Booking.com Full-Year Price Tracker
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Pay $2.00 for 1,000 results
The Yearly Data Scraper is a powerful, easy-to-use tool designed to automatically gather comprehensive data from Booking.com.
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.
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Configure Input Data:
Provide a list of hotel URLs in the
startUrls
key of the input. Here's an example:1{ 2 "startUrls": [ 3 "https://www.example.com/hotel1", 4 "https://www.example.com/hotel2" 5 ] 6}
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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_prices
function to scrape additional information, such as amenities or room details. - Modify the
startUrls
list to include any hotel URLs you wish to scrape.
Actor Metrics
10 monthly users
-
0 No stars yet
>99% runs succeeded
Created in Oct 2024
Modified 3 days ago