Try to convince those "Data Scientists" to learn Julia/Rust or spend another ten years for learning how to write non-crashy C++ then. Also, IMO Python is the r

Try to convince those "Data Scientists" to learn Julia/Rust or spend another ten years for learning how to write non-crashy C++ then. Also, IMO Python is the right tool for glueing optimized C++ implementation of various linalg algos together. And this is exactly how we use Python. And we still have to workaround GIL. Yes, it is that bad. <rant> Glue codes could be slow, but they must scale. They should not unnecessarily contend for a stupid lock. GIL is really a scalability bug and I do acknowledge it is a hard-to-fix one due to the world's legacy codebases depends on it. However when someone applies an absurd amount of computer science (the design OP posted is literally based on state-of-the-art PL research), you should at least be sincerely curious why people are being so serious about it. </rant>