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
Dedication

Manipulating tasks with asyncio

The asyncio module is designed to handle asynchronous processes and concurrent task execution over an event loop. It also provides the asyncio.Task() class for the purpose of wrapping coroutines in a task (https://docs.python.org/3/library/asyncio-task.html). Its use is to allow independently running tasks to run concurrently with other tasks over the same event loop.

When a coroutine is wrapped in a task, it connects Task to the event loop and then runs automatically when the loop is started, thus providing a mechanism for automatically driving the coroutine.

The asyncio module provides the asyncio.Task(coroutine) method to handle computations with tasks; moreover, asyncio.Task(coroutine) schedules the execution of a coroutine (https://docs.python.org/3/library/asyncio-task.html).

A task is responsible for executing a coroutine...