You're reading from Learning Concurrency in Python Build highly efficient, robust, and concurrent applications

Product type Paperback

Published in Aug 2017

Publisher Packt

ISBN-13 9781787285378

Length 360 pages

Edition 1st Edition

Languages

Python

Concepts

Concurrency

Author (1):

Elliot Forbes

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Table of Contents (13) Chapters

Preface

1. Speed It Up! FREE CHAPTER

2. Parallelize It

3. Life of a Thread

4. Synchronization between Threads

5. Communication between Threads

6. Debug and Benchmark

7. Executors and Pools

8. Multiprocessing

9. Event-Driven Programming

10. Reactive Programming

11. Using the GPU

12. Choosing a Solution

Theano

If you are interested in niche topics such as deep learning and machine learning, then it's very probable that you may have considered using Theano. Theano is a Python library that is ideal for working with multi-dimensional arrays such as NumPy’s ndarrays, and it’s exceptionally performant when it comes to doing so. Theano relies on the GPU in order to provide performance that can surpass C on a typical CPU many times over.

Requirements

Theano is available for those of us on either Python 2.7 or on a version of Python greater than 3.3 but less than version 3.6. You'll also need to install NumPy and SciPy. For a fuller list of requirements, I recommend you check out the official requirements...

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Authors (1)

Forbes

Elliot Forbes has worked as a full-time software engineer at a leading financial firm for the last two years. He graduated from the University of Strathclyde in Scotland in the spring of 2015 and worked as a freelancer developing web solutions while studying there. He has worked on numerous different technologies such as Golang, Node.js, and plain old Java, and he has spent years working on concurrent enterprise systems.Elliot has even worked at Barclays Investment Bank for a summer internship in London and has maintained a couple of software development websites for the last three years.

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