🏨 Google Hotels Scraper with Python + Crawlbase

This repository contains two powerful web scrapers for extracting hotel data from Google Hotels using the Crawlbase Crawling API:

• 🔍 Hotel Listings Scraper – Collect hotel names, prices, ratings, and links from search results.

• 🏷️ Hotel Detail Page Scraper – Visit each hotel’s page to extract detailed info like address, contact, and more.

📖 Read the full tutorial → How to Scrape Google Hotels with Python

🔧 Tools Used

• crawlbase – to access Crawlbase Crawling API

• BeautifulSoup – for HTML parsing

• json – for structured data storage

• Python 3.6+

📦 Installation

Install the required dependencies:

pip install crawlbase beautifulsoup4

🗺️ Scraper 1: Google Hotels Listings Scraper

File: google_hotels_listings_scraper.py

✅ What It Does

• Scrapes hotel listings from Google Hotels for a given location.
• Supports pagination by simulating clicks on the “Next” button.
• Saves the scraped data to google_hotels.json.

⚙️ How to Use

1. Replace CRAWLBASE_JS_TOKEN with your Crawlbase token.
2. Run the script:

python google_hotels_listings_scraper.py

🧪 Sample Output

[
  {
    "name": "The Plaza Hotel",
    "price": "$784",
    "rating": "4.6",
    "link": "https://www.google.com/travel/hotels/..."
  },
  ...
]

🏷️ Scraper 2: Google Hotel Detail Page Scraper

File: google_hotel_details_scraper.py

✅ What It Does

• Takes individual hotel URLs and scrapes additional details such as:

  • Address
  • Contact Info
  • Number of Reviews
  • Hotel Type

• Saves the results to google_hotel_details.json.

⚙️ How to Use

1. Replace CRAWLBASE_JS_TOKEN with your Crawlbase token.
2. Add a list of hotel URLs (you can reuse results from the listings scraper).
3. Run the script:

python google_hotel_details_scraper.py

🧪 Sample Output

[
  {
    "name": "The Plaza Hotel",
    "price": "$784",
    "rating": "4.6",
    "no_of_reviews": "1,234 reviews",
    "hotel_type": "5-star hotel",
    "address": "768 5th Ave, New York, NY 10019",
    "contact": "+1 212-759-3000",
    "link": "https://www.google.com/travel/hotels/..."
  },
  ...
]

🧠 Pro Tips

• Increase max_pages in the listings scraper to collect more data.
• Use output from listings as input to the detail scraper.
• Combine both scripts into a pipeline for full automation.