T5.rs – A cross-platform app development template written in Rust

Hacker News

A cross-platform full-stack application template developed with Rust, Cargo Mobile 2, Dioxus, Warp, Diesel, PostgreSQL, Supabase Auth, Bun and TailwindCSS. Available on https://github.com/albbus-stack/t5.rs You can now ship the same Rust codebase on Windows, Linux, Android and Web (and more to test). Currently this template supports authentication, routing and database interactions through an api server. The creation of this project was inspired by an attempt at rewriting in Rust the t4-app project ( https://github.com/timothymiller/t4-app ), a cross-platform template written in Typescript. For now I've tested this on a few devices (Windows, Linux, Android and Web) and works fine after having setup all the necessary tools and environment variables. I would greatly appreciate some testing on MacOS and iOS since I don't have access to those systems. Any other type of feedback is welcome here or directly on Github issues. Hope you guys enjoy this while waiting for the new Dioxus version, happy hacking

Visit product View on Hacker NewsMay 13, 2024

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

80%80% 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: mac, macos, new · Missing: agents, agent, cursor

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

55%55% 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 · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

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

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

42%42% 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

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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