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[Other] Show HN: Made NZ's member of parliament financial disclosure data searchable New Zealand Members of Parliament are required to annually disclose their financial interests (shareholdings, directorships, consultancies, etc.) but this gets published annually as an unwieldy 80+ page PDF that&#x27;s hard to search effectively.<p>I processed structured data out of the PDF and built a searchable interface: <a href="https:&#x2F;&#x2F;open-register-of-pecuniary-interests.joshmcarthur.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;open-register-of-pecuniary-interests.joshmcarthur.co...</a>.<p>You can search across all MPs&#x27; disclosed interests by name, company, or interest type. For example, you can quickly find which MPs have interests in specific sectors or companies, filter by category or political party.<p>The data extraction was interesting - I found that a two-pass approach worked well with Gemini 2.5 Flash - one to pull out MP names and referenced page numbers, then I extracted the specific pages each MP appeared on and extracted structured data just from these pages.<p>The approach could work for similar transparency registers in other countries - most seem to publish open data as PDF, which technically ticks the box, but isn&#x27;t the most accessible format to work with. Even within NZ, I&#x27;m planning to expand the data I process to previous years, as well as processing data for local and regional councils (who have the same legal requirement to publish financial interests of council members).<p>Open sourced at <a href="https:&#x2F;&#x2F;github.com&#x2F;joshmcarthur&#x2F;open-register-of-pecuniary-interests" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;joshmcarthur&#x2F;open-register-of-pecuniary-i...</a>.<p>Tech stack: Ruby on Rails, SQLite (FTS5), Tailwind&#x2F;DaisyUI - keeping it lightweight since this is just a side project to make public data more accessible.

[Other] Show HN: Pgmcp, an MCP server to query any Postgres database in natural language

[Other] Optimizing ClickHouse for Intel's 280 core processors

[Other] Launch HN: RunRL (YC X25) – Reinforcement learning as a service Hey HN, we’re Andrew and Derik at RunRL (<a href="https:&#x2F;&#x2F;runrl.com&#x2F;">https:&#x2F;&#x2F;runrl.com&#x2F;</a>). We&#x27;ve built a platform to improve models and agents with reinforcement learning. If you can define a metric, we&#x27;ll make your model or agent better, without you having to think about managing GPU clusters.<p>Here&#x27;s a demo video: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;EtiBjs4jfCg" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;EtiBjs4jfCg</a><p>I (Andrew) was doing a PhD in reinforcement learning on language models, and everyone kept...not using RL because it was too hard to get running. At some point I realized that someone&#x27;s got to sit down and actually write a good platform for running RL experiments.<p>Once this happened, people started using it for antiviral design, formal verification, browser agents, and a bunch of other cool applications, so we decided to make a startup out of it.<p>How it works:<p>- Choose an open-weight base model (weights are necessary for RL updates; Qwen3-4B-Instruct-2507 is a good starting point)<p>- Upload a set of initial prompts (&quot;Generate an antiviral targeting Sars-CoV-2 protease&quot;, &quot;Prove this theorem&quot;, &quot;What&#x27;s the average summer high in Windhoek?&quot;)<p>- Define a reward function, using Python, an LLM-as-a-judge, or both<p>- For complex settings, you can define an entire multi-turn environment<p>- Watch the reward go up!<p>For most well-defined problems, a small open model + RunRL outperforms frontier models. (For instance, we&#x27;ve seen Qwen-3B do better than Claude 4.1 Opus on antiviral design.) This is because LLM intelligence is notoriously &quot;spiky&quot;; often models are decent-but-not-great at common-sense knowledge, are randomly good at a few domains, but make mistakes on lots of other tasks. RunRL creates spikes precisely on the tasks where you need them.<p>Pricing: $80&#x2F;node-hour. Most models up to 14B parameters fit on one node (0.6-1.2 TB of VRAM). We do full fine-tuning, at the cost of parameter-efficiency (with RL, people seem to care a lot about the last few percent gains in e.g. agent reliability).<p>Next up: continuous learning; tool use. Tool use is currently in private beta, which you can join here: <a href="https:&#x2F;&#x2F;forms.gle&#x2F;D2mSmeQDVCDraPQg8" rel="nofollow">https:&#x2F;&#x2F;forms.gle&#x2F;D2mSmeQDVCDraPQg8</a><p>We&#x27;d love to hear any thoughts, questions, or positive or negative reinforcement!

[Other] UUIDv47: Store UUIDv7 in DB, emit UUIDv4 outside (SipHash-masked timestamp)

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[Other] Notion API importer, with Databases to Bases conversion bounty

[Other] Show HN: A PSX/DOS style 3D game written in Rust with a custom software renderer So, after years of abandoning Rust after the hello world stage, I finally decided to do something substantial. It started with simple line rendering, but I liked how it was progressing so I figured I could make a reasonably complete PSX style renderer and a game with it.<p>My only dependency is SDL2; I treat it as my &quot;platform&quot;, so it handles windowing, input and audio. This means my Cargo.toml is as simple as:<p>[dependencies.sdl2] version = &quot;0.35&quot; default-features = false features = [&quot;mixer&quot;]<p>this pulls around 6-7 other dependencies.<p>I am doing actual true color 3D rendering (with Z buffer, transforming, lighting and rasterizing each triangle and so on, no special techniques or raycasting), the framebuffer is 320x180 (widescreen 320x240). SDL handles the hardware-accelerated final scaling to the display resolution (if available, for example in VMs it&#x27;s sometimes not so it&#x27;s pure software). I do my own physics, quaternion&#x2F;matrix&#x2F;vector math, TGA and OBJ loading.<p>Performance: I have not spent a lot of time on this really, but I am kind of satisfied: FPS ranges from [200-500] on a 2011 i5 Thinkpad to [70-80] on a 2005 Pentium laptop (this could barely run rustc...I had to jump through some hoops to make it work on 32 bit Linux), to [40-50] on a RaspberryPi 3B+. I don&#x27;t have more modern hardware to test.<p>All of this is single threaded, no SIMD, no inline asm. Also, implementing interlaced rendering provided a +50% perf boost (and a nice effect).<p>The Pentium laptop has an ATI (yes) chip which is, maybe not surprisingly, supported perfectly by SDL.<p>Regarding Rust: I&#x27;ve barely touched the language. I am using it more as a &quot;C with vec!s, borrow checker, pattern matching, error propagation, and traits&quot;. I love the syntax of the subset that I use; it&#x27;s crystal clear, readable, ergonomic. Things like matches&#x2F;ifs returning values are extremely useful for concise and productive code. However, pro&#x2F;idiomatic code that I see around, looks unreadable to me. I&#x27;ve written all of the code from scratch on my own terms, so this was not a problem, but still... In any case, the ecosystem and tooling are amazing. All in all, an amazing development experience. I am a bit afraid to switch back to C++ for my next project.<p>Also, rustup&#x2F;cargo made things a walk in the park while creating a deployment script that automates the whole process: after a commit, it scans source files for used assets and packages only those, copies dependencies (DLLs for Win), sets up build dependencies depending on the target, builds all 3 targets (Win10_64, Linux32, Linux64), bundles everything into separate zips and uploads them to my local server. I am doing this from a 64bit Lubuntu 18.04 virtual machine.<p>You can try the game and read all info about it on the linked itch.io page: <a href="https:&#x2F;&#x2F;totenarctanz.itch.io&#x2F;a-scavenging-trip" rel="nofollow">https:&#x2F;&#x2F;totenarctanz.itch.io&#x2F;a-scavenging-trip</a><p>All assets (audio&#x2F;images&#x2F;fonts) where also made by me for this project (you could guess from the low quality).<p>Development tools: Geany (on Linux), notepad++ (on Windows), both vanilla with no plugins, Blender, Gimp, REAPER.

[Other] Irssi: IRC Client in a Docker Image

[Other] Show HN: npm-daycare, an NPM proxy that filters out recent & small packages Hey all! npm-daycare is a simple NPM proxy built on Verdaccio which filters all packages that:<p>- are younger than 48h (it will just provide an old version instead)<p>- have fewer than 5,000 weekly downloads<p><a href="https:&#x2F;&#x2F;github.com&#x2F;stack-auth&#x2F;npm-daycare" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;stack-auth&#x2F;npm-daycare</a><p>This is in response to the recent supply chain attacks that shattered the JavaScript ecosystem [1]. It&#x27;s likely not a problem that will go away any time soon, so we figured we&#x27;d build something to protect against it.<p>Doing this on the proxy layer means it will work across the entire system, as proxies are set globally. In the future, we could also add more filters to the proxy.<p>To get started, just run the Docker container:<p><pre><code> docker run -d --rm --name npm-daycare -p 4873:4873 bgodil&#x2F;npm-daycare npm set registry http:&#x2F;&#x2F;localhost:4873&#x2F; pnpm config set registry http:&#x2F;&#x2F;localhost:4873&#x2F; yarn config set registry http:&#x2F;&#x2F;localhost:4873&#x2F; bun config set registry http:&#x2F;&#x2F;localhost:4873&#x2F; npm view @types&#x2F;node # has recent updates npm view pgmock # has &lt;5,000 weekly downloads </code></pre> Downside: npm-daycare won&#x27;t show packages that are younger than 48h on its default config, so be aware of that when you try to update your packages to patch a zero-day exploit.<p>You probably also shouldn&#x27;t rely on this as your only line of defense. Curious to hear what you think!<p>[1] <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=45260741">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=45260741</a>

[Other] Show HN: Ghostpipe – Connect files in your codebase to user interfaces Hey HN!<p>I built Ghostpipe because:<p>1. I like to keep data about my software in the codebase and under version control.<p>2. I don’t like always working in raw text files with domain specific languages (eg Terraform, Openapi, er diagrams).<p>Ghostpipe is an open source tool that creates a bridge between files in your codebase and applications using webrtc. This lets developers work with user interfaces where appropriate, while still having access to the underlying raw text files.<p>A few side-benefits to this setup are:<p>1. AI agents are good at working with local text files, so we can keep using those.<p>2. Generally speaking, no signup or installation is needed to use Ghostpipe apps, because all relevant data is in the codebase.<p>I built a few demo apps with Ghostpipe support (Excalidraw &amp; Swagger UI), and I hope this proof of concept spurs some interest in taking this idea further.<p>Thanks!

[Other] PyPI Blog: Token Exfiltration Campaign via GitHub Actions Workflows