Web Scraping: How to Gather Articles Using GoogleNews library

<h2>Introduction</h2> In this blog post, we will cover how you can find news or articles of your interest on Google using the GoogleNews and newspaper libraries. With specifying the keywords you can have Python scrape all relevant content that you would typically find when performing manual search. The search will be nicely packaged into a notepad file. As an example, we will fetch articles news articles related to S&P500 and overall stock market. Basically, we are interested in understanding how the stock market behaved in a specified period (as our function will have a time period as a parameter). <h2>Libraries</h2> Let’s go over the libraries we will use to complete our goal: <ul> <li>GoogleNews: it allows accessing Google News data.</li> <li>Article: A class from the newspaper library for parsing news articles.</li> <li>requests: A library for making HTTP requests.</li> <li>nltk: The Natural Language Toolkit library for natural language processing tasks.</li> <li>UserAgent: A class from the fake_useragent library to generate random user agents for making requests.</li> </ul> By using a random UserAgent for each request, the script can appear more like a regular user browsing the web, which can avoid triggering any anti-scraping mechanisms that websites may have in place. <a href="https://python.plainenglish.io/web-scraping-how-to-gather-articles-using-googlenews-library-a7855e906277">Click Here</a>