k8s-openapi VS PyO3

It's called sans-io in Python land, which is where I heard it first.

https://sans-io.readthedocs.io/

I did it for one of my projects back in 2018 https://github.com/Arnavion/k8s-openapi/commit/9a4fbb718b119...

Another option is to implement your API in a sans-io form. Since k8s-openapi was mentioned (albeit for a different reason), I'll point out that its API gave you a request value that you could send using whatever sync or async HTTP client you want to use. It also gave you a corresponding function to parse the response, that you would call with the response bytes however you got them from your client.

https://github.com/Arnavion/k8s-openapi/blob/v0.19.0/README....

(Past tense because I removed all the API features from k8s-openapi after that release, for unrelated reasons.)

Macro expansion is slow, but only noticeably in the specific situation of a) third-party proc macros, b) a debug build, and c) a few thousand invocations of said proc macros. This is because debug builds compile proc macros in debug mode too, so while the macro itself compiles quickly (because it's a debug build), it ends up running slowly (because it's a debug build).

I know this from observing this on a mostly auto-generated crate that had a couple of thousand types with `#[derive(serde::)]` on each. [1]

This doesn't affect most users, because first-party macros like `#[derive(Debug)]` etc are not slow because they're part of rustc and are thus optimized regardless of the profile, and even with third-party macros it is unlikely that they have thousands of invocations. Even if it is* a problem, users can opt in to compiling just the proc macros in release mode. [2]

[1]: https://github.com/Arnavion/k8s-openapi/issues/4

[2]: https://github.com/rust-lang/cargo/issues/5622

>OpenAPI Generator allows generation of API client libraries from OpenAPI Specs

It does, but the generated code can be very shitty for some combinations of spec and output language. I maintain Rust bindings for the Kubernetes API server's API, and I chose to write my own code generator instead. The README at https://github.com/Arnavion/k8s-openapi has more details.

k8s_openapi - https://github.com/Arnavion/k8s-openapi

For example: I have a routine that checks the value of (from k8s-openapi): Ingress -> IngressStatus -> LoadBalancerStatus -> Vec[0] -> String

As the maintainer of the Rust bindings that the library used in the article (kube) is backed by, I can confirm that Kubernetes' openapi spec requires a lot of Kubernetes-specific handling to generate a good client than generic openapi generators do not provide.

See https://github.com/Arnavion/k8s-openapi/blob/master/README.m... for a full description.

I also confirm that I keep it up-to-date with Kubernetes releases and have been doing so for the ~3 years that it's been around. Not just the minor ones every few months, but even the point ones; these days the latter usually only involves updating the test cases instead of code changes and they're done within a few hours of the upstream release.

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.