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

The Jupyter project


This reorganization of code is reflected in the hierarchy of projects that produce it: IPython is now an official subproject of the Jupyter project. IPython is Kernel Zero, in some sense the reference kernel, but in the end just one kernel among many. There are still some sections of code that are shared between the projects and need to be separated, but this is a relatively simple technical issue.

Even after the codebases became completely separate, Jupyter will constrain the future of IPython due to requirements for continued compatibility. Although IPython can be used as an independent tool (as this book attempts to demonstrate), its role in the Jupyter project greatly increases its user base.

At first glance, this would seem impossible. The Jupyter project is large and contains more subprojects than could be comfortably listed here (see http://jupyter.readthedocs.org/en/latest/subprojects.html for a complete list), making any attempt at staying compatible a nightmare...