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  • Book Overview & Buying Mastering IPython 4.0
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Mastering IPython 4.0

Mastering IPython 4.0

By : Thomas Bitterman, Dipanjan Deb
3 (3)
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Mastering IPython 4.0

Mastering IPython 4.0

3 (3)
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 (13 chapters)
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6
6. Works Well with Others – IPython and Third-Party Tools
7
7. Seeing Is Believing– Visualization
12
Index

Summary


While inline comments and type notations are useful for developers who will be working on the code base, external parties need more extensive documentation, and need it in a more attractive format than reading the source (this is especially true when they do not have access to the source). This need for documentation must be balanced against the understandable reluctance of developers to spend a great deal of time and energy producing anything but code.

Python's solution is to employ a lightweight markup language, reStructuredText, and a toolchain (Docutils, Sphinx) to transform reStructuredText into a more aesthetically attractive format (for example, HTML or LaTeX).

Aesthetics are not everything, however. Documentation must contain useful information in order to be worth using. Various guidelines (PEP 0008, PEP 3107, PEP 0484, PEP 0257, Google, NumPyDoc, and others) have come into being to provide advice. A production project should settle for a set of guidelines before coding starts...

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Programming languages
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