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Python Web Scraping Cookbook

You're reading from  Python Web Scraping Cookbook

Product type Book
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Pages 364 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Michael Heydt Michael Heydt
Profile icon Michael Heydt

Table of Contents (13) Chapters

Preface Getting Started with Scraping Data Acquisition and Extraction Processing Data Working with Images, Audio, and other Assets Scraping - Code of Conduct Scraping Challenges and Solutions Text Wrangling and Analysis Searching, Mining and Visualizing Data Creating a Simple Data API Creating Scraper Microservices with Docker Making the Scraper as a Service Real 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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