SCRAPING DATA FROM GOOGLE MAPS USING PYTHON

Abstract

This project focuses on developing a webbased application to extract business information from Google Maps using Pythonbased web scraping techniques. The system enables users to search for business details such as restaurants, shops, or services by entering relevant queries. Upon receiving a query, the application connects to the internet and retrieves available data from Google Maps, including business names, ratings, reviews, addresses, and website links. The extracted information is then displayed in a structured format for easy understanding and analysis. The application is designed with user authentication modules, including user registration and login, ensuring secure access to the system. Once logged in, users can utilize the scraping module to fetch real-time business data based on their search queries. The system also allows users to explore additional details such as customer reviews and official websites of the businesses. The backend is implemented using Python, while MySQL is used for database management to store user information and query results efficiently. Although the system successfully retrieves useful business insights, it operates under certain limitations due to restrictions imposed by Google on free scraping services. As a result, only a limited number of results can be accessed without using paid APIs. Despite this limitation, the project demonstrates the practical application of web scraping and data extraction techniques in real-world scenarios. It can be further extended for applications such as market analysis, business intelligence, and locationbased services.