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FancyLock – A Modern X11 (and soon Wayland) Screenlocker

Hacker News

FancyLock – A Modern X11 (and soon Wayland) Screenlocker

I've been wanting a fancy screen locker for linux, so I built FancyLock, a screen lock solution for Linux with X11 (and soon wayland) support. Key Features - Dynamic media playback during lock screen - Multi-monitor support - PAM-based authentication - Intelligent idle timeout - Highly configurable FancyLock aims to solve several pain points with existing screen lockers: - Boring, static lock screens - Poor multi-monitor support Technical Highlights - Written in Go - Uses X11 extensions for low-level window and input management - Flexible media playback with mpv - Configurable via JSON Current version is v0.0.1 and supports X11. Wayland support is planned. GitHub: https://github.com/tuxx/fancylock Would love to hear your thoughts and feedback! Edit: Happy to answer any questions about the implementation or design choices.

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
59%59% 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.
AppSumoStrong fit for a featured deal · Strong signals: soon · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, 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.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
49%49% 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
16%16% 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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