Items are in a hash table using color/material type/shape as the hashing method optimized for human pattern recognition providing O(1) access. The table is smaller than the number of items causing some collisions. Those items are in a randomly sorted vector. Average case is still around O(1) with an O(n) worst case.
Something like https://graphite.com/ to create stacked PRs that are reviewable probably would have helped. Can be replicated with local LLMs or remote AI providers with locally configured agentic workflows. Never used graphite personally, but I’ve seen some open source maintainers use it to split up large PRs.
Like, from Yellow Dog Linux? Was my first Linux distro as a kid (grew up with an Apple computer). Red Hat based so checks out. TIL.
neovim user (inside zellij) and same. More of a full blown IDE than an editor.
Also for the keybind memory impaired like myself:
There is a praise/validation kink for that.
NixOS. Started with Yellow Dog Linux in 1998.
I don’t do everything through nix’s derivation system.
Many of my configs are just an outOfStoreSymlink to my configs in the same dotfiles repos. I don’t need every change wrapped in a derivation. Neovim is probably the largest. A few node projects for automations I’m fine using pnpm to manage. Nix still places everything but I can tweek those configs and commit in the same repo without a full blown activation.