React library to upload files directly to S3

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Hey HN, In past few weeks I have been developing Better Upload, a library that makes file uploads very simple for React. It uploads directly to your bucket in any S3-compatible service, like AWS S3 and Cloudflare R2. Multipart uploads work out of the box! Fully open-source. It also comes with copy-and-paste shadcn/ui components. If you want more control, there are also hooks available for the client. You can run code in your server before uploading, so adding auth and rate limiting is very easy. Files do not consume bandwidth of your server, it uses pre-signed URLs. It is compatible with any framework that uses standard Request / Response objects, like Next.js and Remix. You can even use a separate backend server, like Hono. Docs: https://better-upload.js.org/ GitHub: https://github.com/Nic13Gamer/better-upload

Visit product View on Hacker NewsOct 22, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% 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 · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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