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Python 3 Text Processing with NLTK 3 Cookbook

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

Product type Book
Published in Aug 2014
Publisher
ISBN-13 9781782167853
Pages 304 pages
Edition 1st Edition
Languages
Author (1):
Jacob Perkins Jacob Perkins
Profile icon Jacob Perkins

Table of Contents (17) Chapters

Python 3 Text Processing with NLTK 3 Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Tokenizing Text and WordNet Basics Replacing and Correcting Words Creating Custom Corpora Part-of-speech Tagging Extracting Chunks Transforming Chunks and Trees Text Classification Distributed Processing and Handling Large Datasets Parsing Specific Data Types Penn Treebank Part-of-speech Tags
Index

Parallel list processing with execnet


This recipe presents a pattern for using execnet to process a list in parallel. It's a function pattern for mapping each element in the list to a new value, using execnet to do the mapping in parallel.

How to do it...

First, we need to decide exactly what we want to do. In this example, we'll just double integers, but we could do any pure computation. Following is the remote_double.py module, which will be executed by execnet. It receives a 2-tuple of (i, arg), assumes arg is a number, and sends back (i, arg*2). The need for i will be explained in the next section.

if __name__ == '__channelexec__':
  for (i, arg) in channel:
    channel.send((i, arg * 2))

To use this module to double every element in a list, we import the plists module (explained in the How it works... section) and call plists.map() with the remote_double module, and a list of integers to double.

>>> import plists, remote_double
>>> plists.map(remote_double, range(10))
...
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