bearclaw VS go

why?

Every year I challenge myself in some new way, this year it is to push one project per week. You might recognize my static site generator [0] or my releaser for go [1] from previous posts as one of these weekly projects. If you want to join me in doing this, it's been a blast and I highly recommend it! Maybe we can chat on the bbs about it :)

[0] - bearclaw tiny static generator - https://github.com/donuts-are-good/bearclaw

[1] - release.sh release builder for go - https://github.com/donuts-are-good/bearclaw

need:

I'd love a few co-conspirators, or even some new friends for the bbs software or the bbs itself. A lofty nice-to-have goal is meeting a few other similarly motivated people to conspire with on a weekly basis. If that's you, drop me a line!

goals:

I have about half of an admin interface endpoint pushed up, which I'd like to finish. I realized mid-commit that I'd lacked some other material in a previous commit, and in pushing it up, I ended up pushing half the admin feature. Stay tuned for that.

I made a cool program for you Go stuff that will check all the supported OS and ARCH combos for your code and compile them all. You just do `release --name "mycoolprogram" --version "0.1.0" and it will output all of your labeled release binaries for every platform your code supports.

check it out! https://github.com/donuts-are-good/release.sh You can see it at work here for this simple markdown blog generator I made, which sports about 39 different platform combos https://github.com/donuts-are-good/bearclaw/release/latest

> tiny static site generator w/ rss https://bearclaw.blog

bearclaw.blog redirects back to source repo[0] on GitHub.

Should not it be a redirect to GitHub Pages site?

[0] https://github.com/donuts-are-good/bearclaw

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/.