Mastering IPython 4.0

Get to grips with the advanced concepts of interactive computing to make the most out of IPython

Mastering IPython 4.0

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Thomas Bitterman

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Get to grips with the advanced concepts of interactive computing to make the most out of IPython
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Book Details

ISBN 139781785888410
Paperback382 pages

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.

Table of Contents

Chapter 1: Using IPython for HPC
The need for speed
FORTRAN to the rescue – the problems FORTRAN addressed
Choosing between IPython and Fortran
An example case – Fast Fourier Transform
High Performance Computing
Going parallel
Summary
Chapter 2: Advanced Shell Topics
What is IPython?
Installing IPython
All-in-one distributions
What happened to the Notebook?
Starting out with the terminal
IPython beyond Python
Magic commands
Cython
Configuring IPython
Debugging
Read-Eval-Print Loop (REPL) and IPython architecture
Alternative development environments
Summary
Chapter 3: Stepping Up to IPython for Parallel Computing
Serial processes
Threading
Using multiple processors
The IPython parallel architecture
Getting started with ipyparallel
Parallel magic commands
Types of parallelism
Data parallelism
Application steering
Summary
Chapter 4: Messaging with ZeroMQ and MPI
The storage hierarchy
ZeroMQ
MPI
ZeroMQ and IPython
Summary
Chapter 5: Opening the Toolkit – The IPython API
Performance profiling
The AsyncResult class
The Client class
The View class
Summary
Chapter 6: Works Well with Others – IPython and Third-Party Tools
R
Octave
Hy
Summary
Chapter 7: Seeing Is Believing– Visualization
Matplotlib
Bokeh
R
Python-nvd3
Summary
Chapter 8: But It Worked in the Demo! – Testing
Unit testing
unittest
pytest
nose2
Summary
Chapter 9: Documentation
Inline comments
Docstrings
reStructuredText
Docutils
Sphinx
Summary
Chapter 10: Visiting Jupyter
Installation and startup
The Dashboard
Creating a notebook
Interacting with Python scripts
Working with cells
Being graphic
Format conversion
Summary
Chapter 11: Into the Future
Some history
The Jupyter project
IPython
The rise of parallelism
Growing professionalism
Summary

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

Authors

Table of Contents

Chapter 1: Using IPython for HPC
The need for speed
FORTRAN to the rescue – the problems FORTRAN addressed
Choosing between IPython and Fortran
An example case – Fast Fourier Transform
High Performance Computing
Going parallel
Summary
Chapter 2: Advanced Shell Topics
What is IPython?
Installing IPython
All-in-one distributions
What happened to the Notebook?
Starting out with the terminal
IPython beyond Python
Magic commands
Cython
Configuring IPython
Debugging
Read-Eval-Print Loop (REPL) and IPython architecture
Alternative development environments
Summary
Chapter 3: Stepping Up to IPython for Parallel Computing
Serial processes
Threading
Using multiple processors
The IPython parallel architecture
Getting started with ipyparallel
Parallel magic commands
Types of parallelism
Data parallelism
Application steering
Summary
Chapter 4: Messaging with ZeroMQ and MPI
The storage hierarchy
ZeroMQ
MPI
ZeroMQ and IPython
Summary
Chapter 5: Opening the Toolkit – The IPython API
Performance profiling
The AsyncResult class
The Client class
The View class
Summary
Chapter 6: Works Well with Others – IPython and Third-Party Tools
R
Octave
Hy
Summary
Chapter 7: Seeing Is Believing– Visualization
Matplotlib
Bokeh
R
Python-nvd3
Summary
Chapter 8: But It Worked in the Demo! – Testing
Unit testing
unittest
pytest
nose2
Summary
Chapter 9: Documentation
Inline comments
Docstrings
reStructuredText
Docutils
Sphinx
Summary
Chapter 10: Visiting Jupyter
Installation and startup
The Dashboard
Creating a notebook
Interacting with Python scripts
Working with cells
Being graphic
Format conversion
Summary
Chapter 11: Into the Future
Some history
The Jupyter project
IPython
The rise of parallelism
Growing professionalism
Summary

Book Details

ISBN 139781785888410
Paperback382 pages
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