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
About the Author
About the Reviewers

How to create a task with Celery

In this recipe, we'll show you how to create and call a task using the Celery module. Celery provides the following methods that make a call to a task:

  • apply_async(args[, kwargs[, …]]): This task sends a task message

  • delay(*args, **kwargs): This is a shortcut to send a task message, but does not support execution options

The delay method is better to use because it can be called as a regular function:

task.delay(arg1, arg2, kwarg1='x', kwarg2='y')

While using apply_async you should write:

task.apply_async (args=[arg1, arg2] kwargs={'kwarg1': 'x','kwarg2': 'y'})

How to do it…

To perform this simple task, we implement the following two simple scripts:

## :Executing a simple task

from celery import Celery

app = Celery('addTask',broker='amqp://guest@localhost//')

def add(x, y):
    return x + y
while the second script is :

### : RUN the AddTask example with 

import addTask

if __name__ == '__main__':
    result = addTask...