Book Image

Python Parallel Programming Cookbook

By : Zaccone
Book Image

Python Parallel Programming Cookbook

By: 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 (8 chapters)
7
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...