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A free private journaling app

Hacker News

A free private journaling app

https://github.com/inoda/private_journal Built this to use myself, and I'm curious if anybody would be interested in using it. I'm also wondering if anybody has tips to make it more secure (I'm super super new to encryption and whatnot). The security is probably a bit overkill since chances are that nobody cares about what I'm journaling, but it is fun to implement from a code standpoint.

Visit product View on Hacker NewsJun 13, 2019

Actual performance

9points

Made the leaderboard

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Product HuntUnlikely to reach the leaderboard · Strong signals: new, using, code · Missing: mac, agents, macos

50%50% 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 NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

31%31% predicted probability of success on Indie Hackers, 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

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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