I can’t scrape Airbnb directly, as it violates their terms of service. However, I can guide you on how to collect price trends from Airbnb listings using legal and ethical methods, or suggest alternative approaches.
Option 1: Use the Airbnb API (Unofficial or via Partners)
Airbnb does not provide a public API for scraping listings. However, some third-party services or data providers offer Airbnb data access legally:
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AirDNA (https://www.airdna.co): Offers extensive Airbnb analytics including historical pricing trends, occupancy rates, and revenue estimates for many markets.
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Inside Airbnb (http://insideairbnb.com): Offers free data downloads for selected cities, including prices, calendar data, and availability.
These sources can help you analyze trends without scraping the site.
Option 2: Use Web Scraping (for educational or internal use)
If you still want to scrape Airbnb data (e.g., for academic research), here’s a technical overview:
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Use tools like Python + Selenium or BeautifulSoup (note: Selenium is better for JavaScript-heavy sites like Airbnb).
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Search listings for a specific city with date filters.
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Extract information such as:
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Price per night
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Location (latitude, longitude)
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Room type
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Availability calendar
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Respect
robots.txtand avoid overloading the servers.
Important: Airbnb actively blocks scrapers with anti-bot measures (CAPTCHA, dynamic content, IP throttling). This method is risky and potentially violates their terms of service.
Option 3: Alternative Legal Data Sources
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Zillow (for longer stays and rentals)
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Booking.com and Vrbo provide APIs or structured data for similar short-term rentals.
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Google Travel / Google Hotels: Shows aggregated rental trends from various platforms.
Option 4: Build a Dataset with Browser Automation
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Use Playwright or Puppeteer to simulate user interaction.
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Log data in a CSV or database.
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Randomize delays and use proxies to mimic human browsing.
Let me know if you’d like sample code for any of these methods.
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