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Building and tuning the ultimate Node.js tech stack for Web App:
Component/Layer Solution Web Framework Vike Frontend Framework SolidJS CSS Framework TailwindCSS CSS Components daisyUI Web Server Hono Web APIs REST-as-RPC Database MongoDB PWA Vite PWA Cloud Provider Vercel -
Create a new project of Mongo Express using a modern technology stack (e.g. Vike, SolidJS, TailwindCSS, Hono) with the best technology stack. See discussion → Draft repository: mongo-pwa
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Contribute to vLite.js player to replace Video.js player → vLite.js currently lacks on some feature
- 📻 Radio Playlist ~ website with a Playlist of Radio stations
- vite-patcher ~ patch Vite/Vike config to add plugins
- mongodb-query-parser-esm ~ fork of mongodb-query-parser to support ESM
- shell-bson-parser-esm ~ fork of shell-bson-parser to support ESM
- fastest-qs ~ fastest parser for query string
- universal-autorouter ~ auto-router to automatically load routes (based on the file tree) inside Vite instance
- universal-autorouter-hono ~ extension of universal-autorouter to add HMR (Hot Module Replacement) in Hono
- vite-plugin-build-routes ~ Vite plugin that bundles an APIs directory to the server bundle directory
- Yarn Berry
- Vike + SolidJS + daisyUI
- Vike + SolidJS + daisyUI + Hono
- Electron + Vite (Not updated: Electron Forge isn't stable, waiting for the v8 release)
- Create a Calisthenics web app that visualizes an exercise progression tree (graph) grouped by difficulty/rank. Includes an AI-assisted wizard that generates custom workouts, based on target skills/exercise and current level/experience, defining exercise progressions (number of seconds/repetitions to progress to the next exercise)
- Create a Fitness AI web app that, on any device, displays real-time feedback and error corrections for a fitness exercise. This is achieved via pose recognition from the device's camera and comparison with a training set (generated from input videos)