utoipa VS go

In case you didn't know https://github.com/juhaku/utoipa is really nice to generate openapi spec and have a swagger!

play-swagger [2] for scala + play. They generate a significant portion of your spec for you, then a client can be generated from the spec.

[1] https://github.com/juhaku/utoipa

[2] https://github.com/iheartradio/play-swagger

utoipa

Latest release notes: https://github.com/juhaku/utoipa/releases/tag/utoipa-3.0.0

I've written a few backend APIs with rust and I have to disagree. Not only have the frameworks managed to get the ergonomics similar to your popular GC lang[0][1], the natural lack of shared mutable state of HTTP handlers means you very rarely have to encounter lifetimes and a lot of the language's advanced features. What's more, now when I go back to work with other languages, I can't help but notice the significant number of unit tests I'd not have had to write in Rust. It doesn't have a Rails and Django but it's an easy pick over anything at the language level.

A note on performance, Rust's the only langauge where I haven't had the need to update my unit test harnesses to `TRUNCATE` data base data instead of creating a separate db per test on PostgresSQL.

I'll also like to mention the gem that is SQLx[1]. As someone who's never been satisfied with ORMs, type checked SQL queries that auto-populate your custom types is revolutionary. With the error-prone langauge-SQL boundary covered, I was surprised just how good it can get making use of the builtin PostgreSQL features. Almost to the point that amount of effort the community's put to building great tools like Prisma.js and feel like a fool's errand (at least so for PosgreSQL).

[0]: https://github.com/alexpusch/rust-magic-function-params

[1]: https://github.com/juhaku/utoipa

[3]: lib.rs/crates/sqlx

Going to strongly disagree here. This isn't necessary in most cases. You likely do not need to test actix-web. actix-web already has more tests than you can possibly think of for exercising its correctness. So why do you need to black-box test it? Further, if your concern is an API client integrating with the API, use code generation not tests to ensure correctness! Generate your clients from a spec generated from your types! I recommend Swagger/OpenAPI or JSON Schema. Here's a nice library for doing this: https://github.com/juhaku/utoipa

utoipa: supports most popular frameworks

Something like that is planned in future releases. There is a closed discussion in Github https://github.com/juhaku/utoipa/issues/201 and traits for this already exists but the derive implementaiton is yet to be done.

Those tags next function parameters look cool. Do you maybe know a crate Utoipa and could share differences between the two crates for those who want to quickly compare them? I've been using utoipa but also I've been following the discussion on Axum's repo about OpenAPI integration in hope for something more comfortable to write. Taking a quick peek they seem very similar but I'm guessing the approach is slightly different?

A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.

I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles

The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397

There used to be the GO FIPS branch :

https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...

But it looks dead.

And it looks like https://github.com/golang-fips/go as well.

I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:

- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644

- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412

Here are some excerpts from the latest Go survey [1]:

- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."

- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."

I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.

[1]: https://go.dev/blog/survey2024-h1-results

Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.

Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.