PyO3 VS rust-cpython

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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.

I've never used pyo3, just cpython, but the latter at least let me do things like:

And don't forget https://github.com/dgrunwald/rust-cpython to complete the circle

For interoperating with Python, check out PyO3 or rust-cpython. (More generally, see Rust Interop and Are We Extending Yet?)

You probably should learn Rust. Aside from the process of learning new and different languages making you a better programmer, rust-cpython, PyO3, or Interoptopus make it easy to expose Python APIs from your Rust code. (eg. So it's easy to compile the same codebase as both a Python module and a WebAssembly module.)

Have you looked into abi_stable, flapigen, interoptopus, cbindgen, PyO3, or rust-cpython?

Personally, I'm not willing to compromise on my GUI look and feel, so I use PyQt or PySide to write my GUIs against the QWidget API (I'm a KDE user and Python is the only language with mature memory-safe bindings to Qt) and, if the project can be structured with a frontend-backend separation, I use rust-cpython or PyO3 to write a backend in Rust that the Python frontend can import. Sort of using Python/Rust as a QWidget analogue to the QML/C++ architecture promoted for Qt Quick. (Which I don't use because it's still too incomplete on Kubuntu 20.04 LTS.)

also, check out rust-cpython, PyO3, and maturin, among other things. They're really nice options for using Rust for its strengths and Python for its strengths within the same project.

This section uses flapigen to expand the foreign_class macro into many cpython functions as an extension module, and cargo compiles it as a cdylib. If you want to see what that looks like, install cargo-expand and run cargo expand. You'll get a lot of generated rust code.

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.

hlua or rlua are what you want for Lua, rust-cpython or PyO3 for Python, rutie for Ruby, and possibly deno_core for JavaScript.