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Python 3 Text Processing with NLTK 3 Cookbook

You're reading from   Python 3 Text Processing with NLTK 3 Cookbook

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Product type Paperback
Published in Aug 2014
Publisher
ISBN-13 9781782167853
Length 304 pages
Edition 2nd Edition
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Author (1):
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Jacob Perkins Jacob Perkins
Author Profile Icon Jacob Perkins
Jacob Perkins
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Table of Contents (12) Chapters Close

Preface 1. Tokenizing Text and WordNet Basics FREE CHAPTER 2. Replacing and Correcting Words 3. Creating Custom Corpora 4. Part-of-speech Tagging 5. Extracting Chunks 6. Transforming Chunks and Trees 7. Text Classification 8. Distributed Processing and Handling Large Datasets 9. Parsing Specific Data Types A. Penn Treebank Part-of-speech Tags
Index

Storing an ordered dictionary in Redis


An ordered dictionary is like a normal dict, but the keys are ordered by an ordering function. In the case of Redis, it supports ordered dictionaries whose keys are strings and whose values are floating point scores. This structure can come in handy in cases where we need to calculate the information gain (covered in the Calculating high information words recipe in Chapter 7, Text Classification), and when you want to store all the words and scores for later use.

Getting ready

Again, you'll need Redis and redis-py installed with an instance of redis-server running, as explained in the earlier recipe, Storing a frequency distribution in Redis.

How to do it...

The RedisOrderedDict class in rediscollections.py extends collections.MutableMapping to get a number of dict compatible methods for free. Then, it implements all the key methods that require Redis ordered set (also known as Zset) commands:

class RedisOrderedDict(collections.MutableMapping):
  def __init__...
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