numpy wiki summaries that well [1]. Too many things especially with complex math cannot run in parallel unless one spends a lot of time on workarounds. One sta

numpy wiki summaries that well [1]. Too many things especially with complex math cannot run in parallel unless one spends a lot of time on workarounds. One starts with quick and dirty solution, makes it work on a small dataset and then struggle to make it utilize at least 4 cores to cut running time with more realist datasets. Surelly I can code numerical calculations in C++, but then the code cannot be maintained by python-only guy. So I hope that Julia or anything else with better parallel support replaces Python for scientific calculations when scaling quick and dirty solutions is straightforward. [1] http://scipy-cookbook.readthedocs.io/items/ParallelProgramming.html http://scipy-cookbook.readthedocs.io/items/ParallelProgrammi...