O. Manik, P. Venkata Siva Nandha, P. Chaitanya, Mr.A.T.Barani Vijay Kumar
Abstract
This project presents an advanced web scraping solution leveraging the Playwright framework, designed for developers requiring robust, scalable, and dynamic content extraction capabilities. Unlike basic web scrapers that rely on static HTML parsing, this project enables real-time interaction with websites, allowing full rendering of JavaScript- based elements. By automating browser interactions, the scraper supports complex websites, ensuring the retrieval of dynamic content with full JavaScript execution.
The Advanced Web Scraper provides multiple data extraction techniques, including post contents, links, visible text, query-based searches, and custom tag extraction, making it highly versatile. Additionally, it supports multiple output formats such as text, JSON, and CSV, allowing flexibility in data storage. The script handles relative links, network resilience, and errors efficiently, providing seamless and uninterrupted scraping.
This project is aimed at developers with experience in browser automation who need fine grained control over scraping operations and require handling dynamic websites with real-time rendering. By offering robust features, such as enumerated data types, custom tag selection, and Playwright’s built-in functionalities, this tool significantly enhances the efficiency and accuracy of web data extraction projects.
Keywords
Assistive technology, Dynamic Extraction, Multiple Output Formats, Custom Tag Selection
Conclusion
The Advanced Web Scraper project effectively demonstrates the capabilities of modern web scraping techniques using Python and the Playwright library for browser automation. By enabling users to extract diverse types of data from web pages, including paragraphs, links, all text content, and specific elements through search queries or custom tags, the scraper caters to a wide range of web scraping needs.
Overall, this project not only serves as a practical tool for data extraction but also serves as an educational resource for understanding the principles of web scraping and automation. The use of asynchronous programming with asyncio enhances its efficiency, making it suitable for scraping large volumes of data or processing multiple requests concurrently.
References
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How to Cite This Paper
O. Manik, P. Venkata Siva Nandha, P. Chaitanya, Mr.A.T.Barani Vijay Kumar (2026). DYNAMIC WEB DATA EXTRACTION. International Journal of Computer Techniques, 13(3). ISSN: 2394-2231.
