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Getting Started with Python Data Analysis

You're reading from   Getting Started with Python Data Analysis Learn to use powerful Python libraries for effective data processing and analysis

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781785285110
Length 188 pages
Edition 1st Edition
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introducing Data Analysis and Libraries FREE CHAPTER 2. NumPy Arrays and Vectorized Computation 3. Data Analysis with Pandas 4. Data Visualization 5. Time Series 6. Interacting with Databases 7. Data Analysis Application Examples 8. Machine Learning Models with scikit-learn Index

Interacting with data in Redis


Redis is an advanced kind of key-value store where the values can be of different types: string, list, set, sorted set or hash. Redis stores data in memory like memcached but it can be persisted on disk, unlike memcached, which has no such option. Redis supports fast reads and writes, in the order of 100,000 set or get operations per second.

To interact with Redis, we need to install the Redis-py module to Python, which is available on pypi and can be installed with pip:

$ pip install redis

Now, we can connect to Redis via the host and port of the DB server. We assume that we have already installed a Redis server, which is running with the default host (localhost) and port (6379) parameters:

>>> import redis
>>> r = redis.StrictRedis(host='127.0.0.1', port=6379)
>>> r
StrictRedis<ConnectionPool<Connection<host=localhost,port=6379,db=0>>>

As a first step to storing data in Redis, we need to define which kind of data...

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