I Built 20+ Web Scrapers and Published Them for Free — Here's What I Learned

I recently built over 20 web scrapers and published them all on the Apify Store . Here's what I learned about building scrapers at scale, dealing with anti-bot systems, and making data extraction tools that actually work. The Stack Runtime: Node.js with ES modules Framework: Crawlee — handles retries, proxy rotation, rate limiting Browsers: Playwright for JS-heavy sites, Cheerio for static HTML Proxies: Residential proxies via Apify proxy pool Platform: Apify for hosting, scaling, and monetization What I Built Category Scrapers E-commerce Amazon, Walmart Real Estate Zillow Jobs Indeed, LinkedIn Jobs Social Media Reddit, TikTok, Pinterest, Facebook Reviews Trustpilot, TripAdvisor, Google Maps Places Tech/Dev Hacker News, DEV.to, GitHub Video YouTube SEO Google SERP Travel Booking.com All output clean, structured JSON with the fields you'd expect — prices, ratings, URLs, dates, etc. Hard Lessons Learned 1. CheerioCrawler vs PlaywrightCrawler My biggest mistake was defaulting to CheerioCr