use tuple products and parallel map.py

tuple_parallel_map.py

import numpy as np
from itertools import product
from multiprocessing import Pool


def smash(a_tuple):
    """
    smash some strings and numbers together and return final string
    """
    return a_tuple[0] + str(a_tuple[1]) + a_tuple[2] + str(a_tuple[3])


location_string = "location_"
location_list = np.arange(0, 3)
item_string = "_product_"
item_list = np.arange(0, 3)
product_location_X_item = list(
    product([location_string], location_list, [item_string], item_list)
)
# prod = list(map(smash, product_location_X_item))
# print(prod)

# easy conversion to parallel
with Pool() as P:
    parallel_prod = list(P.map(smash, product_location_X_item))
print(parallel_prod)