Classified permutations using itertools or numpy

Question

I have a series of dimensions which can take discrete values.

For instance, say I have 4 dimensions each containing a keyword from a dimension-specific list:

color: black, blue, red, green, yellow
size: xs, s, m, l, xl
material: leather, fabric, cotton, wool
gender: male, female

I want to iterate and do some stuff through every possible combination of those dimensions' values.

Is there a way to do this with itertools or numpy assuming two different cases?

• If each dimension can have only one keyword
• If each dimension can have one or several keywords

Answer 1

Have you tried itertools.product(*iterables)? Sounds like it's what you're looking for.

The function takes as many iterables as you want and makes a Cartesian product. Here is an example:

import itertools

dimension1 = range(3)
dimension2 = ['a']
dimension3 = ['hello', 'world']

for res in itertools.product(dimension1, dimension2, dimension3):
    print(*res)

Output:

0 a hello
0 a world
1 a hello
1 a world
2 a hello
2 a world