Key Features

• Most updated book on Interactive computing with IPython 4.0;
• Detailed, example-rich guide that lets you use the most advanced level interactive programming with IPython;
• Get flexible interactive programming with IPython using this comprehensive guide

Book Description

IPython is an interactive computational environment in which you can combine code execution, rich text, mathematics, plots, and rich media.

This book will get IPython developers up to date with the latest advancements in IPython and dive deep into interactive computing with IPython. This an advanced guide on interactive and parallel computing with IPython will explore advanced visualizations and high-performance computing with IPython in detail.

You will quickly brush up your knowledge of IPython kernels and wrapper kernels, then we'll move to advanced concepts such as testing, Sphinx, JS events, interactive work, and the ZMQ cluster. The book will cover topics such as IPython Console Lexer, advanced configuration, and third-party tools.

By the end of this book, you will be able to use IPython for interactive and parallel computing in a high-performance computing environment.

What you will learn

• Develop skills to use IPython for high performance computing (HPC)
• Understand the IPython interactive shell
• Use XeroMQ and MPI to pass messages
• Integrate third-party tools like R, Julia, and JavaScript with IPython
• Visualize the data
• Acquire knowledge to test and document the data
• Get to grips with the recent developments in the Jupyter notebook system

About the Author

Thomas Bitterman has a PhD from Louisiana State University and is currently an assistant professor at Wittenberg University. He previously worked in the industry for many years, including a recent stint at the Ohio Supercomputer Center. Thomas has experience in such diverse areas as electronic commerce, enterprise messaging, wireless networking, supercomputing, and academia. He also likes to keep sharp, writing material for Packt Publishing and O'Reilly in his copious free time.

Table of Contents

1. Using IPython for HPC
2. Advanced Shell Topics
3. Stepping Up to IPython for Parallel Computing
4. Messaging with ZeroMQ and MPI
5. Opening the Toolkit – The IPython API
6. Works Well with Others – IPython and Third-Party Tools
7. Seeing Is Believing– Visualization
8. But It Worked in the Demo! – Testing
9. Documentation
10. Visiting Jupyter
11. Into the Future