I’m doing a bunch of AI stuff that needs compiling to try various unrelated apps. I’m making a mess of config files and extras. I’ve been using distrobox and conda. How could I do this better? Chroot? Different user logins for extra home directories? Groups? Most of the packages need access to CUDA and localhost. I would like to keep them out of my main home directory.

  • DryTomatoes@lemmy.world
    11·
    1 year ago

    I did Linux From Scratch recently and they have a brilliant solution. Here’s the full text but it’s a long read so I’ll briefly explain it. https://www.linuxfromscratch.org/hints/downloads/files/more_control_and_pkg_man.txt

    Basically you make a new user with the name of the package you want to install. Login to that user then compile and install the package.

    Now when you search for files owned by the user with the same name as the package you will find every file that package installed.

    You can document that somewhere or just use the find command when you are ready to remove all files related to the package.

    I didn’t actually do this for my own LFS build so I have no further experience on the matter. I think it will eventually lead to dependency hell when two packages want to install the same file.

    I guess flatpaks are better about keeping libraries separate but I’m not sure if they leave random files all over your hard drive the way apt remove/apt purge does. (Getting really annoyed about all the crud left in my home dir)

    • FOSS Is Fun@lemmy.worldEnglish
      4·
      1 year ago

      Flatpak apps can be uninstalled without leaving a trace: flatpak uninstall --delete-data com.google.Chrome

      But you might need some global overrides to make all apps write their configuration into ~/.var. Personally I globally revoke apps the permission to access filesystem= host, home, xdg-config, xdg-data.

      That was actually the main reason that made me switch to Flatpak. Previously I used VMs to try out software, but with Flatpak I know that I can get rid of the application completely.

      • DryTomatoes@lemmy.world
        2·
        1 year ago

        Thanks for the info! I’m definitely gonna look into flatpak.

        I built nodejs from source yesterday and it took forever. I’d definitely prefer something huge like that in a flatpak.

    • j4k3@lemmy.worldOPEnglish
      2·
      1 year ago

      Thanks for the read. This is what I was thinking about trying but hadn’t quite fleshed out yet. It is right on the edge of where I’m at in my learning curve. Perfect timing, thanks.

      Do you have any advice when the packages are mostly python based instead of makefiles?

      • DryTomatoes@lemmy.world
        2·
        1 year ago

        This method should work with any command that’s installing files on your disk but it’s probably not worth the headache when virtual environments exist for python.

        • j4k3@lemmy.worldOPEnglish
          2·
          1 year ago

          Python, in these instances, is being used as the installer script. As far as I can tell it involves all of the same packaging and directory issues as what make is doing. Like, most of the packages have a Python startup script that takes a text file and installs everything from it. This usually includes a pip git+address or two. So far, just getting my feet wet to try out AI has been enough for me to overlook what all is happening behind the curtain. The machine is behind an external whitelist firewall all by itself. I am just starting to get to the point where I want to dial everything in so I know exactly what is happening.

          I’ve noticed a few oddball times during installations pip said something like “package unavailable; reverting to base system.” This was while it is inside conda, which itself is inside a distrobox container. I’m not sure what “base system” it might be referring to here or if this is something normal. I am probing for any potential gotchas revolving around python and containers. I imagine it is still just a matter of reading a lot of code in the installation path.

          • DryTomatoes@lemmy.world
            1·
            1 year ago

            I hope someone who has more info comes along. It might be time for you to make a new post though since we’re getting to the heart of the problem now.

            Also it will be a lot easier for people to diagnose if you are specific about which programs you are failing to install.

            I’ve only experimented with Python in docker and it gave me a lot of headaches.

            That’s why I prefer to pip install things inside venvs because I can just tar them myself and have decent portability.

            But since your installing files across the system I’m not sure what the best solution is.