Google Flights, a popular flight booking service, lacks a public API to access its data, prompting the use of web scraping as an alternative. This approach enables users to extract valuable information such as flight prices, schedules, and airline details, which can be beneficial for both travelers seeking the best deals and businesses aiming for market analysis and competitive intelligence. The article outlines the process of building a Google Flights scraper using Python, highlighting the steps involved, including setting up the environment, defining data classes, and implementing the main scraping logic using the Playwright library. It emphasizes the importance of handling challenges like IP blocking and CAPTCHAs, suggesting solutions like using Bright Data’s residential proxies and Web Unlocker for more efficient data extraction. The scraper is designed to gather comprehensive data, including airline names, departure and arrival times, and CO2 emissions, and saves the results in a JSON file for further analysis.