Book Image

Mastering IPython 4.0

By : Thomas Bitterman, Dipanjan Deb
Book Image

Mastering IPython 4.0

By: Thomas Bitterman, Dipanjan Deb

Overview of this book

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.
Table of Contents (18 chapters)
Mastering IPython 4.0
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
6
Works Well with Others – IPython and Third-Party Tools
Index

Summary


Whether the project calls for interactive visuals created at the command line for immediate consumption, or a more off-line approach where results are expressed as an image that can be viewed at leisure, there is a tool that fits the need.

The degree to which various tools are integrated with IPython varies: R uses Rmagics to enable a mode in which the developer is virtually running an R interpreter, while Plotly prefers using Python as much as possible. Development in this area is rapid, and it seems likely that there will be an even greater degree of interoperability between different tools in the future, whether supported by the tools themselves or by new frameworks designed for that purpose.

To a large extent, the choice of which tool to use should come down to the one that the developer finds the easiest to use. Many good options are free, and the use of IPython to generate data makes it relatively easy to switch from one tool to another without loss of data.

Although seeing is...