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Python Web Scraping

Python Web Scraping

By : Jarmul
3 (2)
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Python Web Scraping

Python Web Scraping

3 (2)
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)
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Solving CAPTCHA

CAPTCHA stands for Completely Automated Public Turing test to tell Computers and Humans Apart. As the acronym suggests, it is a test to determine whether the user is human or not. A typical CAPTCHA consists of distorted text, which a computer program will find difficult to interpret but a human can (hopefully) still read.

Many websites use CAPTCHA to prevent bots from interacting with their website. For example, my bank website forces me to pass a CAPTCHA everytime I log in, which is a pain. This chapter will cover how to solve CAPTCHAs automatically, first through Optical Character Recognition (OCR) and then with a CAPTCHA solving API.

In this chapter, we will cover the following topics:

  • Solving CAPTCHAs
  • Using a CAPTCHA service
  • Machine learning and CAPTCHAs
  • Reporting errors

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