M3

M3ripple – React Library for Ripple Effect with Sparkles Like Android

Hacker News

M3ripple – React Library for Ripple Effect with Sparkles Like Android

Hi HN, nice to meet you — I'm yuyake-litrain. I've always liked the Ripple Effect with sparkles that was introduced in Android 12. (Some people said it looked like a graphics bug, which is probably why it was toned down in later versions.) When I saw Vuetify's beautifully crafted implementation of the Material 2 Ripple Effect, I thought it would be great if we could have something similar for Material 3 on the web as well. After a lot of trial and error, I’ve now created a React library that reproduces this effect. I’ve also built a documentation site that mimics the look and feel of the Android settings screen. I'd love to hear your thoughts — feedback, questions, suggestions, or anything else are all welcome! (English is not my first language, so I rely on machine translation. Please forgive any awkward phrasing.) Documentation: https://m3ripple.js.org/ GitHub Repository: https://github.com/yuyake-litrain/m3ripple NPM Package: https://www.npmjs.com/package/@m_three_ui/m3ripple

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac · Missing: agents, macos, agent
75%75% 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: created · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, 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 · Strong signals: introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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