How To Identify 3 Layer Combinations From Different Lists

I have two different lists (list1 and list2) of image datasets. I want to determine possible three feature combinations considering the integration of both lists, but not individua

Solution 1:

After gathering all the information required, my proposed solution is to use a product instead:

from itertools import product

def apply_op(list1, list2):
   part_1 = product(list1, list1, list2)
   part_2 = product(list1, list2, list2)
   return set(list(part_1)).union(set(list(part_2)))

print(apply_op(A, B))

EDIT: above solution doesn't work, since the result contains duplicate members in tuples.

def apply_op(list1, list2):
    ret = []
    for i in range(len(list1)):
        for j in range(i + 1, len(list1)):
            for k in range(len(list2)):
                ret.append((list1[i], list1[j], list2[k]))
    for i in range(len(list1)):
        for j in range(len(list2)):
            for k in range(j + 1, len(list2)):
                ret.append((list1[i], list2[j], list2[k]))
    return ret

print(apply_op(A, B))

Solution 2:

I am not sure what is exactly that you want, but if you want to merge two lists based on inputs in first lists, I suggest you to use dictionary. You can put element in list1 as key and put elements of list2 two in list, a value to that key. you can then use dictionary methods to update those value lists.