Frej – iOS weather app as analog clocks

Hacker News

Weather apps nowadays seem to be less and less about data and just about looking nice. I was frustrated by this so I wrote Frej (from the Norse god of fair weather). https://apps.apple.com/se/app/frej/id1566974295?l=en You can instantly see the weather for the entire day (24h) in two circles of 12h each. A yellow arc shows when the sun is up. A blue arc when present shows rainfall, with a thicker line meaning lots of rain. Weather data is supplied by Open-Meteo (https://open-meteo.com/) which I found out about via a Show HN. The source code is on Github: https://github.com/boxed/frej

Visit product View on Hacker NewsNov 2, 2021

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

72%72% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, code · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps · Missing: mobile apps, personal, entrepreneurs

69%69% 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

40%40% 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

29%29% 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

20%20% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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