How to scrape Craigslist

 Scraping Craigslist allows you to collect valuable data such as listings, prices, descriptions, locations, and contact details across categories like jobs, rentals, and services. Start by inspecting Craigslist’s webpage structure using browser developer tools to identify HTML tags that contain relevant information — typically <li> or <a> tags for listings and <span> tags for prices or dates.

Use Python tools such as BeautifulSoup, Scrapy, or Selenium to extract the data. BeautifulSoup is efficient for static pages, while Selenium handles Craigslist’s dynamic content. You can send requests using the Requests library, parse the HTML, and store results in CSV, Excel, or JSON formats for further analysis.

Craigslist employs anti-bot mechanisms, so use rotating proxies, user-agent headers, and delays between requests to prevent blocking.

For an easier and more scalable solution, use Web Scraping HQ’s Craigslist Scraper. It automates data collection from multiple cities and categories, delivering clean, structured data in real time — no coding needed. This helps businesses monitor listings, analyze market prices, or generate leads efficiently.

✅ Tip: Always follow Craigslist’s terms of service and use scraped data ethically for analysis, market research, or business intelligence.