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Python Parallel Programming Cookbook

You're reading from   Python Parallel Programming Cookbook Master efficient parallel programming to build powerful applications using Python

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Product type Paperback
Published in Aug 2015
Publisher
ISBN-13 9781785289583
Length 286 pages
Edition 1st Edition
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Author (1):
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Giancarlo Zaccone Giancarlo Zaccone
Author Profile Icon Giancarlo Zaccone
Giancarlo Zaccone
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Table of Contents (8) Chapters Close

Preface 1. Getting Started with Parallel Computing and Python 2. Thread-based Parallelism FREE CHAPTER 3. Process-based Parallelism 4. Asynchronous Programming 5. Distributed Python 6. GPU Programming with Python Index

Using the concurrent.futures Python modules


With the release of Python 3.2, the concurrent.future module was introduced, which allows us to manage concurrent programming tasks, such as process and thread pooling, nondeterministic execution flows, and processes and thread synchronization.

This package is built by the following classes:

  • concurrent.futures.Executor: This is an abstract class that provides methods to execute calls asynchronously.

  • submit (function ,argument): This schedules the execution of a function (called callable) on the arguments.

  • map (function,argument): This executes the function on arguments in an asynchronous mode.

  • shutdown (Wait = True): This signals the executor to free any resource.

  • concurrent.futures.Future: This encapsulates the asynchronous execution of a callable function. Future objects are instantiated by submitting tasks (functions with optional parameters) to executors.

Executors are abstractions that are accessed through their subclasses: thread or process...

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