Scraping Zillow, an online real estate platform, can provide significant insights into the real estate market, including property prices, locations, features, and historical trends, which are valuable for market analysis and investment decisions. This comprehensive tutorial guides users through the process of building a web scraper using Python's Beautiful Soup and Requests libraries, while highlighting the importance of understanding Zillow's website structure and identifying key data points such as address, price, and property type. It also addresses the anti-scraping techniques employed by Zillow, such as CAPTCHAs and IP blocking, and suggests using Bright Data’s Scraping Browser to overcome these challenges by providing access to multiple IP addresses and bypassing detection. The tutorial further emphasizes the legal and ethical considerations of web scraping and provides instructions for saving extracted data in JSON or CSV formats. Additionally, it introduces an alternative approach using Bright Data’s Scraping Browser, which facilitates seamless data extraction by running Puppeteer scripts, and advises on adjusting configurations to avoid IP blocks.