How To Speed Up Nested For-loop Logic In Python With Pandas, Numpy?

I would like to check out whether the field of table TestProjectcontains the parameter from the Client-side passed, nested for loop is ugly, is there any efficient and easy way to

Solution 1:

May be use itertools.product and all?

from itertools import product

def test(parameter_a: list, parameter_b: list) -> bool:
    age = TestPeople.ageproject_code= TestProject.project_code
    return(
        age is None 
        or age > 16
        or all(code.startswith(p)for code, p in product(project_code, parameter_a))
    )

EXPLANATION:

Here python tries to use short-circuit evaluation, so it will first check whether age is None, if it is, return True, otherwise check age > 16, if it is return True otherwise check if all the code, p pair match the condition code.startswith(p), if all the pairs pass the condition, return True, otherwise if any of the pair fail, return False immediately without checking the rest.