dtparse VS py2many

ciso8601 is blazingly fast, and also its wall time is very stable. By all means, use ciso8601 if the format allows :)

On my machine, ciso8601 always runs in 240ns, and the Rust lib median time is 1250ns.

You can run a benchcmark too! Just call pytest, and it will generate an .svg report: https://github.com/gukoff/dtparse/blob/master/tests/test_per...

> 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