abseil-py VS nixpkgs

Noticed it wasn't on Nixpkgs, so... https://github.com/NixOS/nixpkgs/pull/399843

https://github.com/nixos-bsd/nixbsd This is a very cool project that I hope will get upstreamed into NixOS proper, eventually.

I always thought InitWare would be good for that. See https://github.com/NixOS/nixpkgs/issues/26850 --- we've been discussing this before NixBSD existed, even!

If you are currently involved in managing packages for a Linux distribution, then you might want to use the instructions outlined in the GitHub repo to help you build packages for your distributions. My colleague James Ward has recently done this for NixOS (you can see his PR here)

You can do this with vanilla Firefox using policies.json[1]. Check out `DisableAppUpdate` attribute.

If you're using Firefox from nixpkgs this is already disabled by default[2].

[1]: https://support.mozilla.org/en-US/kb/customizing-firefox-usi...

[2]: https://github.com/NixOS/nixpkgs/blob/nixos-24.11/pkgs/appli...

Ah, this is awesome! I currently run k3s on a decently spec-ed NixOS rig. I tried getting k3s to recognize my Nvidia GPU but was unsuccessful. I even used the small guide for getting GPU in k3s to work in nixpkgs[0], but without success.

For now I’m just using Docker’s Nvidia container runtime for containers that need GPU acceleration.

Will likely spend more time digging into your findings — hoping it results in me finding a solution to my setup!

[0] https://github.com/NixOS/nixpkgs/blob/master/pkgs/applicatio...

- Method 1: doesn't really improve layer caching, but it provides a familiar way (via Dockerfile) to use Nix packages. As with any Dockerfile, the creator is in charge of creating layers and making sure those layers are as small (cleaning cache, ...).

- Method 2: Nix language is used to describe (in a declarative way) what the end image should look like. Layers are then calculated based on the dependency tree (or as Nix calls it, dependency closure). The algorithm that creates layers[1] makes sure that there is higher likelihood of cache hits without the user needing to worry about layers, but you can even roll-up your own algorithm that fits your project better.

- Method 3: Using Flox you would get sort of both. An easy way to configure the final docker image via toml configuration and using Method 2 under the hood.

There are other ways how to improve caching efficiency, but those are very use case specific (eg. big "builder" images) and would probably require a completely separate blog post.

[1] https://github.com/NixOS/nixpkgs/blob/63f0da03a3b2c323ea924b...

I spent a while messing around with https://github.com/ansiwave/nimwave, which I enjoyed but I haven't gotten very far. Though I've been avoiding the front end for so long, I don't know what reasonable feels like in that space anyway.

My Nim journey was stalled by this bug in its nix toolchain: https://github.com/NixOS/nixpkgs/issues/308593. I guess that's the price we pay for straying from the beaten path.

The build will actually fail if Gixy finds any issues.

[1]: https://github.com/NixOS/nixpkgs/blob/nixos-24.11/nixos/modu...