Website Scraping With Python

Website Scraping With Python×200&!1&btvi=1&fsb=1&xpc=l4B7eCrvxi&p=https%3A//


There are a lot of use cases where you can leverage your knowledge of website scraping. Some might be common sense, while others are extreme cases. In this section you will find some use cases where you can leverage your knowledge. The main reason to create a scraper is to extract information from a website. This information can be a list of products sold by a company, nutrition details of groceries, or NFL results from the last 15 years. Most of these projects are the groundwork for further data analysis: gathering all this data manually is a long and error-prone process. Sometimes you encounter projects where you need to extract data from one website to load it into another—a migration. I recently had a project where my customer moved his website to WordPress and the old blog engine’s export functionality wasn’t meant to import it into WordPress. I created a scraper that extracted all the posts (around 35,000) with their images, did some formatting on the contents to use WordPress short codes, and then imported all those posts into the new website.

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