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

Handling coroutines with asyncio

Throughout the various examples presented, we have seen that when a program becomes very long and complex, it is convenient to divide it into subroutines, each of which implements a specific task. However, subroutines cannot be executed independently, but only at the request of the main program, which is responsible for coordinating the use of subroutines.

In this section, we introduce a generalization of the concept of subroutines, known as coroutines: just like subroutines, coroutines compute a single computational step, but unlike subroutines, there is no main program to coordinate the results. The coroutines link themselves together to form a pipeline without any supervising function responsible for calling them in a particular order. 

In a coroutine, the execution point can be suspended and resumed later, since the coroutine keeps track...