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BDC – Ergonomic, sub 1KiB virtual DOM library

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BDC – Ergonomic, sub 1KiB virtual DOM library

BDC is a simple library for updating the DOM to match a javascript description. Does not require JSX or a compilation step. clobber( document.body, h("marquee", [ h("span", {"style": "font-weight: bold"}, "Hello"), ", ", h("blink", "world"), "!", ]), ); Very fast to first render, moderately slow on subsequent updates. Prompted by the post on millionjs, which compiles user code to hit the same outrageously small size target.

Visit productView on Hacker NewsJul 31, 2022
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23points
4comments
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Launch Intel predictions

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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
63%63% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, code · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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