py2many VS pythran

> Another problem is that there are hundreds of built-in library functions that need to be compiled from Python from C

An approach I've advocated as one of the main authors of py2many is that all of the python builtin functions be written in a subset of python[1] and then compiled into native code. This has the benefit of avoiding GIL, problems with C-API among other things.

Do checkout the examples here[2] which work out of the box for many of the 8-9 supported backends.

[1] https://github.com/py2many/py2many/blob/main/doc/langspec.md

https://github.com/py2many/py2many/blob/main/doc/langspec.md

Reimplement a large enough, commonly used subset of python stdlib using this dialect and we may be in the business of writing cross platform apps (perhaps start with android and Ubuntu/Gnome)

For py2many, there is an informal specification here:

https://github.com/py2many/py2many/blob/main/doc/langspec.md

Would be great if all the authors of "python-like" languages get together and come up with a couple of specs.

I say a couple, because there are ones that support the python runtime (such as cython) and the ones which don't (like py2many).

It'd not fully solve your issue, but have you ever seen https://github.com/py2many/py2many ?

Cython doesn't consume python3 type hints and needs special type hints of its own. But it's certainly more mature than other players in the field.

What we need is a rpython suitable for app programming and a stdlib written in that dialect.

https://github.com/py2many/py2many/blob/main/doc/langspec.md

No intermediate AST. To understand the various stages of transpilation and separation of language specific and independent rewriters, this file is a good starting point:

https://github.com/adsharma/py2many/blob/main/py2many/cli.py...

Link to the test that's relevant for this discussion:

https://github.com/adsharma/py2many/blob/main/tests/cases/in...

This is an explicit deviation from python's bigint, which doesn't map very well to systemsey languages. The next logical step is to build on this to have dependent and refinement types.

Work in progress here:

https://github.com/adsharma/Typpete

Numpy and Scipy are good reasons. Unfortunately Scipy does not even compile on FreeBSD lately, and I have opened three issues about it against Scipy and Pythran (and the fix was with xsimd).

https://github.com/serge-sans-paille/pythran/issues/2070

In someone lands here seeking a maintained compiler for Python, there's a lot, on top of my head:

- Pythran (https://pythran.readthedocs.io) (ahead of time compiler)

Yes, I mean Pythran ( https://github.com/serge-sans-paille/pythran ). Thank you.

Was Nuitka better? Pythran is quite simple to install and use in Jupyter.

The only project that compares 1:1 is Pythran: https://github.com/serge-sans-paille/pythran

Pythran is fairly nice, and it really does work. I tried it last year and it compiles down to modifiable templated C++. I was able to use it to build Python for a highly specialized environment.

All the others compile down to dynamically linked binaries, and that just puts them in the "other" box.

You might want to contact the author of Pythran [1], maybe something can be learned from what they do.

[1] https://github.com/serge-sans-paille/pythran/commits/master

[1] https://github.com/serge-sans-paille/pythran