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Home > Computing and Information Technology Books > Computer programming / software engineering > Web programming > Parallel Programming with Python: Develop efficient parallel systems using the robust Python environment.
Parallel Programming with Python: Develop efficient parallel systems using the robust Python environment.

Parallel Programming with Python: Develop efficient parallel systems using the robust Python environment.


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About the Book

Key Features Book DescriptionStarting with the basics of parallel programming, you will proceed to learn about how to build parallel algorithms and their implementation. You will then gain the expertise to evaluate problem domains, identify if a particular problem can be parallelized, and how to use the Threading and Multiprocessor modules in Python. The Python Parallel (PP) module, which is another mechanism for parallel programming, is covered in depth to help you optimize the usage of PP. You will also delve into using Celery to perform distributed tasks efficiently and easily. Furthermore, you will learn about asynchronous I/O using the asyncio module. Finally, by the end of this book you will acquire an in-depth understanding about what the Python language has to offer in terms of built-in and external modules for an effective implementation of Parallel Programming. This is a definitive guide that will teach you everything you need to know to develop and maintain high-performance parallel computing systems using the feature-rich Python.What you will learn Explore techniques to parallelize problems Integrate the Parallel Python module to implement Python code Execute parallel solutions on simple problems Achieve communication between processes using Pipe and Queue Use Celery Distributed Task Queue Implement asynchronous I/O using the Python asyncio module Create threadsafe structures Who this book is for

Table of Contents:
Table of Contents

  1. Contextualizing Parallel, Concurrent and Distributed Programming
  2. Identifying if a problem can be parallelizable
  3. Using Threading Module
  4. Using Multiprocessing Module
  5. Using Python Parallel Module
  6. Distributing tasks with Celery
  7. Making Things Asynchronously
  8. Building your own thread-safe structures


About the Author :
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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Product Details
  • ISBN-13: 9781783288403
  • Publisher: Packt Publishing Limited
  • Publisher Imprint: Packt Publishing Limited
  • Language: English
  • Sub Title: Develop efficient parallel systems using the robust Python environment.
  • ISBN-10: 178328840X
  • Publisher Date: 25 Jun 2014
  • Binding: Digital (delivered electronically)
  • No of Pages: 124


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Parallel Programming with Python: Develop efficient parallel systems using the robust Python environment.
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Parallel Programming with Python: Develop efficient parallel systems using the robust Python environment.
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