git-lfs VS go

What's the difference between this and Git-LFS?

https://git-lfs.com/

It doesn't, since Git's data model has to be changed to content-defined chunks to solve the issue.

You should look at git-lfs[1] instead.

[1] https://git-lfs.com

Congrats on the HN launch. How does this improve or expand or blow git-lfs[1] out of the water because if I needed large blob file support it's what I would use instead. It offers pointers to the big files to the hosted git instead of pushing around the binaries itself -- though I am speculating since I've not used it myself just read about it online.

[1] https://git-lfs.com/

Specifics depend on project types, but literate programming[0] and using/enforcing coding/git/versioning standards helps. re: outdated responses -- email list for 'new/updated version available' with errata/change log location.

[0] : https://blog.bitsrc.io/literate-programming-a-radical-approa...

[1] : https://blog.codacy.com/coding-standards

[2] : https://github.com/git-lfs/git-lfs/blob/main/.github/workflo...

fine with layers: e.g., large binary files via git-lfs (https://git-lfs.com) and merge conflicts in non-textual files by custom merge resolvers like Unity’s (https://flashg.github.io/GitMerge-for-Unity/).

Perhaps in the future, almost everyone will keep using Git at the core, but have so many layers to make it more intuitive and provide better merges, that what they’re using barely resembles Git at all. This flexibility and the fact that nearly everything is designed for Git and integrates with Git, are why I doubt it’s ever going away.

Some alternatives for thought:

- pijul (https://pijul.org), a completely different VCS which allegedly has better merges/rebases. In beta, but I rarely hear about it nowadays and have heard more bad than good. I don’t think we can implement this alternate rebases in Git, but maybe we don’t need to; even after reading the website, I don’t understand why pijul’s merges are better, and in particular I can’t think of a concrete example nor does pijul provide one.

- Unison (https://www.unison-lang.org). This isn’t a VCS, but a language with a radical approach to code representation: instead of code being text stored in files, code is ASTs referenced by hash and stored in essentially a database. Among other advantages, the main one is that you can rename symbols and they will automatically propagate to dependencies, because the symbols are referenced by their hash instead of their name. I believe this automatic renaming will be common in the future, whether it’s implemented by a layer on top of Git or alternate code representation like Unison (to be clear, Unison’s codebases are designed to work with Git, and the Unison project itself is stored in Git repos).

- SVN, the other widespread VCS. Google or ask ChatGPT “Git vs SVN” and you’ll get answers like this (https://www.linode.com/docs/guides/svn-vs-git/, https://stackoverflow.com/a/875). Basically, SVN is easier to understand and handles large files better, Git is decentralized and more popular. But what about the differences which can’t be resolved by layers, like lazygit for intuition and git-lfs for large files? It seems to me like even companies with centralized private repositories use Git, meaning Git will probably win in the long term, but I don’t work at those companies so I don’t really know.

- Mercurial and Fossil, the other widespread VCSs. It seems these are more similar to Git and the main differences are in the low-level implementation (https://stackoverflow.com/a/892688, https://fossil-scm.org/home/doc/trunk/www/fossil-v-git.wiki#....). It actually seems like most people prefer Mercurial and Fossil over Git and would use them if they had the same popularity, or at least if they had Git’s popularity and Git had Mercury or Fossil’s. But again, these VCSs are so similar that with layers, you can probably create a Git experience which has their advantages and almost copies their UI.

> I don’t know what that is

its a standard output from `go doc`, rendered as HTML. if you dont recognize that, then you aren't really in a position to be commenting on the topic. nothing is stopping anyone from pinning to a tag:

https://github.com/git-lfs/git-lfs/tags

or even a commit and relying of a specific version of the software. yes upgrades might be painful but a module IS available.

# git push origin feature-branch /usr/bin/gh auth git-credential get: 1: /usr/bin/gh auth git-credential get: /usr/bin/gh: not found /usr/bin/gh auth git-credential store: 1: /usr/bin/gh auth git-credential store: /usr/bin/gh: not found Enumerating objects: 9228, done. Counting objects: 100% (7495/7495), done. Delta compression using up to 8 threads Compressing objects: 100% (2090/2090), done. Writing objects: 100% (6033/6033), 72.77 MiB | 7.39 MiB/s, done. Total 6033 (delta 4402), reused 5194 (delta 3616) remote: Resolving deltas: 100% (4402/4402), completed with 477 local objects. remote: error: Trace: c1c90b47a5483929dcdd8c974a6c7d0695e86f67f680d8b88b80ef1c1bce74a remote: error: See https://gh.io/lfs for more information. remote: error: File deployment_20200220.sql is 872.78 MB; this exceeds GitHub's file size limit of 100.00 MB remote: error: GH001: Large files detected. You may want to try Git Large File Storage - https://git-lfs.github.com. To https://github.com/my-org/my-project.git ! [remote rejected] rest-logging -> rest-logging (pre-receive hook declined) error: failed to push some refs to 'https://github.com/my-org/my-project.git'

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/.