nimpylib

Another nim & python thread that has not been mentioned yet here https://news.ycombinator.com/item?id=28506531 - project allows creating pythonic bindings for your nim libraries pretty easily, which can be useful if you still want to write most of your toplevel code in python, but leverage nim's speed when it matters. If you want to make your nim code even more "pythonic" there is a https://github.com/Yardanico/nimpylib, and for calling some python code from nim there is a https://github.com/yglukhov/nimpy

I have never written anything “production” grade with Julia, so do take my opinion with a grain of salt. However, I did once try to translate a simple algorithm library from Python into both Nim and Julia. Julia was no faster than Python with my initial naive implementation. After consulting the forum and getting help, I did manage to get it running fast. My impression of Julia is that it can be incredibly fast but it takes work to get to that stage. In contrast, with Nim, my code looked nearly identical to my Python code (i.e. quite simple) and ran fast from the start. This has been my general impression of Nim after doing a few projects in it: you write clean, readable code and get fast code out. There is no step 2. With respect to numerical algorithms, Nim has good support for BLAS and LAPACK. I personally haven’t used them, so I can’t