Parallelize data processing

parallelize.py

# install job lib

from joblib import Parallel, delayed
import numpy as np

def myfun(p):
    return np.linalg.norm(p[0]-p[1])

X = [1,2,3,4]
Y = [6,4,8,1]

element = [(x, y) for x in X for y in Y]

results = Parallel(n_jobs=-1, verbose=1, backend="threading")(map(delayed(myfun), element))
print(results)