def manhattan_distance(point_a: list, point_b: list) -> float: """ Expectts two list of numbers representing two points in the same n-dimensional space https://en.wikipedia.org/wiki/Taxicab_geometry >>> manhattan_distance([1,1], [2,2]) 2.0 >>> manhattan_distance([1.5,1.5], [2,2]) 1.0 >>> manhattan_distance([1.5,1.5], [2.5,2]) 1.5 >>> manhattan_distance([-3, -3, -3], [0, 0, 0]) 9.0 >>> manhattan_distance([1,1], None) Traceback (most recent call last): ... ValueError: Missing an input >>> manhattan_distance([1,1], [2, 2, 2]) Traceback (most recent call last): ... ValueError: Both points must be in the same n-dimensional space >>> manhattan_distance([1,"one"], [2, 2, 2]) Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found str >>> manhattan_distance(1, [2, 2, 2]) Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found int >>> manhattan_distance([1,1], "not_a_list") Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found str """ _validate_point(point_a) _validate_point(point_b) if len(point_a) != len(point_b): raise ValueError("Both points must be in the same n-dimensional space") return float(sum(abs(a - b) for a, b in zip(point_a, point_b))) def _validate_point(point: list[float]) -> None: """ >>> _validate_point(None) Traceback (most recent call last): ... ValueError: Missing an input >>> _validate_point([1,"one"]) Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found str >>> _validate_point(1) Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found int >>> _validate_point("not_a_list") Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found str """ if point: if isinstance(point, list): for item in point: if not isinstance(item, (int, float)): raise TypeError( f"Expected a list of numbers as input, " f"found {type(item).__name__}" ) else: raise TypeError( f"Expected a list of numbers as input, found {type(point).__name__}" ) else: raise ValueError("Missing an input") def manhattan_distance_one_liner(point_a: list, point_b: list) -> float: """ Version with one liner >>> manhattan_distance_one_liner([1,1], [2,2]) 2.0 >>> manhattan_distance_one_liner([1.5,1.5], [2,2]) 1.0 >>> manhattan_distance_one_liner([1.5,1.5], [2.5,2]) 1.5 >>> manhattan_distance_one_liner([-3, -3, -3], [0, 0, 0]) 9.0 >>> manhattan_distance_one_liner([1,1], None) Traceback (most recent call last): ... ValueError: Missing an input >>> manhattan_distance_one_liner([1,1], [2, 2, 2]) Traceback (most recent call last): ... ValueError: Both points must be in the same n-dimensional space >>> manhattan_distance_one_liner([1,"one"], [2, 2, 2]) Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found str >>> manhattan_distance_one_liner(1, [2, 2, 2]) Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found int >>> manhattan_distance_one_liner([1,1], "not_a_list") Traceback (most recent call last): ... TypeError: Expected a list of numbers as input, found str """ _validate_point(point_a) _validate_point(point_b) if len(point_a) != len(point_b): raise ValueError("Both points must be in the same n-dimensional space") return float(sum(abs(x - y) for x, y in zip(point_a, point_b))) if __name__ == "__main__": import doctest doctest.testmod()