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Parallel Programming with Python

You're reading from Parallel Programming with Python Develop efficient parallel systems using the robust Python environment.

Product type Paperback

Published in Jun 2014

Publisher

ISBN-13 9781783288397

Length 124 pages

Edition 1st Edition

Languages

Python

Concepts

Parallel Programming

Author (1):

Palach

View More author details

Table of Contents (10) Chapters

Preface

1. Contextualizing Parallel, Concurrent, and Distributed Programming FREE CHAPTER

2. Designing Parallel Algorithms

3. Identifying a Parallelizable Problem

4. Using the threading and concurrent.futures Modules

5. Using Multiprocessing and ProcessPoolExecutor

6. Utilizing Parallel Python

7. Distributing Tasks with Celery

8. Doing Things Asynchronously

Index

Chapter 3. Identifying a Parallelizable Problem

The previous chapter presented some of the different ways in which we can think about a problem in terms of parallelism. Now we will analyze some specific problems that will be useful in guiding us throughout the implementation.

This chapter covers the following topics:

Obtaining the highest Fibonacci value for multiple inputs
Crawling the Web

The rest of the chapter is locked

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83

Tech Concepts

36

Programming languages

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Authors (1)

Palach

Palach

Jan Palach has been a software developer for 13 years, having worked with scientific visualization and backend for private companies using C++, Java, and Python technologies. Jan has a degree in Information Systems from Estácio de Sá University, Rio de Janeiro, Brazil, and a postgraduate degree in Software Development from Paraná State Federal Technological University. Currently, he works as a senior system analyst at a private company within the telecommunication sector implementing C++ systems; however, he likes to have fun experimenting with Python and Erlang—his two technological passions. Naturally curious, he loves challenges and learning new technologies, meeting new people, and learning about different cultures.

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