hckrnws

Impressive stuff but it would be polite to the potentially interested users if the line, "... this package is currently a proof of concept with limited direct use", had been put a little earlier. It's about nine or so dense paragraphs in.

It's fine that it is still in development but it just seems worth being upfront.

> The result is very fast native code with no GC, no syscalls, and no memory allocations at runtime.

I guess, that's only achievable for certain kind of code, already designed with hard real-time in mind. It would be good to have some information about the limitations of this approach.

THAT'S INSANE!

I always wondered if this could be possible. Like you fuzz a program, map out each possible allocation and deallocation and optimize the code with those hot paths and some statistics.

Very interesting project, would love some sort of write up on it.

Thanks for your comment, I'll give a full write up a try.

I think for deterministic control applications this concept has a sweet spot. While in conventional code the number of branch combinations can blow up easely, here you need to be able to guarantee worst case execution time which forces you anyway to be very carefull with branching.

On https://copapy.nonan.net/compiler.html is the how-it-works readme section extended with the generated machine code for stencils and a simple example.

This looks like it could become an excellent alternative in time to not just NumPy and Numba, but also Cython. I know that may be more ambitious than your original intentions, but that's absolutely what sprung to mind.

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