Lucia 1.0 – A simple and flexible auth library for TypeScript

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This is a project I've been working for nearly a year. Lucia is a server-side authentication library for TypeScript that aims to be unintrusive, straightforward, and flexible. At its core, it’s a library for managing users and sessions, providing the building blocks for setting up auth just how you want. Database adapters allow Lucia to be used with any modern ORMs/databases and integration packages make it easy to implement things like OAuth. Key features: - Session based auth - Support for popular databases/ORMs - Built in support for frameworks: Express, SvelteKit, Astro, Next.js - OAuth support - Multiple auth methods with keys - Email verification links and OTPs with tokens

Visit product View on Hacker NewsApr 10, 2023

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

76%76% 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: user, email · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

57%57% 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: users · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

40%40% 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

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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