Parallel Programming with Python: Develop Efficient Parallel Systems Using the Robust Python Environment (Paperback or Softback)

Palach, Jan

ISBN 10: 1783288396 / ISBN 13: 9781783288397

Edité par Packt Publishing 6/14/2014, 2014

A propos de cet article

Parallel Programming with Python: Develop Efficient Parallel Systems Using the Robust Python Environment 0.5. N° de réf. du vendeur BBS-9781783288397

Détails bibliographiques

Titre : Parallel Programming with Python: Develop ...

Éditeur : Packt Publishing 6/14/2014

Date d'édition : 2014

Reliure : Paperback or Softback

Etat : New

Type de livre : Book

A propos de ce titre

Présentation de l'éditeur:

Develop efficient parallel systems using the robust Python environment

About This Book

• Demonstrates the concepts of Python parallel programming
• Boosts your Python computing capabilities
• Contains easy-to-understand explanations and plenty of examples

Who This Book Is For

If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.

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 thread-safe structures

In Detail

Starting 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.