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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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Concurrent Downloading

In the previous chapters, our crawlers downloaded web pages sequentially, waiting for each download to complete before starting the next one. Sequential downloading is fine for the relatively small example website but quickly becomes impractical for larger crawls. To crawl a large website of one million web pages at an average of one web page per second would take over 11 days of continuous downloading. This time can be significantly improved by downloading multiple web pages simultaneously.

This chapter will cover downloading web pages with multiple threads and processes and comparing the performance with sequential downloading.

In this chapter, we will cover the following topics:

  • One million web pages
  • Sequential crawler
  • Threaded crawler
  • Multiprocessing crawler
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