The post is about using numpy or pypy to get better speed in python since in python for is slow. That is well known, is like the well known fact that you should use vectorized operations in R to get better performance. Anyway there is something interesting: The problem of given a point P0 as input, find the the nearest point to P0 among a fixed billion points (all of them on a sphere) can be solved easily and quickly. You should be surprised the code a mathematician could devise to solve this.