Efficient and precise calculation of the euclidean distance

Question

Following some online research (1, 2, numpy, scipy, scikit, math), I have found several ways for calculating the Euclidean Distance in Python:

Answer 1

I don't know how the precision and speed compares to the other libraries you mentioned, but you can do it for 2D vectors using the built-in math.hypot() function:

from math import hypot

def pairwise(iterable):
    "s -> (s0, s1), (s1, s2), (s2, s3), ..."
    a, b = iter(iterable), iter(iterable)
    next(b, None)
    return zip(a, b)

a = (52, 106, 35, 12)
b = (33, 153, 75, 10)

dist = [hypot(p2[0]-p1[0], p2[1]-p1[1]) for p1, p2 in pairwise(tuple(zip(a, b)))]
print(dist)  # -> [131.59027319676787, 105.47511554864494, 68.94925670375281]