DuckieTV (Tv-Show tracker) now runs standalone on Windows/Linux/MacOS

Hacker News

I've just finished wrapping up my AngularJS web-app DuckieTV in node-webkit so that now it can run not only as a Chrome or Opera plugin, but also standalone on Windows, Mac and Linux. This makes DuckieTV the most cross-platform app i've ever built and i'm pretty proud. I started this project somewhere in february this year as a chrome extension to teach myself AngularJS and I've come a long way: DuckieTV is a web-app built with pure AngularJS that takes care of TV-Show addicts by providing a personalized TV-Show calendar. DuckieTV makes sure the information is always up-to-date and gives you an integrated blocking-resistant torrent search to help you get to the right download as easy as possible. With the integrated DuckieTorrent client you can connect DuckieTV to your local µTorrent/BitTorrent client and be updated on the download progress without switching applications. Experimental ChromeCast integration even provides the possibility to stream videos to your TV while still downloading. More info, screenshots, changelog, and release on github: https://SchizoDuckie.github.io/DuckieTV

Visit product View on Hacker NewsNov 5, 2014

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos · Missing: agents, agent, cursor

66%66% 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: started · Missing: supports, reddit linkedin, podcasting

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on AppSumo, 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

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.

TrustMRRLess likely to generate early MRR · Strong signals: personal, video, way · Missing: mobile apps, ios, entrepreneurs

34%34% 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

13%13% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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