Granted, but I already have to run isolated container registries, pypi, maven, terraform, CI/CD, etc., etc., and so locally addressing the problems you've described is unavoidable and will realize significant efficiencies in any case. Everything about working in partially or fully air gapped environments is painful - no surprises there.

But I also think it's fine for individuals and researchers working in ML to expect some extra compiling, as long as the outcome is reliable. I'm stuck at home this weekend resurrecting an analysis from 10+ years ago, complete with Python, R, Java, and Fortran dependencies^, and I'm definitely wishing I'd known about Nix back then.

^btw, thanks to whomever included hdf5-mpi in Nixpkgs. Your work is greatly appreciated.