EasyAria – A JavaScript library for manipulating HTML ARIA attributes

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Hello guys, I created my first library! It's a simple library called "EasyAria". The library aids web developers in building accessible websites and web apps by providing a convenient and type-safe way to manipulate HTML ARIA attributes in JavaScript. It's based on the latest W3C WAI-ARIA 1.2 Specification. It's also written entirely in TypeScript, so developers can catch errors during development. GitHub repo: https://github.com/emamoah/easy-aria Please feel free to try it out, and I'd like to know what you guys think!

Visit product View on Hacker NewsNov 19, 2023

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

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: apps · Missing: mac, agents, macos

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

59%59% 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: apps, way · Missing: mobile apps, ios, personal

45%45% 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

39%39% 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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