Julia vs Pyccel: a Python-to-X transpiler for scientific high-performance computing

I noticed Pyccel has a this still open discussion from long ago, recently added to:

And while it may get that feature, or not, Python already has in a package:

I don’t think Python will get inherently get better than Julia (with tools and/or Mojo), but I note it’s a dynamic language like Julia (Python even more dynamic), compiling (subsets of Python, I think no tool handles all) to static languages Fortran and C, for speed.

I’m thinking Julia could actually do that compile to another language, to get e.g. C code (like Pyccel, human readable), and static binaries from e.g. Julia language library code… or for full apps.

I’m thinking is there a subset of Julia that we could, and should, standardize as a static language subset (or if not strictly a static language subset, then something that can compile to such a language)? I don’t think code working for StaticCompiler.jl is it, i.e. it’s too restrictive, see need something that supports way more already working Julia code. One of its downsides is not allowing GC, and it’s a blocker for much else, and code in Julia Base, that would otherwise work.

Julia wouldn’t be the first language to have a subset, e.g. D has a betterC subset, but it also means much of D’s standard library is unusable. We could have such a subset (already do), one with GC (a superset of it) and full.