cinder VS hpy

Meta is actually contributing directly to upstream cpython. If you really wanted to, the internal fork is also open source: https://github.com/facebookincubator/cinder

Just one example: last year Meta open-sourced Cinder, which powers Instagram and provides sizeable speedups compared to CPython.

I used to work on the Cinder JIT and can help document any passes you find interesting or confusing.

You might enjoy Cinder then. It's based on CPython so it is nearly 100% compatible.

https://github.com/facebookincubator/cinder/

Disclaimer: I used to work on it.

I think Cinder's Static Python, which also performs runtime type checking, is more ambitious. Though it's not production ready yet.

Here's a fork that implements that https://github.com/facebookincubator/cinder - it might be nice to one day get that up streamed but obviously it'll be controversial and it certainly needs more time to bake. Hopefully at some point we can make it a pip installable extension though.

The other thing that was interesting to me, was the potential of type annotations to help make for a faster, safer experience on the compiler end of things. One example is seen in Meta’s Cinder project, on the docs it explains how typing can be used to reduce the number of steps for the compiler ([cinder/static_python.rst at cinder/3.8 · facebookincubator/cinder · GitHub](https://github.com/facebookincubator/cinder/blob/cinder/3.8/CinderDoc/static_python.rst)), making it more effective.

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.