Gr

GrainJS – a light TypeScript web framework

Hacker News

GrainJS – a light TypeScript web framework

GrainJS is a JavaScript / TypeScript library for building dynamic web applications. - It's in part inspired by React, but based on observables (like Knockout) instead of virtual dom. - It is lightweight, has no dependencies, and takes only ~30KB minified. - It needs no special tooling. It's nothing more than a library. - It supports convenient DOM-building in JS, event dispatching, DOM event subscriptions, 9disposable components, and in-code CSS styling. - It's fully typed for use with TypeScript. - It's proven its worth by powering Grist's rich frontend app. Source code: https://github.com/gristlabs/grainjs/

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
15%15% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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