How to Scrape Booking.com in 2026: Hotel Data, Prices, and Reviews

Booking.com holds one of the richest datasets in the travel industry — hotel listings, nightly rates, guest reviews, availability calendars, and property photos across millions of properties worldwide. Whether you're building a price comparison tool, analyzing travel trends, or doing market research for the hospitality industry, Booking.com data is incredibly valuable. But scraping it? That's where things get interesting. In this guide, I'll walk you through scraping Booking.com hotel data with Python — what works, what doesn't, and the anti-bot challenges you'll face in 2026. What Data Can You Extract from Booking.com? Before writing any code, let's map out what's available: Hotel listings — name, star rating, address, coordinates, property type Pricing — nightly rates, total stay cost, taxes, discounts Availability — room types, dates available, occupancy limits Reviews — guest scores, review text, reviewer country, review date Photos — property images, room photos Amenities — WiFi,