Book Image

Python Web Scraping - Second Edition

By : Katharine Jarmul
Book Image

Python Web Scraping - Second Edition

By: Katharine 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)

Summary

This chapter analyzed a variety of prominent websites and demonstrated how the techniques covered in this book can be applied to them. We used CSS selectors to scrape Google results, tested a browser renderer and an API for Facebook pages, used a Sitemap to crawl Gap, and took advantage of an AJAX call to scrape all BMW dealers from a map.

You can now apply the techniques covered in this book to scrape websites that contain data of interest to you. As demonstrated by this chapter, the tools and methods you have learned throughout the book can help you scrape many different sites and content from the Internet. I hope this begins a long and fruitful career in extracting content from the Web and automating data extraction with Python!