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MeteorJS's tracker.js ported to Android

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MeteorJS's tracker.js ported to Android

Did this as a side project in writing a library for android. I haven't really used meteor's deps/tracker system heavily at all, but a friend was describing it to me and it seemed pretty cool. Luckily all of meteor is open sourced, and tracker.js is surprisingly simple. Here's the lib: https://github.com/dinosaurwithakatana/AndroidTracker It contains a sample application that shows a simple example of how to use it. I've also written a basic intellij code generator plugin (found: [here](https://github.com/dinosaurwithakatana/android-tracker-intellij-plugin)). One thing I'd like to do, is make the plugin obsolete through annotations, but I'm not quite sure how to do it (See my stackoverflow post [here](https://stackoverflow.com/questions/27640291/annotation-processing-generate-methods-based-on-an-annotated-field)). This hasn't been tested outside of the sample application, so let me know what you think and what improvements could be made. Thanks!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% 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.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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.
Product HuntUnlikely to reach the leaderboard · Strong signals: code, open · Missing: mac, agents, macos
27%27% 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
15%15% 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.

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