Extracting Data with Web Scraping
Explore how to extract data from web pages using web scraping techniques with Python. Learn to send HTTP requests, parse HTML content with BeautifulSoup, extract specific elements like titles and links, navigate webpage structures, and export data for analysis. This lesson provides practical skills to gather online data when APIs are not available.
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Introduction to web scraping
Web scraping is a method for extracting data from web pages. With web scraping, we can extract data in HTML, XML, or JSON format from webpages, parse it, and extract the relevant data. We can create scripts to automatically retrieve and parse data from web pages according to a schedule and extract online data, such as comments from a forum or a social media platform or the latest price of product items from Amazon.
Web scraping can also be used as a one time process to extract relevant data. It has a wide range of applications, including data mining, data analysis, online market research, and more. It’s a useful tool for extracting data from websites that do not provide an API.
Python is an awesome tool for web scraping. It has two great libraries for web scraping called requests and Beautifulsoup.
The requests library
The requests library lets us send HTTP requests to websites and handle the response. The most common type of request for our purpose is a get request. We use a get request to retrieve information from a server or a service. If the request is successful, the server will return a response, which is the data we requested, usually in HTML/JSON format.
The Beautifulsoup library
After creating a successful request ...