refactor VS hpy

Indeed! I also would suggest people to use a CST implementation (parso / LibCST) instead of refactor if they intend do large scale refactors, but from what I can see in my previous attempts (e.g teyit, a unittest assertion formatter) when you deal with small code fragments (a single expression, or a small statement) then you generally don't need to worry much about the style. The only concern is the literals (especially strings, which there are a few different variations of the same AST) where you could resurrect them back from the token stream (which the CustomUnparser representative in refactor allows).

The real start point for this project was to find / replace all type()'s in CPython codebase with type(type()) (e.g type('') would become type(str)) which is very light weight transformation, and I was able to write a script which did it without having any major problems about style on over 2000 files. Here it is for the reference: https://github.com/isidentical/refactor/blob/master/examples...

Also one thing to note here is that; in the last couple of years, thanks to black (and yapf), the adoptance of code formatters have really increased which is very nice for custom refactoring tools like refactor since the end-code would be refactored anyways so that means if you convert a multi line call, or a list to a single line version then the formatter you use probably reformat that segment anyways.

But thanks for authoring Bowler! It is a very cool project.

I've just released 0.2.0 version of refactor, https://github.com/isidentical/refactor, which features additional information collection from the surrounding code.

There is a merge request up to add autogen rust bindings to hpy

https://github.com/hpyproject/hpy/pull/457

Are you referencing https://github.com/hpyproject/hpy?

I do hope it takes off.

The HPy project [0] seems like a promising way out of this.

[0] https://hpyproject.org/

socketify.py breaks the record for Python no other Python WebFramework/Server as able to reach 6.2 mi requests per second before in TechEmPower Benchmarks, this puts Python at the same level of performance that Golang, Rust and C++ for web development, in fact Golang got 5.2 mi req/s in this same round. Almost every server or web framework tries to use JIT to boost the performance, but only socketify.py deliveries this level of performance, and even without JIT socketify.py is twice as fast any other web framework/server in active development, and still can be much more optimized using HPy (https://hpyproject.org/). Python will get even faster and faster in future!

I think Propose a better messaging for Python is the option and a lot of languages will learn it from Rust, because rust erros are the best described errors I see in my life lol. Cargo is amazing and I think we will need a better poetry/pip for sure, HPy project will modernize extensions and packages 📦 too https://hpyproject.org/

It also show that PyPy3 will not magically boost your performance, you need to integrate in a manner that PyPy3 can optimize and delivery CPU performance, with a more complex example maybe it can help more. But why socketify is so much faster using PyPy3? The answer is CFFI, socketify did not use Cython for integration and cannot delivery the full performance on Python3, this will be solved with HPy.

HPy integration to better support CPython, PyPy and GraalPython

Absolutely everything in CPython is a PyObject, and that can’t be changed without breaking the C API. A PyObject contains (among other things) a type pointer, a reference count, and a data field; none of these things can be changed without (again) breaking the C API.

There have definitely been attempts to modernize; the HPy project (https://hpyproject.org/), for instance, moves towards a handle-oriented API that keeps implementation details private and thus enables certain optimizations.