Book Image

Python Parallel Programming Cookbook

By : Giancarlo Zaccone
Book Image

Python Parallel Programming Cookbook

By: Giancarlo Zaccone

Overview of this book

This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will understand anche Pycsp, the Scoop framework, and disk modules in Python. Further on, you will learnGPU programming withPython using the PyCUDA module along with evaluating performance limitations.
Table of Contents (13 chapters)
Python Parallel Programming Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Task manipulation with Asyncio


Asyncio is designed to handle asynchronous processes and concurrent task executions on an event loop. It also provides us with the asyncio.Task() class for the purpose of wrapping coroutines in a task. Its use is to allow independently running tasks to run concurrently with other tasks on the same event loop. When a coroutine is wrapped in a task, it connects the task to the event loop and then runs automatically when the loop is started, thus providing a mechanism to automatically drive the coroutine.

Getting ready

The Asyncio module provides us with the asyncio.Task(coroutine) method to handle computations with tasks. It schedules the execution of a coroutine. A task is responsible for the execution of a coroutine object in an event loop. If the wrapped coroutine yields from a future, the task suspends the execution of the wrapped coroutine and waits for the completion of the future.

When the future is complete, the execution of the wrapped coroutine restarts...