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()