This is the code repository for Python Parallel Programming Cookbook - Second Edition , published by Packt.

Over 70 recipes to solve challenges in multithreading and distributed system with Python 3

Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable.

This book covers the following exciting features:

• Synchronize multiple threads and processes to manage parallel tasks
• Use message passing techniques to establish communication between processes to build parallel applications
• Program your own GPU cards to address complex problems
• Manage computing entities to execute distributed computational task
• Write efficient programs by adopting the event-driven programming model
• Explore cloud technology with Django and Google App Engine
• Apply parallel programming techniques that can lead to performance improvements

If you feel this book is for you, get your copy today!

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

class Pdb_test(object):
    def __init__(self, parameter):
    self.counter = parameter

Following is what you need for this book: The Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing.

With the following software and hardware list you can run all code files present in the book (Chapter 01-09).

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

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Giancarlo Zaccone Giancarlo Zaccone has over fifteen years' experience of managing research projects in the scientific and industrial domains. He is a software and systems engineer at the European Space Agency (ESTEC), where he mainly deals with the cybersecurity of satellite navigation systems.

Giancarlo holds a master's degree in physics and an advanced master's degree in scientific computing.

Giancarlo has already authored the following titles, available from Packt: Python Parallel Programming Cookbook (First Edition), Getting Started with TensorFlow, Deep Learning with TensorFlow (First Edition), and Deep Learning with TensorFlow (Second Edition).

Python Parallel Programming Cookbook

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