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Nodino – Simple URL shortener built with ExpressJS, React and Redis

Hacker News

Nodino – Simple URL shortener built with ExpressJS, React and Redis

Hi there, I've just built this simple web app to play a bit with node/express on server and React/Stylus on frontend. http://nodino.herokuapp.com/ NOTE: demo has a safe-mode option that expires links after 30 minutes. This should reduce spammers impact. Source code is available at: https://github.com/apeacox/nodino Comments and feedbacks are welcome :-)

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Actual performance

8points
3comments
Made the leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
61%61% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
50%50% predicted probability of success on AppSumo, 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
44%44% 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
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
32%32% predicted probability of success on Product Hunt, 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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Product Hunt+5