Simple Crawling Server

Hacker News

I’ve built a crawling server that you can use to crawl urls It: - Accepts requests via GET and responds with JSON data, including page contents, properties, headers, and more. - Supports multiple crawling methods—use requests, Selenium, Crawlee, and more. Just specify the method by name! - Perfect for developers who need a versatile and customizable solution for simple web scraping and crawling tasks - Can read information about youtube links using yt-dlp Check it out on GitHub https://github.com/rumca-js/crawler-buddy There is also a docker image.

Visit product View on Hacker NewsJan 16, 2025

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2points

1comments

Did not reach leaderboard

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

73%73% 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: dock, tasks, using · Missing: mac, agents, macos

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io, including · Missing: https docs, excited, just released

49%49% 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

37%37% 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

36%36% 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

11%11% 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.

Correct prediction on native model

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