Book Image

Learning Concurrency in Python

By : Elliot Forbes
Book Image

Learning Concurrency in Python

By: Elliot Forbes

Overview of this book

Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

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 documentation, which can be found at http://deeplearning.net/software/theano/requirements.html.

Getting started

Theano is incredibly easy to get started with, and it was a pleasure learning it for the purpose of this chapter. The official documentation for the library is surprisingly good and features...