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)

CAPTCHAs and machine learning

With advances in deep learning and image recognition, computers are getting better at properly identifying text and objects in images. There have been several interesting papers and projects applying these deep learning image recognition methods to CAPTCHAs. One Python-based project (https://github.com/arunpatala/captcha) uses PyTorch to train a solver model on a large dataset of CAPTCHAs. In June 2012, Claudia Cruz, Fernando Uceda, and Leobardo Reyes (a group of students from Mexico) published a paper with an 82% solving accuracy on reCAPTCHA images (http://dl.acm.org/citation.cfm?id=2367894). There have been several other research and hacking attempts, especially those targeting the often-included audio components of the CAPTCHA images (which are included for accessibility purposes).

It's unlikely that you'll need more than your OCR or API-based CAPTCHA-service to solve...