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TapLock – double tap to lock your Android device

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TapLock – double tap to lock your Android device

When I switched from a Samsung to a Pixel, I was shocked to discover that the 'double-tap to lock' feature (where you double-tap an empty area of the home screen to lock your device) wasn't a native option. This feature existed as far back as 2014 on my LG G3, so why is it missing on the Pixel? While there are alternatives on the Play Store, most are either closed-source or bundled into custom launchers — neither of which I wanted. Sending the lock-screen signal requires the Accessibility Service, and I wasn’t comfortable granting that level of access to a closed-source third-party app. So, I decided to create my own solution. My app is completely open-source, contains no tracking or analytics libraries, and doesn’t make any external requests. The Accessibility Service permission is used solely to send the lock-screen command. I tried to find an alternative to locking the screen without requiring Accessibility permissions but the options either required root or weren't what I needed. I also saw this as a chance to explore modern Android development. The last time I built an app from scratch, Jetpack Compose didn’t even exist. While I didn’t hate the experience, I won’t say I miss the days of wrestling with XML either. That said, some aspects of Compose felt harder to fully grasp and work with. You can download it here: https://play.google.com/store/apps/details?id=com.ah.taplock Source code is here: https://github.com/modelorona/TapLock Any suggestions or feedback, please feel free to leave here or on the repo.

Visit productView on Hacker NewsDec 21, 2024
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58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, io · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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