PyO3 VS setuptools-rust

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This story unfolds as a captivating journey where the agile Flounder, representing the Python programming language, navigates the vast seas of coding under the wise guidance of Sebastian, symbolizing Rust. Central to their adventure are three powerful tridents: cargo, PyO3, and maturin.

I would not recommend FFI + ctypes. Maintaining the bindings is tedious and error-prone. Also, Rust FFI/unsafe can be tricky even for experienced Rust devs.

Instead PyO3 [1] lets you "write a native Python module in Rust", and it works great. A much better choice IMO.

[1] https://github.com/PyO3/pyo3

Same w/ Rust and Python, this is really neat because now each thread could have a GIL without doing exactly what you said. The pyO3 commit to allow subinterpreters was merged 21 days ago, so this might "just work" today: https://github.com/PyO3/pyo3/pull/3446

I expected someone to write a rust-based scripting language which tightly integrated with rust itself.

In reality, it seems like the python developers and toolchain are embracing rust enough to reduce the benefits to a new alternative.

https://github.com/PyO3/pyo3

Hey HN! I am one of the people working on Bytewax. Bytewax came out of our experience working with ML infrastructure at GitHub. We wanted to use Python because we could move fast, the team was very fluent in it, and the rest of our tooling was Python-native already. We didn't want to introduce JVM-based solutions into our stack because of the lack of experience and the friction we had trying to get Python-centric tooling working with existing solutions like Flink.

In our research, we found Timely Dataflow (https://timelydataflow.github.io/timely-dataflow/, https://news.ycombinator.com/item?id=24837031) and the Naiad project (https://www.microsoft.com/en-us/research/project/naiad/) as well as PyO3 (https://github.com/PyO3/pyo3) and we thought we found a match made in heaven :). Bytewax leverages both of these projects and builds on them to provide a clean API (at least we think so) and table stakes features like connectors, state recovery, and cloud-native scaling. It has been really cool to learn about the dataflow computation model, Rust, and how to wrangle the GIL with Rust and Python :P.

Would love to get your feedback :).

`pip install bytewax` to get started. We have a page of guides (https://www.bytewax.io/guides) with ready-to-run examples.

You can practice your Rust skills by writing performant and/or gluey extensions for higher-level language such as NodeJS (checkout napi-rs) and Python or complementing JS in the browser if you target Webassembly.

For instance, checkout Llama-node https://github.com/Atome-FE/llama-node for an involved Rust-based NodeJS extension. Python has PyO3, a Rust-Python extension toolset: https://github.com/PyO3/pyo3.

They can help you leverage your Rust for writing cool new stuff.

For Python specifically, In addition to using rust-cpython or PyO3, maturin makes it really comfortable to build, package, and publish Rust code into Python packages and, if your niche doesn't quite fit, there's setuptools-python which might do it.

Aside from the PyO3 and rust-cpython crates already mentioned, I'd suggest maturin as a way to integrate your build processes or possibly setuptools-rust.

Compiled modules for Python stuff (I'd recommend PyO3 but the last one I started was before that worked on stable Rust, so I used its progenitor, rust-cpython. See also maturin or setuptools-rust).

...but you will need to rename the generated library to match import conventions. setuptools-rust or Maturin can help with that.

Between pyodide, pyo3, rust-cpython, and rustpython, I think Pyo3 is the best way to drop in rust in a python project for a speed up, if that is your goal. Some of the demos show using python from rust, but to me the biggest feature is without a doubt compiling rust code to native python modules. I'm using it to speed up image manipulation backed by numpy arrays.

There’s a setuptools rust [0] extension package that can be used to hook the compilation of the rust into the wheel building or install from source. Maturin [1] seems to be regarded as the new and improved solution for this, but I found that it’s angled toward the using python from rust.

There’s also the rust numpy [2] package by the same org which is fantastic in that it lets you pass a numpy matrix to a native method written in rust and convert it to the rust equivalent data structure, perform whatever transformation you want (in parallel using rayon [3]), and return the array. When building for release, I was seeing speed ups of 100x over numpy on the most matrix mathable function imaginable, and numpy is no joke.

I think there is a lot of potential for these two ecosystems together. If there’s not a python package for something, there’s probably a rust crate.

If anyone is interested the python package that I'm building with some rust backend, its called pyrogis [4] for making custom image manipulations through numpy arrays.

https://github.com/PyO3/setuptools-rust