HNWidgets – Hacker News Widget for iOS

Hacker News

As an avid HN user I wanted to have a simple widget showing me the top links shared on here, I also wanted to experiment for the first time with WidgetKit, this is what I came up with. HNWidgets is open source and offers a simple widget in three different sizes (medium, large, extra-large). You can choose between different HN lists to fetch links from and how frequently the widget should refresh its content. It's currently being rolled out on the App Store so the link in the README might still not work for some people. Hope you find it useful!

Visit product View on Hacker NewsOct 24, 2023

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

69%69% 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.

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

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, hacker news, io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% 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

19%19% 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.

Incorrect prediction on native model

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