I Made an Event Countdown App in React Native

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I recently created an Events Countdown app for iOS. Basically, user can create event like Birthday, Anniversary, ... and the app will show a countdown time until or since the event. User can also add reminder days, weeks, months before or after the event. It's not shown in the video but the user can choose different display mode like: List, Grid or Carousel and sizes,... This is my first time trying this business model my apps. It's free to use. You can create unlimited number of events, reminders, you can switch between dark/light theme... All the core features of an Event Countdown apps are free. But there are interstitial ads after the user created an event once in a while. (using facebook audience network and google admob). Some premium features like layouts, online gallery, cloud syncing,... are unlocked through a subscription monthly or yearly. I created the project with [typescript-react-native-starter](https://github.com/NewBieBR/typescript-react-native-starter). I also tried to contribute some open-source components like: - [react-native-easy-icon](https://github.com/NewBieBR/react-native-easy-icon): wrapper component of react-native-vector-icons to use icon easily - [react-native-unsplash](https://github.com/NewBieBR/react-native-unsplash): The online gallery feature that you see from the video use directly this component. It's basically a photos browser using the unsplash api. - [react-native-store-rate](https://github.com/NewBieBR/react-native-store-rate): I'm still testing this so I don't recommend you to use All of my components above are written in typescript so it's kinda self-documented, I didn't have the time to update the documentation so PRs are welcome. You can download it here: https://apps.apple.com/us/app/timecount-day-counter/id1497946231 I would love to hear feedbacks. Thanks.

Visit product View on Hacker NewsMar 26, 2020

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting

94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

57%57% 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

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

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

20%20% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

14%14% 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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