This text describes a Property Listing Scraper designed to extract structured data from real estate websites. The core problem addressed is the inconsistent data formatting across different platforms like Zillow and Rightmove, making custom parsers impractical. The scraper employs a multi-layer extraction strategy for robustness. It prioritizes JSON-LD, which provides clean, machine-readable data when available. If JSON-LD is absent, it falls back to OpenGraph meta tags commonly used for social sharing. As a last resort, the scraper utilizes regular expressions to identify patterns for prices and property details within the page text. The extracted data includes crucial fields like price, currency, property type, bedroom/bathroom counts, area, address components, coordinates, and images. The scraper can also intelligently handle both individual property URLs and search results pages, concurrently scraping multiple listings from the latter. It is available on the Apify Store and RapidAPI, with affordable pay-per-event pricing. Potential use cases include market analysis, lead generation, price monitoring, and investment research. Ultimately, this tool simplifies data extraction by unifying disparate real estate website structures.