- eBook:Python Web Scraping: Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python, 2nd Edition
- Author:Katharine Jarmul, Richard Lawson
- Edition:2 edition
- Data:May 30, 2017
- Pages:220 pages
- Format:PDF, ePUB
- A hands-on guide to web scraping using Python with solutions to real-world problems
- Create a number of different web scrapers in Python to extract information
- This book includes practical examples on using the popular and well-maintained libraries in Python for your web scraping needs
Book DescriptionThe 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 jаvascript-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.
What you will learn
- Extract data from web pages with simple Python programming
- Build a concurrent crawler to process web pages in parallel
- Follow links to crawl a website
- Extract features from the HTML
- Cache downloaded HTML for reuse
- Compare concurrent models to determine the fastest crawler
- Find out how to parse jаvascript-dependent websites
- Interact with forms and sessions
Chapter 2: Scraping the Data
Chapter 3: Caching Downloads
Chapter 4: Concurrent Downloading
Chapter 5: Dynamic Content
Chapter 6: Interacting with Forms
Chapter 7: Solving CAPTCHA
Chapter 8: Scrapy
Chapter 9: Putting It All Together