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Python Web Scraping Cookbook

You're reading from   Python Web Scraping Cookbook Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Length 364 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Scraping 2. Data Acquisition and Extraction FREE CHAPTER 3. Processing Data 4. Working with Images, Audio, and other Assets 5. Scraping - Code of Conduct 6. Scraping Challenges and Solutions 7. Text Wrangling and Analysis 8. Searching, Mining and Visualizing Data 9. Creating a Simple Data API 10. Creating Scraper Microservices with Docker 11. Making the Scraper as a Service Real 12. Other Books You May Enjoy

Working with CSV and JSON data

Extracting data from HTML pages is done using the techniques in the previous chapter, primarily using XPath through various tools and also with Beautiful Soup. While we will focus primarily on HTML, HTML is a variant of XML (eXtensible Markup Language). XML one was the most popular for of expressing data on the web, but other have become popular, and even exceeded XML in popularity.

Two common formats that you will see are JSON (JavaScript Object Notation) and CSV (Comma Separated Values). CSV is easy to create and a common form for many spreadsheet applications, so many web sites provide data in that for, or you will need to convert scraped data to that format for further storage or collaboration. JSON really has become the preferred format, due to its easy within programming languages such as JavaScript (and Python), and many database now support...

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