There are many different reasons why you would want to use a web scraping library to automate the process of parsing HTML, collecting data across the web, and then storing or performing specialized marketing analysis on that data. It may be that you want to check keyword density and perform keyword analysis for a client with hundreds or even thousands of legacy blogs. Maybe a client’s previous web development company has locked a client out of their own website, and you are looking to pull every image from their old site while you wait for their legal action to be completed. You could be creating a script to scrape top news aggregator websites for articles on certain keywords for your clients. Or perhaps you are performing targeted market research to determine whether or not a new business is targeting a viable market space. Whatever the reason, working with web scrapers can be a valuable asset for the marketing analytics component of your SEO. There are a variety of tools and languages that web scrapers can run in, but many of the most popular tools are built in Python. Some of the most popular web scraping solutions include Selenium, Scrapy, and Beautiful Soup.
For projects of higher complexity, Scrapy is an enterprise-level solution based in Python that also uses XPath and XSL bindings to perform web scraping projects and select the information you are scraping. Scrapy’s library has many useful features for processing the data and storing in immediately usable formats, and although there is a higher learning curve, there are books and resources available that have adequate examples to onboard new users.
For a more unique solution, Beautiful Soup is a clean web scraping package with easy to learn bindings that use the lxml library instead of full XPath selection markup. Named after a Lewis Carroll poem, Beautiful Soup is one of the most popular options for parsing HTML and integrates into many enterprise solutions including Scrapy, which can accept Beautiful Soup objects while performing collection and analysis.
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