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Web scraping Walmart with Python can be challenging due to dynamically loaded content, complex HTML structures, and access restrictions. In our tests, a basic Python requests script returned a "Robot or human?" verification page instead of the product page, even when the status code was 200.
Imagine a company needs to track product prices, inventory, or page changes across dozens or even thousands of websites. Checking each page manually would quickly become repetitive and time-consuming. A scraping bot can automate this work by visiting web pages, extracting specific information, and collecting the results according to predefined rules.
A person can look at a web page or file and recognize names, prices, dates, and other details. A program, however, needs rules to identify how that information is organized. Data parsing applies those rules to recognize structures and fields, turning raw input into data that software can use.
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