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)

LXML and Family Trees

lxml also has the ability to traverse family trees within the HTML page. What is a family tree? When you used your browser's developer tools to investigate the elements on the page and you were able to expand or retract them, you were observing family relationships in the HTML. Every element on a web page can have parents, siblings and children. These relationships can help us more easily traverse the page.

For example, if I want to find all the elements at the same node depth level on the page, I would be looking for their siblings. Or maybe I want every element that is a child of a particular element on the page. lxml allows us to use many of these relationships with simple Python code.

As an example, let's investigate all children of the table element on the example page:

>>> table = tree.xpath('//table')[0]
>>> table.getchildren()
[<Element tr at...