Multiprocessing using the SCOOP library

Another approach to introduce multiprocessing is by utilizing SCOOP, a Python library designed to parallelize and distribute code execution across multiple processes. SCOOP, which stands for Simple COncurrent Operations in Python, provides a straightforward interface for parallel computing in Python, which we’ll explore shortly.

Applying SCOOP to a DEAP-based program is quite similar to using the multiprocessing.Pool module, as demonstrated by the Python 05_one_max_scoop.py program, available at https://github.com/PacktPublishing/Hands-On-Genetic-Algorithms-with-Python-Second-Edition/blob/main/chapter_13/05_one_max_scoop.py.

This program requires only a couple of modifications to the original non-multiprocessing version of the 02_one_max_busy.py program; these are outlined here:

1. Import SCOOP’s futures module:

   from scoop import futures

2. Register the map method of SCOOP’s futures module as the “map”...