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Syncthing-map – a utility to map syncthing devices and folders

Hacker News

Syncthing-map – a utility to map syncthing devices and folders

If you use the excellent Syncthing[1], you may quickly be lost in the various shares between devices. I was. This was the trigger to write a small application that creates a map of your devices, their folders, and how each is shared. It is directly based on the configuration file of each device. The stable version[2] generates a HTML file you can render in a browser to show the map (based on mermaid.js[3]). I just released an experimental feature[4] that starts a web server which will dynamically create the map based on configurations shared by the devices. Binaries are available as well[5]. I would be glad to hear any comments or advice (I am an amateur developper). Thanks! [1] https://syncthing.net/ [2] https://github.com/wsw70/syncthing-map/releases/tag/master [3] https://mermaid.js.org/#/ [4] https://github.com/wsw70/syncthing-map/blob/dev/README.md#au... [5] https://github.com/wsw70/syncthing-map/releases/tag/dev

Visit product View on Hacker NewsJan 10, 2023

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Hacker NewsStrong engagement from HN community · Strong signals: just released, io · Missing: https docs, excited, exist

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

29%29% 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

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

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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