strop VS PyO3

I am completely rewriting strop, (the code sucks, and I know Rust a lot better than when I started, so I wanted to make it a bit better structured and more idiomatic). And I like to have static analysis make sure my code has certain qualities, so I stick this:

Do you think it's an architecture for strop then? It has a focus on code-generation on platforms not well supported by mainstream compilers

Here is a project for generating code for CPUs that do not have much support from mainstream compilers. Currently supported are the 6502 and the STM8 (I'll possibly be adding others in the future, feature requests welcome).

I could use some help on my project strop. Feel free to take a look and see if it's the kind of thing you feel you could contribute to! but be aware that the quality of the codebase is poor. There's a pull request to address this though.

It is my first time of making a Rust library. Actually, my project strop has been a binary crate and only recently have I started trying to use it from a different crate. This is happening on the breakapart branch.

Still working on a big rewrite of strop.

If you're offering free help, then I could use some help with my project strop. (TL;DR: instead of compiling code, it's evolving code. And it has a focus on architectures that don't have good support from mainstream compilers, but I'm open to adding other architectures as well).

My frustration with this kind of situation (and PICs are not unique here, the 6502, CP1600 and other very low end chips have similarly problematic toolchaining) led me to invent strop, for evolving code sequences. It has some basic PIC support.

Hadn't thought of this. I even encountered it recently too.

I am still working on strop. (TL;DR alternative to compiled code, it's evolved code. Tell it which function you want and which registers to use, and it'll randomly generate an assembly language program that does what you wanted)

Integrating Rust into Python, Edward Wright, 2021-04-12 Examples for making rustpython run actual python code Calling Rust from Python using PyO3 Writing Python inside your Rust code — Part 1, 2020-04-17 RustPython, RustPython Rust for Python developers: Using Rust to optimize your Python code PyO3 (Rust bindings for Python) Musing About Pythonic Design Patterns In Rust, Teddy Rendahl, 2023-07-14

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.