anst

Many thanks! Incredibly versatile implementation.

Time to go amd, poor old me, Intel MB Air 2018 (zsh: exec format error, Darwin Kernel Version 22.2.0, MacOS Ventura 13.1).

On my old Mac: Python=133.5 s, Numba=2.61 s (parallel prange in count_primes), Taichi=1.8 s. (on ti.cpu, but fails with metal).

In a winner-takes-all finite world a tipping point may never happen...

Yeah, stir some mysterious ideas, maybe someone sees there a meaning. Quite surprised with this kind of vague magical thinking coming from lesswrong (thought they were rationalists or something).

Python + Jupyter OK, but pandas actually reads everything at once, doesn’t it. 100MB is no problem but bigger files could result in high swapping pression.

A really interesting collection for teaching Data Science. But the "WorkshopScipy" and the "scientific computation" make reference to something like scipy.org. It seems that this repo has different interests.