Dummy example of process parallelization in Python

parallelize.py

from multiprocessing import Pool, cpu_count

cores = cpu_count()

# whatever parameters or stuff you want to iterate over to run them on your job (function call)
parameters = [0, 1, 2, 3]


def job(iter):
    # the code you want to parallelize
    print(iter)


# this iterable list is actually not necessary if no other parameter is passed (so parameters could be used instead)
# but you can pass another parameter by using tuples, for example iterable = [(dataset, param) for param in parameters]
# then you should "unpack" your tuple inside your job function, i.e. iter[0] and iter[1], to use the values in there
iterable = [parameter for parameter in parameters]
pool = Pool(processes=cores)
pool.map(job, iterable)
pool.close()