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Mastering Social Media Mining with Python

You're reading from   Mastering Social Media Mining with Python Unearth deeper insight from your social media data with advanced Python techniques for acquisition and analysis

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781783552016
Length 338 pages
Edition 1st Edition
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Author (1):
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Marco Bonzanini Marco Bonzanini
Author Profile Icon Marco Bonzanini
Marco Bonzanini
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Table of Contents (10) Chapters Close

Preface 1. Social Media, Social Data, and Python FREE CHAPTER 2. #MiningTwitter – Hashtags, Topics, and Time Series 3. Users, Followers, and Communities on Twitter 4. Posts, Pages, and User Interactions on Facebook 5. Topic Analysis on Google+ 6. Questions and Answers on Stack Exchange 7. Blogs, RSS, Wikipedia, and Natural Language Processing 8. Mining All the Data! 9. Linked Data and the Semantic Web

Building a custom Python client


Throughout the book, we accessed different social media platform through Python libraries, either officially supported by the social media server themselves or provided by third parties.

This section answers the question: what if they don't provide a Python client for their API (and there is no unofficial library either)?

HTTP made simple

In order to implement the calls to the desired API, the recommended library for easy HTTP interactions is requests. From our virtual environment, use the following command:

$ pip install requests

The requests library offers a straightforward interface to perform HTTP calls. In order to test the library, we're going to implement a simple client for the httpbin.org service, a web service, that offers basic request/response interactions, perfect for our educational purposes.

The httpbin.org web page (http://httpbin.org/), explains the various endpoints and their meaning. To showcase the use of the requests library, we will implement...

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