unasync VS k8s-openapi

Nice! This is similar to the solution here: https://github.com/python-trio/unasync

Lastly, I found another project name unasync that is pretty interesting and might works for me. Basically, you write the async version, you run unasync, it generate the sync version from the AST. This project is used by the official elastic search python client.

Fibers "allow blocking and non-blocking implementations to share the same API"

That's an interesting contrast to Python where the need to use "value = await fn()" v.s. "value = fn()" depending on whether or not that function is awaitable causes all kinds of API design complexity, all the way up to the existence of tools like https://github.com/python-trio/unasync which can code-generate the non-async version of a library from the async version.

Async Python has proven faster in my uses for IO and non-CPU-related stuff. But I think Python, either as a community or within the language, needs to solve the anti-pattern of maintaining separate sync and async versions of a library. I'm thinking specifically of aioredis and redis-py, both of which I've worked on.

Some people are looking at ways to solve this. I know urllib3, elasticsearch-py, and a few others use unasync (https://github.com/python-trio/unasync) to transform async code into sync code, leaving one codebase supporting both uses in different namespaces. This leaves you with some conditional logic (is_async_mode() -- https://github.com/python-trio/hip/blob/master/src/ahip/util...). I'm seriously considering this approach.

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.