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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

Storing data in Redis


Redis (REmote DIctionary Server) is an in-memory, key-value database, written in C. In the in-memory mode, Redis is extremely fast, with writing and reading being almost equally fast. Redis follows the publish/subscribe model and uses Lua scripts as stored procedures. Publish/subscribe makes use of channels to which a client can subscribe in order to receive messages. The most recent Redis version at the time of writing was 2.8.12. Redis can be downloaded from the home page at http://redis.io/. After unpacking the Redis distribution, issue the following command to compile the code and create all the binaries:

$ make

Run the server as follows:

$ src/redis-server

Now let's install a Python driver:

$ sudo pip install redis
$ pip freeze|grep redis
redis==2.10.1

It's pretty easy to use Redis when you realize it's a giant dictionary. However, Redis does have its limitations. Sometimes, it's just convenient to store a complex object as a JSON string (or other format). That...

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