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Scraping pipeline that uses hidden api calls to extract needed data from Booking.com.

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Booking.com API Scraper

Overview

The Booking.com API Scraper is a tool designed to quickly retrieve data from Booking.com using the hidden API. This approach enables fast data extraction without the need for proxy servers, streamlining the scraping process.

Features

  • Efficient Data Retrieval: Utilizes Booking.com's hidden API for rapid extraction of hotel information.

  • No Proxy Requirement: Unlike traditional web scraping, this method bypasses the need for proxy servers, reducing costs and complexity.

  • Comprehensive Hotel Overview: Gathers essential details such as hotel names, star ratings, distance from the center, and the lowest available price.

  • Data Trend Analysis: Ideal for regular scraping to track price trends, making it a valuable tool for market analysis.

Limitations

  • Overview Pages Only: The API provides access to overview pages, limiting detailed information to what's available on the hotel list.

  • Machine Learning Potential: While current functionality is focused on overview data, the collected information serves as a foundation for potential machine learning applications in the future.

Use Cases

  • Daily Price Tracking: Daily scraping allows tracking price changes over time, enabling users to identify trends and make informed decisions.

  • Data for Machine Learning: The extracted data provides a rich dataset for potential machine learning projects related to hotel pricing and market analysis.

Sibling Scraper

This scraper has a sibling built with the Scrapy framework, allowing for more detailed information retrieval by crawling individual hotel pages. However, please note that this method is more resource-intensive as it requires the usage of proxies due to Booking.com's bot detectors. Explore the sibling scraper here: Booking.com Scrapy Scraper.

License

This project is licensed under the MIT License.

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Scraping pipeline that uses hidden api calls to extract needed data from Booking.com.

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  • Python 100.0%