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I have built a code library for Flutter projects

Hacker News

I have built a code library for Flutter projects

As a Flutter fan since 2019, the number of mobile and web apps I developed with Flutter grew over the years. A nice side effect was that over time, a library of reusable widgets emerged that were often useful in my future projects. For example, there's the DashedPathPainter, which converts any path to a dashed path. Similarly, there's the AnimatedBorderPainter, which adds an animated border to its child, similar to the Trim Path feature from Adobe AfterEffects. Or the ChatBubble, inspired by WhatsApp and Telegram, which might be useful in an app with a chat function. I built many of these widgets from scratch because I didn't want to add another package to my pubspec.yaml for a single function. Of course, I also use packages for dependency injection, state management, or as an add-on for functional programming. But I've never been a fan of adding another dependency to my project, just for a few helper functions or a single widget. I thought that maybe I'm not the only Flutter developer in this situation. So I came up with the idea for Flutter Code Snippets: a simple code library for Flutter widgets, entire screens, as well as all kinds of helper functions. You can search for the right component, copy the code and paste it into your project. Done! At least that's how simple I imagine it to be ;) Since I had already built a small library from my existing projects, I still had to build the frontend (a web app built with Flutter), add authentication and a database (Firestore), integrate a payment flow (Stripe) and write some backend logic (Google Cloud Functions). The result can be seen at https://flutter-code-snippets.web.app. I'm now at a point where I've completed all the basic work I wanted to do, and I'm looking for another round of feedback. I'd love for you guys to check it out and let me know what you think. Thanks!

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Actual performance

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps, stripe · Missing: mac, agents, macos
84%84% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, google, widgets · Missing: mobile apps, ios, personal
41%41% 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
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
31%31% 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 · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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