Web Scraping with Python

Web Scraping with PythonFree Download Web Scraping with Python, 2nd Edition book in PDF written by Ryan Mitchell and published by O’Reilly Media, Inc.

According to the Author, “To those who have not developed the skill, computer programming can seem like a kind of magic. If programming is magic, web scraping is wizardry: the application of magic for particularly impressive and useful—yet surprisingly effortless—feats. In my years as a software engineer, I’ve found that few programming practices capture the excitement of both programmers and laymen alike quite like web scraping. The ability to write a simple bot that collects data and streams it down a terminal or stores it in a database, while not difficult, never fails to provide a certain thrill and sense of possibility, no matter how many times you might have done it before.

Web scraping is a diverse and fast-changing field, and I’ve tried to provide both high level concepts and concrete examples to cover just about any data collection project you’re likely to encounter. Throughout the book, code samples are provided to demonstrate these concepts and allow you to try them out. The code samples themselves can be used and modified with or without attribution (although acknowledgment is always appreciated). All code samples are available on GitHub for viewing and downloading.

What Is Web Scraping?

The automated gathering of data from the internet is nearly as old as the internet itself. Although web scraping is not a new term, in years past the practice has been more commonly known as screen scraping, data mining, web harvesting, or similar variations. General consensus today seems to favor web scraping, so that is the term I use throughout the book, although I also refer to programs that specifically traverse multiple pages as web crawlers or refer to the web scraping programs themselves as bots.

In theory, web scraping is the practice of gathering data through any means other than a program interacting with an API (or, obviously, through a human using a web browser). This is most commonly accomplished by writing an automated program that queries a web server, requests data (usually in the form of HTML and other files that compose web pages), and then parses that data to extract needed information.

About This Book

This book is designed to serve not only as an introduction to web scraping, but as a comprehensive guide to collecting, transforming, and using data from uncooperative sources. Although it uses the Python programming language and covers many Python basics, it should not be used as an introduction to the language. If you don’t know any Python at all, this book might be a bit of a challenge. Please do not use it as an introductory Python text. With that said, I’ve tried to keep all concepts and code samples at a beginning-to-intermediate Python programming level in order to make the content accessible to a wide range of readers. To this end, there are occasional explanations of more advanced Python programming and general computer science topics where appropriate. If you are a more advanced reader, feel free to skim these parts!

Table of Contents

  1. Your First Web Scraper
  2. Advanced HTML Parsing
  3. Writing Web Crawlers
  4. Web Crawling Models
  5. Scrapy
  6. Storing Data
  7. Reading Documents
  8. Cleaning Your Dirty Data
  9. Reading and Writing Natural Languages
  10. Crawling Through Forms and Logins
  11. Scraping JavaScript
  12. Crawling Through APIs
  13. Image Processing and Text Recognition
  14. Avoiding Scraping Traps
  15. Testing Your Website with Scrapers
  16. Web Crawling in Parallel
  17. Scraping Remotely
  18. The Legalities and Ethics of Web Scraping

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File Size: 6.84 MB                  Pages: 306               Please Read Disclaimer

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