Custom license that doesn’t meet the FSF’s definition. Tldr restrictions on redistribution and minor restrictions on modification. It isn’t on fdroid’s main, but they host a fdroid compatible one with a out of date version of Grayjay

I’d look into the git-maintenance’s prefetch task. From what I understand, that is more or less what you are looking for. Then just run any old http(s) server and clone them from that https://git-scm.com/docs/git-maintenance

There is also writefreely. It is fairly basic, but says it supports “publish[ing] to multiple blogs from one account”. Haven’t really used it, but it looks kinda cool imo

https://github.com/writefreely/writefreely

I’m not an expert on btrfs, but I assume the inconsistencies come from deduplication, metadata, and maybe compression. I think some of them just count raw block storage, and some include the cost of metadata.

Traditional du assumes that each file takes up it’s full space on disk which isn’t always the case on btrfs. When using btrfs backed oci images, storage can easily appear multiple times higher.

I use btrfs filesystem usage /. I’m not sure that it is the “correct” way, but it works fairly well.

Standard forgejo shoutout. It is a fork of gitea with more features following the foss philosophy. It is codeberg’s backend https://forgejo.org/2024-02-monthly-update/

You can still compile infinity from source with your own api key

Slint has fairly decent docs and has worked fairly well for my small projects

I’ve gotten tired of weird regex stuff in awk, sed, and grep, so I’ve moved to perl -E for all but the most basic of things.

1. Codeberg is fully open source(forgejo) while gitlab has an open source core+community edition but a source available propietary enterprize edition.

2. Codeberg is a nonprofit with no ulterior motives. Gitlab is a publicly traded for profit entity with a goal to make profit

3. This could just be me, but codeberg feels a lot more transparent. When they have outages, they explain why.

4. Super minor, but the codeberg team “self-hosts” their own servers so you only need to trust the one entity rather than additionally trusting the server provider.

The main advantage of having a /home partition is that you can easily preserve it during reinstalls or during a distro hop. Reinstalls used to be more common in the past when some distros didn’t allow full distro upgrades without reinstalling. See this result which is still ranked #1 on duckduckgo

I personally use a @home btrfs subvolume which has most of the same advantages to me, and additionally allows @home and @root to share the same partition. It also allows me to use luks on everthing without bothering with lvm.

I also don’t believe it’s even fully source availiable. There are no build instructions, and you can’t clone all the submodules without signing in to their closed application gitlab instance. If anyone has sucessfully built it from source, please lmk.

Nevermind they did add build instructions since I last checked. Still lmk if anyone’s tested them.

Section 4 is what gets me. Your rights are temporary and revokable meaning the the rest of the license doesn’t matter in the long term

## Section 4: Termination, suspension and variation
1. We may suspend, terminate or vary the terms of this license and any access to the code at any time, without notice, for any reason or no reason, in respect of any licensee, group of licensees or all licensees including as may be applicable any sub-licensees.

Are you sure your screen refresh rate is correct?

Zellij - a better way for a cli application to communicate with the terminal

Warp - a terminal emulater that integrates LLM completion natively

Fish - a shell that generates completions automatically from a man-page

They could be refering to the V programming language

I may be missing something, but the only machine learning focused api I know of are AMD’s ROCM, Nvidia’s CUDA, and now Intel’s oneAPI. I haven’t looked into Apple’s machine learning frameworks and I consider vulkan more of a general purpose api than a machine learning one.

Now there are 3 competing standards Edit: 6ish accually

Turing Complete Configuration

• more extensible
• tend to be heavier
• harder to provide detailed error messages
• more difficult for new users

Data Based Configuration

• easier to use
• easier to provide documentation
• lighter to embed
• more limited usecases

To enable the use of flakes, you have to use the ‘extra-expiremental-features flakes’ flag.

Edit: Apparently they are called ‘extra-expiremental-features’ not ‘extra-unstable-features’. Regardless the nix docs explicitly describe them as unstable here

https://nixos.org/manual/nix/unstable/contributing/experimental-features.html

Nixos

Pros

• Delarative Config
• largest package repos

Cons

• poor documentation
• cli and package management is in limbo with unstable flakes/cli