python-scoop

I am trying to get familiar with the library Scoop (documentation here: https://media.readthedocs.org/pdf/scoop/0.7/scoop.pdf ) to learn how to perform statistical computations in parallel, using in particular the futures.map function. As such, at first, I would like to try to run a simple linear regression, and assess the difference in performance between serial and parallel computations, using 10000000 data point (4 features, 1 target variable) randomly generated from a Normal Distribution. This is my code: import pandas as pd import numpy as np import random from scoop import futures import