Booking.com Full-Year Price Scraper
Pricing
$10.00/month + usage
Booking.com Full-Year Price Scraper
The Yearly Data Scraper is a powerful, easy-to-use tool designed to automatically gather comprehensive data from Booking.com.
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Pricing
$10.00/month + usage
1
65
1
Issues response
17 hours
Last modified
5 days ago
Hotel Data Scraper
This project is a robust web scraping solution built with Playwright and Python, designed to extract detailed hotel data from various hotel booking pages. The tool scrapes information such as hotel names, check-in/check-out dates, and prices, and exports the data into an Excel file. Additionally, it integrates seamlessly with Apify for storing the extracted data in a dataset for further processing.
Key Features
- Accurate Data Extraction: Scrapes hotel names, check-in/check-out dates, and prices for any provided hotel URL.
 - Date Navigation: Automatically navigates between calendar months to extract data for the required period.
 - Excel Export: Saves the extracted data to an Excel file for easy sharing and analysis.
 - Apify Integration: Pushes the extracted data to an Apify dataset, enabling cloud-based storage and further processing.
 - Error Handling and Retries: The scraper automatically retries failed attempts to ensure consistent data extraction.
 - Price Formatting: Cleans and formats prices, removing unnecessary characters such as currency symbols.
 
Benefits for You
- Easy Data Access: Automatically extracts the data you need from multiple hotel booking pages.
 - Time-Saving: Eliminates manual data collection, saving time and improving efficiency.
 - Scalable: Can handle multiple hotel URLs in one run, ideal for large-scale data collection.
 - Reliable: Includes retry mechanisms to handle network errors and page loading issues.
 - Flexible: Can be easily customized to scrape additional data or integrate with other systems.
 
- 
Configure Input Data:
Provide a list of hotel URLs in the
startUrlskey of the input. Here's an example:{"startUrls": ["https://www.example.com/hotel1","https://www.example.com/hotel2"]} - 
Run the Scraper:
Once the setup is complete, run the scraper The script will:
- Extract data from each provided hotel URL.
 - Save the data to an Excel file (named with a timestamp for easy identification).
 - Push the data to the Apify dataset for cloud-based storage.
 
 
Output
- Excel File: The extracted data will be saved in an Excel file (
hotel_data_<timestamp>.xlsx). - Apify Dataset: All the extracted data will be pushed to your Apify dataset for further processing or storage.
 
Customization
- You can adjust the 
extract_dates_and_pricesfunction to scrape additional information, such as amenities or room details. - Modify the 
startUrlslist to include any hotel URLs you wish to scrape. 
