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Python Web Scraping

You're reading from Python Web Scraping Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python

Product type Paperback

Published in May 2017

Publisher

ISBN-13 9781786462589

Length 220 pages

Edition 2nd Edition

Languages

HTML

Tools

PyQt

Concepts

Data Mining

Author (1):

Katharine Jarmul

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to Web Scraping FREE CHAPTER

2. Scraping the Data

3. Caching Downloads

4. Concurrent Downloading

5. Dynamic Content

6. Interacting with Forms

7. Solving CAPTCHA

8. Scrapy

9. Putting It All Together

Facebook

To demonstrate using a browser and API, we will investigate Facebook's site. Currently, Facebook is the world's largest social network in terms of monthly active users, and therefore, its user data is extremely valuable.

The website

Here is an example Facebook page for Packt Publishing athttps://www.facebook.com/PacktPub:

Viewing the source of this page, you would find that the first few posts are available, and that later posts are loaded with AJAX when the browser scrolls. Facebook also has a mobile interface, which, as mentioned in Chapter 1, Introduction to Web Scraping, is often easier to scrape. The same page using the mobile interface is available at https://m.facebook.com/PacktPub:

If we interacted with the mobile website and then checked...

The rest of the chapter is locked

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Authors (1)

Jarmul

Jarmul

Katharine Jarmul is a data scientist and Pythonista based in Berlin, Germany. She runs a data science consulting company, Kjamistan, that provides services such as data extraction, acquisition, and modelling for small and large companies. She has been writing Python since 2008 and scraping the web with Python since 2010, and has worked at both small and large start-ups who use web scraping for data analysis and machine learning. When she's not scraping the web, you can follow her thoughts and activities via Twitter (@kjam)

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