pip_upgrade_outdated which upgrades all outdated packages by doing pip install pip-upgrade-outdated and pip-upgrade-outdated according this this site