git-bug VS go

Unfortunately github appears to be actively breaking the ability to use git-bug on large repositories (like nixpkgs):

https://github.com/MichaelMure/git-bug/issues/749#issuecomme...

True but getting less true by the day:

https://github.com/MichaelMure/git-bug

https://www.fossil-scm.org/home/doc/trunk/www/index.wiki

Only not having access to https://todo.sr.ht made me to recognize fully, that I don’t have any access to it. https://github.com/MichaelMure/git-bug suddenly looks much more interesting.

Neither do the issues support. But there is git-bug [0].

[0]: https://github.com/MichaelMure/git-bug

As a sort of spiritual successor to git-appraise, I've been working on git-bug[1] which support issues and will at some point support kanban and code review. There is a few notables improvements:

- CRDT-like reusable data structure [2][3] for true p2p workflow and easily create new entities (code review ...)

- bidirectional bridges to github, gitlab ... to ease the transition or just use git-bug as a complement of those platform

- CLI, terminal UI and web UI, for different taste and integrate into your tooling/workflow

[1]: https://github.com/MichaelMure/git-bug

[2]: https://github.com/MichaelMure/git-bug/blob/master/doc/model...

[3]: https://github.com/MichaelMure/git-bug/blob/master/entity/da...

> but that is for the development of the platform and network of Gitopia. For the end user the workflows remain almost the same for collaboration.

I have to disagree here. Accidental complexity in a system can have severe downstream impacts on end users, whether that be in the form of poor performance, unreliability, or just slow update cycles. It's not something you can paper over and completely hide from the user.

> Along with this the blockchain layer layer offers immutable, transparent and tamper proof versioning of code

Tamper-proof can be accomplished natively by signing [0]. receive.denyNonFastForwards and receive.denyDeletes[1] can be used to make a git repository immutable. Git commits are also already content-addressable. And transparency is achieved by just having the repo available for people to clone.

> along with the collaboration meta and augments the current collaboration flow

Could this augmentation not be accomplished by storing the collaboration information in the repo under a set of special-purpose branches? Like git-bug[2] or git-issue[3]? Coupled with GPG signatures and you've got your immutability, too!

> Along with this it enables us to provide a novel means to incentivize open-source contributions along with fostering a more decentralized approach for governance (even for projects), every token holder could have a say in the decision making, reducing the risk of undue influence by a single party, hence eliminating centralized control.

This one I'll grant you, but it's by far the least compelling aspect of the project to me. I don't think we're going to solve the centralization of GitHub by centralizing on a new plutocracy, I'd much rather see efforts towards full decentralization. There's nothing inherent to Git that requires that we all use the same set of servers.

[0] https://git-scm.com/book/en/v2/Git-Tools-Signing-Your-Work

[1] https://git-scm.com/book/en/v2/Customizing-Git-Git-Configura...

[2] https://github.com/MichaelMure/git-bug

[3] https://github.com/dspinellis/git-issue

Regarding the issues, there are some projects like git-bug https://github.com/MichaelMure/git-bug trying to embed these sorts of meta-work into git.

Probably git-bug is closer to what Fossil does: It uses Git as a storage engine, and can coexist with your code in the same physical repository, but the issues don't actually show up as source files. Instead, each issue is a special branch (buried in refs so it won't clutter up git branch) that has zero common ancestry with anything else. So in theory you can poke at it with Git, but really, the Git under the hood is mostly an implementation detail, and as long as you interact with those files through the tool, it guarantees you won't have merge conflicts.

You might be interested by git-bug and https://github.com/MichaelMure/git-bug/blob/master/doc/model..., which seems to be exactly what you describe. (Disclaimer: author).

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/.

The Go Programming Language

When Go first shipped, it was already well-documented that the only stable ABI on some platforms was via dynamic libraries (such as libc) provided by said platforms. Go knowingly and deliberately ignored this on the assumption that they can get away with it. And then this happened:

https://github.com/golang/go/issues/16606

If that's not "getting burned", I don't know what is. "Trying to provide a nice feature" is an excuse, and it can be argued that it is a valid one, but nevertheless they knew that they were using an unstable ABI that could be pulled out from under them at any moment, and decided that it's worth the risk. I don't see what that has to do with "not being as broadly compatible as they had hoped", since it was all known well in advance.