wingo VS go

I've been using X11 on my Framework laptop for years. No desktop environment at all. Just my regulard old school window manager[1]. No KDE or GNOME. But also no XFCE.

The only thing I had to do to get scaling working for me was set two environment variables[2].

I was indeed worried about this when I bought the laptop. Prior to this, I avoided anything with resolutions higher than 1920x1200. But it turned out that everything mostly worked with a couple tweaks.

I think the only real issue I've run into is `git gui`. As I understand it, the GUI toolkit it uses doesn't support scaling? Not sure. I ended up working around it by just increasing font sizes. I suppose this exposes the weakness that is probably impacting you: the scaling on my laptop is being done by the GUI toolkits, not the display server or compositor. (I don't always run a compositor, but when I do, I use `picom`. Mostly just to avoid tearing.)

[1]: https://github.com/BurntSushi/wingo

[2]: https://github.com/BurntSushi/dotfiles/blob/ea3a88e6160f4244...

I used Wingo (https://github.com/BurntSushi/wingo) for a while and it did the floating/tiling mix pretty well.

I also used StumpWM (https://stumpwm.github.io/) for years, primarily in purely-tiling mode. The killer feature for me was that you (the user) define frames on the desktop, and then windows are placed into frames rather than resizing and re-jiggering everything whenever a new window opens.

Yeah I remember activities from over a decade ago. I don't recall ever being able to get it to work right.

I ended up writing my own WM instead: https://github.com/BurntSushi/wingo

That's why I went and wrote my own window manager that breaks this aspect of EWMH so that workspaces can be changed independently on each head: https://github.com/BurntSushi/wingo/

Wingo

Switching to a desktop environment is a no-go for me. (I wrote my own WM.) So I'm very likely going to be spending quite a bit of time trying to find a configuration that works for my eyes. I don't mind putting in that time, I'm just hoping that I can find something that works. But others might bounce off. This is actually why I have historically not purchased laptops with HiDPI displays, specifically to avoid dealing with this problem. I made an exception this time because there are so many other great aspects of the laptop.

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/.