Scraping Booking.com and Hotels.com for Travel Price Data

Travel sites like Booking.com and Hotels.com display thousands of hotel listings with prices that change constantly. Scraping this data lets you build price trackers, comparison tools, and travel analytics dashboards. Here's how to do it with Python. Why Scrape Travel Sites? Price monitoring — track hotel rates over time to find the best deals Market research — analyze pricing patterns across regions and seasons Comparison tools — build apps that show the cheapest option across platforms Revenue management — hotels use competitor data to optimize their own pricing The Challenge Travel sites are heavily protected. They use JavaScript rendering, CAPTCHAs, rate limiting, and bot detection. You'll need proxies and potentially a headless browser. Setting Up pip install requests beautifulsoup4 pandas Scraping Booking.com Search Results import requests from bs4 import BeautifulSoup import json def scrape_booking ( city , checkin , checkout , api_key ): url = f " https://www.booking.com/search