Sk

Skip – Build native iOS and Android apps from a single Swift codebase

Hacker News

Skip – Build native iOS and Android apps from a single Swift codebase

Hello Hacker News. I'm Marc, one half of the team that created skip.tools. Skip is a tool that transpiles your SwiftUI iOS app into a Kotlin Jetpack Compose app, and enables you to use a single language to create a complete app that reaches the entire mobile marketplace. What it is: Skip stands in contrast to other cross-platform development tools like Flutter, React Native, and Xamarin, in that it enables the creation of genuinely native applications for both of the dominant mobile platforms. It doesn't embed a separate engine or runtime into your app, but instead lets you use pure Swift and SwiftUI to create the iOS side of the app (as per Apple's recommended best practices for creating iOS apps), and transpiles it into a pure Kotlin and Jetpack Compose app for the Android side (which is Google's recommendation for building Android apps). So your application will use platform-native controls and will automatically have all the affordances provided by the platform vendor: animations, accessibility, and future-proof evolution alongside OS updates. How it works: you build a Skip app using the same tools that you use to create a standard iOS app: Xcode, Swift, and SwiftUI. Skip augments this workflow with a Swift Package Manager plugin called "skipstone", which transpiles your Swift into Kotlin each time you build your app, and launches the Android app side-by-side with the iOS app each time you run the app. The transpilation works not just on your primary app module, but also transitively processes all your dependent SwiftPM modules, so you can break complex projects down into individually testable sub-modules containing business logic or UI code. In fact, this is how our own adaptor modules for the standard frameworks are structured: SkipFoundation adapts the Foundation framework and SkipUI adapts the SwiftUI framework, so the same familiar API can be used when building the app. And there's a GitHub ecosystem of open-source modules supporting popular frameworks, including SQLite, Firebase, Lottie, and many other common building blocks of modern apps. Over the past year Skip has evolved into a fully-capable solution for creating best-in-class apps for both iOS and Android. And today we are delighted to announce the release of version 1.0, meaning that it is ready for production use. We have a wealth of videos and documentation available at https://skip.tools , and I'll be around to field any questions that any of you might have. Thanks in advance for taking a look! Home: https://skip.tools FAQ: https://skip.tools/docs/faq/ GitHub: https://github.com/skiptools/

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, para, ios · Missing: supports, reddit linkedin, podcasting
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos
89%89% 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
69%69% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released
58%58% 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 · Strong signals: platform · Missing: plus, intuitive, reviews
34%34% 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
18%18% 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.

Correct prediction on native model

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