llvm-cbe VS prometeo

So how does the LLVM C backend work then?

https://github.com/JuliaHubOSS/llvm-cbe

One alternative worth mentioning, though, would be the LLVM C Backend maintained by the Julia community.

If you drop "easily" and "human" (/s) from your requirements list, then the C backend for LLVM might work. Then you can choose any programming language you want that has LLVM 10-compatible frontend.

If you really must have something that compiles in C (e.g. for a platform where you only have a C compiler) there's an LLVM backend that outputs C code: https://github.com/JuliaComputingOSS/llvm-cbe

You can convert llvm bitcode to C and then use C compiler, there is such project https://github.com/JuliaComputingOSS/llvm-cbe .

I'm really surprised that the LLVM C backends have continually been resurrected then abandoned over the years. It's a good solution to this sort of thing and would enable a lot of cool stuff like Rust to weird embedded platforms. The most recent one is the Julia backend: https://github.com/JuliaComputingOSS/llvm-cbe

Check this project out: https://github.com/JuliaComputingOSS/llvm-cbe.

Well IMO it can definitely be rewritten in Julia, and to an easier degree than python since Julia allows hooking into the compiler pipeline at many areas of the stack. It's lispy an built from the ground up for codegen, with libraries like (https://github.com/JuliaSymbolics/Metatheory.jl) that provide high level pattern matching with e-graphs. The question is whether it's worth your time to learn Julia to do so.

You could also do it at the LLVM level: https://github.com/JuliaComputingOSS/llvm-cbe

For interesting takes on that, you can see https://github.com/JuliaLinearAlgebra/Octavian.jl which relies on loopvectorization.jl to do transforms on Julia AST beyond what LLVM does. Because of that, Octavian.jl beats openblas on many linalg benchmarks

You can try your luck with the "resurrected" C backend: https://github.com/JuliaComputingOSS/llvm-cbe

I don't understand why I see so many requests for LLVM-based languages to change around their backend or IR, that seems to be a huge amount of work for comparatively little benefit. The correct thing to do there is to just add support for those to LLVM.

Not impossible but I guess you might end up with an extra runtime layer and some more dynamic operations will not be very fast. Or you restrict it to a subset of Python like this project does: https://github.com/zanellia/prometeo

You could of course write a bytecode VM in Golang but I guess that defeats the purpose.

Honest question: How does pycom compare to similar tools like Nuitka, prometeo, or mypyc?

If you don't mind switching to a little different syntax of Python, then you also might want to take a look at prometeo - an embedded domain specific language based on Python, specifically aimed at scientific computing. Prometeo programs transpile to pure C code and its performance can be comparable with hand-written C code.

This is awesome! The direction of using a subset of python, while leveraging the user base and static typing to accomplish some other everyday task in a different language is very legit IMO.

I took a cursory look at:

https://github.com/zanellia/prometeo/blob/master/prometeo/cg...

It seems quite similar in spirit to

https://github.com/adsharma/py2many/blob/main/pyrs/transpile...

I'm not spending much time on py2many last few months (started a new job). Let me know if any of it sounds useful - especially the ability to transpile to 7-8 languages including Julia, C++ and Rust.