Book Image

Python Web Scraping - Second Edition

By : Jarmul
Book Image

Python Web Scraping - Second Edition

By: Jarmul

Overview of this book

The Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online. This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you'll see how to extract data from static web pages. You'll learn to use caching with databases and files to save time and manage the load on servers. After covering the basics, you'll get hands-on practice building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers. You'll determine when and how to scrape data from a JavaScript-dependent website using PyQt and Selenium. You'll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You'll find out how to automate these actions with Python packages such as mechanize. You'll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites. By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics.
Table of Contents (10 chapters)

Scraping the Data

In the previous chapter, we built a crawler which follows links to download the web pages we want. This is interesting but not useful-the crawler downloads a web page, and then discards the result. Now, we need to make this crawler achieve something by extracting data from each web page, which is known as scraping.

We will first cover browser tools to examine a web page, which you may already be familiar with if you have a web development background. Then, we will walk through three approaches to extract data from a web page using regular expressions, Beautiful Soup and lxml. Finally, the chapter will conclude with a comparison of these three scraping alternatives.

In this chapter, we will cover the following topics:

  • Analyzing a web page
  • Approaches to scrape a web page
  • Using the console
  • xpath selectors
  • Scraping results
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