nalgebra

Rust has amazing integration with Python through PyO3 [1] so see it like a safe alternative for high performance calculations and operations. The rust data science ecosystem itself is starting to come together with projects like Polars [2] (Pandas alternative), nalgebra [3], Datafusion [4] and Ballista [5]. Of course nowhere near Python but that is hard to beat today. [1] https://github.com/PyO3/pyo3 [2] https://github.com/pola-rs/polars/ [3] https://github.com/dimforge/nalgebra [4] https://github.com/apache/arrow-datafusion [5] https://github.com/apache/arrow-ballista

I would add also nlgebra[1] and Simba[2]. [1] https://github.com/dimforge/nalgebra [2] https://github.com/dimforge/simba

Thanks! Rusty-machine doesn't really solve the same problems as leaf so there would certainly be some value in both existing. I agree on the linear algebra front too! I think it's well worth investing time into. Though - there are some other alternatives you may want to check out: nalgebra: https://github.com/sebcrozet/nalgebra ndarray: https://github.com/bluss/rust-ndarray (a little light on linear algebra right now) And there are probably a few others.

This library is sort of rough as you delve deeper, for instance mesh data gets put into an Arc, which in Rust terms is read only and thread safe but doesn't seem to belong in the library in my opinion because something simple like scaling a mesh is complicated now: https://github.com/sebcrozet/ncollide/issues/112 There are some other quirks I found like trying to store sphere colliders in a hashmap but found I instead need to store the Point type explicitly which wasn't obvious at first. Overall I think the library is good but needs more work, and an abstraction to work with space partitioning would be nice, even if it was in a different library or module. I wish I could offer help, this is definitely a good project. The sister library nalgebra is fantastic in my opinion, great linear algebra library: https://github.com/sebcrozet/nalgebr

Why reimplement linear algebra? Rust has got that part very well covered, for example using nalgebra: https://github.com/sebcrozet/nalgebra

Ok I think I was unfair to Rust in my top message. "Creating problems of their own" was not accurate, but I am under the impression I would miss some D things if using Rust. > Note that 80% of the compilation time in rustc is actually in LLVM passes (the same used by clang), which are mostly optimizations. OK I had a flawed perception probably because of this. > That said, I think there is a strong argument to be made that for many classes of programs it is worth some pain to eliminate memory safety problems I agree 100%, especially on teams memory safety become incredibly important, also I have to thank you for fixing C integer promotion which I've seen create many bugs. > It'd be helpful to know exactly what limitations you were hitting. Trying to implement a "small vector" structure is my "hello world" program to get to know a language