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Building desktop WebView apps in Go without CGo

I have been working on Glaze , a small desktop WebView toolkit for Go. The short version: Glaze lets a Go program open a native desktop window backed by the WebView already available on the operating system, without using CGo. It currently targets: macOS, through WKWebView Linux, through WebKitGTK Windows, through WebView2 The project is still young, but the core idea is already useful: keep small Go desktop tools close to the normal Go workflow. No C compiler in the build path. No bundled native helper library. No large application framework around it. Just Go code calling the system WebView. Why I wanted this I write a lot of small tools in Go. Some of them are fine as CLI programs. Others need a basic interface: a form, a preview, a local dashboard, a small editor, or a way to inspect and manipulate data visually. For those cases, HTML is often enough. The browser gives me layout, text rendering, forms, tables, keyboard handling, and a familiar debugging model. But I do not always want to ship a web server as the user interface. I also do not always want to pull in a large desktop framework when all I need is a native window around a local UI. A WebView is a reasonable middle ground. The problem is that many WebView solutions eventually bring CGo, native build tooling, helper libraries, or larger framework assumptions into the project. That is not necessarily wrong. For many applications, those trade-offs are acceptable. For this project, I wanted something narrower. The design constraint The main constraint behind Glaze is simple: Use the WebView already provided by the OS, but call it from Go without CGo. Glaze uses purego to call native platform APIs directly from Go. That means each backend talks to the platform WebView: WKWebView on macOS WebKitGTK on Linux WebView2 on Windows The result is not a full GUI toolkit. That is intentional. Glaze is focused on the window, the WebView, JavaScript-to-Go bindings, and a few desktop helpers that are useful for small t

2026-06-30 原文 →
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Stop Slouching! Build an AI-Powered Posture Monitor with MediaPipe and Electron

Let’s be honest: as developers, our relationship with our office chairs is... complicated. We start the day sitting upright like productivity gurus, but four hours into a debugging session, we’ve morphed into a human pretzel. This "gamer lean" isn't just a meme; it leads to chronic back pain and decreased focus. In this tutorial, we are going to build a real-time posture tracking system using MediaPipe Pose and Computer Vision to save your spine. By leveraging AI productivity tools and the power of cross-platform Electron desktop apps , we will create a silent guardian that watches your form and pings you the moment you start slouching. If you've been looking for a practical way to dive into MediaPipe and Node.js integration, you're in the right place. For those looking for more production-ready patterns and advanced AI implementations, I highly recommend checking out the deep dives at WellAlly Blog . 🏗 The Architecture The system works by capturing frames from your webcam, processing them through a pre-trained neural network to identify body landmarks, and then applying some basic trigonometry to determine if your posture is healthy. graph TD A[Webcam Stream] --> B[MediaPipe Pose Engine] B --> C[Extract 33 Keypoints] C --> D{Geometry Engine} D -->|Angle > Threshold| E[Slouch Detected] D -->|Angle < Threshold| F[Good Posture] E --> G[Electron Main Process] G --> H[System Notification 🔔] F --> I[Wait 5s] I --> A 🛠 Prerequisites To follow along, you'll need: Node.js (v16+) MediaPipe (The pose solution) OpenCV.js (For frame manipulation) Electron (For the desktop shell) 🚀 Step 1: Setting Up the Pose Engine MediaPipe provides a "Pose" model that gives us 33 landmarks in 3D space. For posture correction, we specifically care about the Ears (7, 8) , Shoulders (11, 12) , and Hips (23, 24) . The Math: Calculating the "Slouch" We measure the angle between the Ear, the Shoulder, and a vertical axis. If your ear moves too far forward relative to your shoulder, that's "Forward

2026-06-30 原文 →
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The GitHub Actions workflow that's been failing for weeks (and how to find yours)

trpc has a scheduled workflow called "Lock Issues & PRs." Its own scorecard shows it failing on almost every run. It is still scheduled, still running, still red. trpc ships excellent software, which is exactly the point: if a project this careful has a workflow that has been red for ages, the rest of us almost certainly do too. It is not a one-off. drizzle-orm has one ("Unpublish release"). cal.com has one ("PR Update"). I scanned 35 popular open-source repos and the same thing kept turning up: a scheduled workflow that fails on nearly every run, quietly, for a long time. Why nobody notices GitHub does email you when a scheduled workflow fails. So how do these survive? Two reasons. First, those emails are routine. You get them for flaky reruns and transient blips too, so you filter them out. Second, a workflow that is always red stops reading as a signal. It is just how that row looks now. I did exactly this on my own project. GitHub emailed me that a workflow had failed. The next day it emailed again. I saw it, told myself I would fix it tomorrow, and promptly forgot. It was my nightly database backup, quietly broken the whole time, and I only caught it when a failure-rate number crept up where I would notice. An always-red workflow is not free It burns minutes every run to produce nothing but a red X. Worse, it trains you to ignore the failure that actually matters: the day a real one lands in the same inbox you have learned to skim past. How to find yours Open your Actions tab and look at the scheduled workflows, the cron-triggered ones nobody watches. If the last several runs are all red, you found one. From the CLI: gh run list --workflow = "Lock Issues & PRs" --status = failure What to do about it Two honest options: fix it, or if the workflow is genuinely abandoned, turn it off. Do not leave it scheduled and red. gh workflow disable "Lock Issues & PRs" Or drop the schedule trigger from the workflow file if it should not run on a timer at all. A disabled work

2026-06-30 原文 →
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Why your GitHub Actions CI is slow (and how to speed it up)

Two days ago GitHub emailed me to say one of my workflows had failed. The next day it emailed me again. I saw it, told myself I would fix it tomorrow, and promptly forgot. It was my nightly database backup, quietly broken the whole time, and I only caught it because a failure-rate number nudged up. A failed run at least gets you an email. A slow run gets you nothing. GitHub never pings you when CI quietly takes twice as long, runs the whole suite twice per PR, or rebuilds dependencies from scratch every time. That waste compounds where no one looks. Here are the usual culprits, each with the exact fix. When I scanned 35 popular open-source repos, not one had a fully clean config. 32 of 35 had no concurrency control, 33 of 35 had no job timeouts, and 22 of 35 ran the full suite twice on every PR. If projects this polished leave minutes on the table, the rest of us definitely do. Your suite runs twice on every PR Trigger a workflow on both push and pull_request and, for a branch in the same repo, opening a PR fires both. You just paid for two identical runs. This one is pure waste and it can roughly halve your PR-related minutes. Trigger on pull_request , and keep push for your default branch: on : push : branches : [ main ] pull_request : Old runs don't cancel when you push again Push a fix 30 seconds after the first push and, with no concurrency group, both runs go to completion. The first is dead weight, and it is holding a slot in your queue while it finishes. This hides even when you do have a group: astro has a concurrency group on one workflow but left off cancel-in-progress , which our scan estimates leaves roughly 1,850 minutes a month on the table. Add a group keyed on the branch, with cancel-in-progress , so a new push supersedes the old run: concurrency : group : ${{ github.workflow }}-${{ github.ref }} cancel-in-progress : true Every run reinstalls dependencies from scratch No cache means every run re-downloads and rebuilds your dependencies. On a typical

2026-06-30 原文 →
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Galfus Script MVP is complete

Galfus Script has reached its first MVP milestone. Galfus is an experimental programming language written in Rust, designed around a typed VM-first execution model, compact .gfb artifacts, deterministic module/workspace resolution, and an ownership model based on anchors, edges, and weak observers. The MVP goal was not to build a full ecosystem yet. The goal was to prove the complete local execution pipeline: txt .gfs source -> lexer and parser -> resolver -> type checker and semantic analyzer -> ownership check -> MIR lowering -> bytecode emitter -> Galfus Module Image -> .gfb serialization -> VM interpreter execution https://github.com/vulppi-dev/galfus-script/discussions/10

2026-06-29 原文 →
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