Weekly Plans – An open source React Native app

Hacker News

Hey guyz checkout my 1st React Native Project made using Expo. I made this project twice bcz 1st time my Ubuntu got corrupted & lost all my projects. Thank God I push some of my projects to Github. Then I made this project again on my Mac. If u have any feedback please give it. Its nothing groundbreaking though. A simple app to track weekly plans. & if u can plz give it a rating. The app is open source. Source Code - https://github.com/deadcoder0904/weeklyplans Official Website - https://weekly-plans.surge.sh/ Play Store Link - https://play.google.com/store/apps/details?id=com.deadcoder0... If you have any questions feel free to ask

Visit product View on Hacker NewsSep 28, 2017

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, google, apps · Missing: agents, macos, agent

79%79% 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.

TrustMRRFits verified-revenue profile · Strong signals: apps, google · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

35%35% predicted probability of success on AppSumo, 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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