nimhdf5 VS flambeau

While indeed we are less people developing stuff in Nim compared to even the Julia community (which itself is of course much smaller than say Python), we do have cover a large amount of the typical needs in the scientific computing domain. And where we miss stuff it's a) easy to wrap C/C++ or b) simply call Julia, R or Python (As a personal reference I'm doing data analysis & numerical physics stuff in context of my PhD in physics and I literally do everything in Nim. The only significant C dependency {and only as a shared lib} I depend on is libhdf5 via nimhdf5).

In particular for deep learning as bobsyourunkl already mentioned there is arraymancer on the one hand and also flambeau on the other. The latter is a Nim wrapper around libtorch (i.e. the PyTorch C++ backend). It is missing things (to be wrapped by adding a few lines) and has some rough edges, but if one needs to get stuff done, it's possible.

That’s one thing I like about Nim. It can compile to C++ and so can directly wrap C++ code. While Nim’s ecosystem is small it’s easy enough to wrap most any C/C++ library. It’s great for OpenCV. Some folks have been updating direct PyTorch C++ api (1)!

1: https://github.com/SciNim/flambeau