Thi.ng/hdom – S-expression based, pure ES6 UI/VDOM components

Hacker News

https://github.com/thi-ng/umbrella/blob/master/packages/hdom... Lightweight UI component tree definition syntax, DOM creation and differential updates using only vanilla JS data structures (arrays, iterators, closures, attribute objects or objects with life cycle functions, closures). By default targets the browser's native DOM, but supports other arbitrary target implementations in a branch-local manner, e.g. to define scene graphs for a canvas element as part of the normal UI tree. Benefits: - Use the full expressiveness of ES6 / TypeScript to define user interfaces - No enforced opinion about state handling, very flexible - Clean, functional component composition & reuse - No source pre-processing, transpiling or string interpolation - Less verbose than HTML / JSX, resulting in smaller file sizes - Supports arbitrary elements (incl. SVG), attributes and events in uniform, S-expression based syntax - Supports branch-local custom update behaviors & arbitrary (e.g. non-DOM) target data structures to which tree diffs are applied to - Suitable for server-side rendering and then "hydrating" listeners and components with life cycle methods on the client side - Can use JSON for static components (or component templates) - Optional user context injection (an arbitrary object/value passed to all component functions embedded in the tree) - Default implementation supports CSS conversion from JS objects for style attribs - Auto-expansion of embedded values / types which implement the IToHiccup or IDeref interfaces (e.g. atoms, cursors, derived views, streams etc.) - Only ~5.5KB gzipped

Visit product View on Hacker NewsSep 23, 2018

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, user, context · Missing: mac, agents, macos

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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