Abstract:
With the increasing availability of structured and semi-structured data on websites, there is a need for efficient tools to extract such information. Web scraping, the process of automatically extracting data from web pages, has been very important in applications like financial analytics and job market studies. This study presents a powerful, multifunctional web scraper created specially to retrieve employment and stock market data. Implemented using Python and its companion tools, including Beautiful Soup and Selenium, the scraper fixes every problem caused by dynamic site content, JavaScript rendering, and CAPTCHA methods. It has been verified and tested on websites for employment portals and livestock.
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