swift-format VS go

I actually don't see anything worth changing. It looks good to me. I think the most important thing is just to maintain the constructive attitude you already have about future-you dealing with the code, because only future-you will really know where you could have done better. One personal-preference thing I carried over from working on Go code is to look for a tool like gofmt [1,2] for Swift. I've been using swift-format [3] for about 2 years and haven't been dissatisfied enough to reach for something more fully featured like SwiftLint [4]. I didn't like the idea at first of delegating most formatting control over to a tool designed with someone else's subjective idea of formatting. But my feeling afterward was that it was freeing: it was no longer (completely) my job/burden/responsibility. An "assistant" would clean up the formatting of my code every time I saved the file. That's a nightmare if you can't configure the tool as much as you need, but if you're lucky and find a configuration you can live with, it lets you focus more on naming and other conventions that aren't so easily automated (yet). [1] https://go.dev/blog/gofmt [2] https://twitter.com/bitfield/status/953395343353315329 [3] https://github.com/apple/swift-format [4] https://github.com/realm/SwiftLint

if you want your code to be formatted with a specific set of rules in mind, you can forward the generated code to a formatting utility, e.g. swift-format

VERSION=0.50500.0 # replace this with the version you need git clone https://github.com/apple/swift-format.git cd swift-format git checkout "tags/$VERSION" swift build -c release ln -s /usr/local/bin/swift-format .build/release/swift-format

Apple literally provides a version that you can integrate into Xcode should you wish to.

swift-format works across different platforms and does a pretty good job with minimal configuration fuss.

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/.