Book Image

Python Parallel Programming Cookbook - Second Edition

By : Giancarlo Zaccone
Book Image

Python Parallel Programming Cookbook - Second Edition

By: Giancarlo Zaccone

Overview of this book

<p>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. </p><p> </p><p>This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. </p><p> </p><p>By the end of this book, you will be confident in building concurrent and high-performing applications in Python.</p>
Table of Contents (16 chapters)
Title Page

Using the concurrent.futures Python module

The concurrent.futures module, which is part of the standard Python library, provides a level of abstraction on threads by modelling them as asynchronous functions.

This module is built by two main classes:

  • concurrent.futures.Executor: This is an abstract class that provides methods to execute calls asynchronously.
  • concurrent.futures.Future: This encapsulates the asynchronous execution of a callable. Future objects are instantiated by submitting tasks (functions with optional parameters) to Executors.

Here are some of the main methods of the module:

  • submit(function,argument): This schedules the execution of the callable function on the arguments.
  • map(function,argument): This executes the functions of arguments in asynchronous mode.
  • shutdown(Wait=True): This signals the executor to free any resource.

The executors are...