from random import randint
import numpy as np

def dist1(loc, other_loc):
	return (loc[0]-other_loc[0])**2 + (loc[1]-other_loc[1])**2 + (loc[2]-other_loc[2])**2
	
def yield_pts(n):
	
	for i in range(0,n):
		p1 = (10000-randint(0,20000), 10000-randint(0,20000), 10000-randint(0,20000))
		p2 = (10000-randint(0,20000), 10000-randint(0,20000), 10000-randint(0,20000))
		
		yield p1, p2
		
		
def native(ptlst):
	return [dist1(p[0], p[1]) for p in ptlst]

def fast(x1s, y1s, z1s, x2s, y2s, z2s):
	
	p1 = np.array([x1s, y1s, z1s])
	p2 = np.array([x2s, y2s, z2s])
		
	squared_dist = np.sum((p1-p2)**2, axis=0)
	return np.sqrt(squared_dist)

import cProfile

ptlst = [(p1, p2) for (p1, p2) in yield_pts(41000*5*10)]
cProfile.runctx("native(ptlst)", globals(), locals())


n=41000*5*10
x1s = [10000-randint(0,20000) for i in range(0, n)]
y1s = [10000-randint(0,20000) for i in range(0, n)]
z1s = [10000-randint(0,20000) for i in range(0, n)]
x2s = [10000-randint(0,20000) for i in range(0, n)]
y2s = [10000-randint(0,20000) for i in range(0, n)]
z2s = [10000-randint(0,20000) for i in range(0, n)]
cProfile.runctx("fast(x1s, y1s, z1s, x2s, y2s, z2s)", globals(), locals())