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React-Pulsable – Add Pulsating Effect to Any React Component

Hacker News

React-Pulsable – Add Pulsating Effect to Any React Component

Hi HN, I released React-Pulsable GitHub last year, and after seeing it in action across a few projects, I wanted to share it with a wider audience. It’s a lightweight library that lets you easily add customizable pulsating animations to any React component, helping to highlight elements like buttons, icons, or any UI component. Key Features: Easy integration with any React component Fully customizable (duration, color, size, etc.) Lightweight and doesn't rely on external dependencies Great for adding subtle yet engaging effects to your UI Here’s an example: <Pulsable isLoading={isLoading}> <YourComponent /> </Pulsable> Now that it's been stable for a while, I’m looking for feedback and ideas on how it can be improved! Feel free to check it out on GitHub ( https://github.com/abdheshnayak/react-pulsable ).

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
69%69% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
38%38% predicted probability of success on Indie Hackers, 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
37%37% 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 · Missing: arr, mrr, revenue
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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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