Em

Embed ViteJS-compiled assets in your Rust binary

Hacker News

Embed ViteJS-compiled assets in your Rust binary

Dear HN community -- Merry Christmas, Happy Hannukah, and all the best in the upcoming new year :) Just wanted to share a crate I've been working on that I finally felt was ready to publish. It's primary purpose is to make it easy to integrate ViteJS with your Rust project. It tries to be a low-touch integration so you can continue using ViteJS as you normally would. The next step for this is to show the community how you could integrate this into templating engines and web frameworks like `actix-web`/`axum`/`poem`/etc. I've previously drafted a ViteJS integration for Rust backends[1] in `create-react-app` and I hope to adapt that to use `vite-rs` soon. [1] https://github.com/Wulf/create-rust-app/blob/main/create-rus...

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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: new, using · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: soon · Missing: plus, platform, intuitive
59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
54%54% 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 · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · 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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