Linux and Windows CalDAV calendar client

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Hello, I have been developing self hosted CalDAV calendar Bloben (https://bloben.com), which is now available also as standalone Electron desktop client for Linux and Windows. It is using same client and server code base with some changes like: - switching from PostgreSQL database to SQLite - requests are handled with IPC - no account management, just single user Why Electron app when there is already self hosted client? I think there are some people, who don't want all features from self hosted version and using desktop app might be easier for them or it is just better alternative (be it maintenance, security, features). Published versions are advised to be for testing purposes only due to possibly many bugs. They can be found here: https://bloben.com/download Main git repository is here: https://github.com/nibdo/bloben-app Thank you and feel free to try it or ask if you are interested in anything.

Visit product View on Hacker NewsJan 21, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, single, using · Missing: mac, agents, macos

77%77% 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.

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

66%66% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

33%33% 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.

Incorrect prediction on native model

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