kuberwastaken
This is one of the weirdest batch of printers HP made because it's a rebranded Samsung - it "comes" under HP's unified drivers system but specifically has Samsung's printer language so compatibility is extremely messy.
What this version does is take the Linux Unified Driver and extract just the relevant component, rastertospl, basically the codec that turns CUPS raster data into the Samsung SPL format the printer understands. That codec is then wired into macOS’s native CUPS stack, so printing happens through the system like a normal driver. There’s no Linux VM handling the actual print workflow and the entire process basically acting as a driver normally at system level.
In theory, yeah - rastertospl could be reimplemented from scratch. But that would be way more unreliable while turning this from a ~4-hour project into a ~4-day reverse-engineering project, when starting this, I really just wanted a working home printer and running a tiny compatibility applet in Docker just for that codec feels like a pretty reasonable compromise AND I get to not see my mac kernel crash if it messes up.
I didn't expect this to blow up this much lol, so I'll be experimenting with this further and am already in talks with the splix team to sort this specific version out"
I usually answer saying there's not really a hack for it, you just work with it, convey thoughts decently and try out things with educated guesses until it sticks with these projects.
But I actually went ahead and exported the chat in a readable format for anyone curious enough to go through :) https://cdn.kuber.studio/chat/hp-laser-1008a-driver
linking this here for those who don't wanna read the threads https://github.com/Kuberwastaken/hp-laser-1008a-macos
genuinely very interesting case to learn from for me because this was one of the HP branded Samsung printers which doesn't have native non-windows support !
Not sure if I agree with a lot of this, even while spending a lot of time building with LLM, but was interesting nonetheless.
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https://github.com/Kuberwastaken/megaphone
I was casually scrolling HN yesterday when I came across the post comparing whisper small with Apple's new native SpeechAnalyser API, where it beat it in both accuracy and speed [1] so I built it into a fully native, OSS dictation swift app that does everything I need.Megaphone is built on top of Freeflow and uses the SpeechAnalyser API along with Apple's own foundational model for intelligence...
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To my surprise, I found almost no repos covering this decently, so I went through the process and made it a reusable skill
It's MIT licensed and open, would love to hear feedback