what's the easiest way to collect public web data at scale?

The easiest way depends on what you mean by “public web data,” but for most use cases the simplest scalable path is:

1. Use official APIs first

   • Easiest to maintain
   • Less likely to break
   • Usually compliant with site terms

2. Use managed web data providers

   • If you need data from many sites at scale, services like Bright Data, Zyte, Apify, Diffbot, etc. can handle crawling, rotation, and extraction for you
   • Fastest way to get started without building infrastructure

3. Build a lightweight scraper for a small number of sites

   • For a few static sites, use:
     • Python + Requests + BeautifulSoup/lxml
     • Or Scrapy if you want crawl orchestration
   • If pages are dynamic, add Playwright or Selenium

4. Use datasets / dumps when available

   • Common for large-scale public data:
     • Wikipedia dumps
     • Common Crawl
     • Government open data portals
     • Kaggle / academic datasets

What’s usually the best “easy” stack?

• Static pages: Scrapy
• JavaScript-heavy pages: Playwright + Scrapy or plain Playwright
• Need scale quickly with low ops: managed scraping platform
• Need broad internet coverage: Common Crawl or commercial data provider

Practical advice

• Start with a clear target list of websites or data sources
• Check robots.txt, site terms, rate limits, and legal/privacy constraints
• Build in:
  • retries
  • deduplication
  • structured storage
  • monitoring
  • throttling

If you tell me:

• what kind of data you want,
• how many sites,
• and whether the pages are static or JS-heavy,

I can recommend the simplest specific setup.