Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Sign In Start Free Trial

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Mastering IPython 4.0
  • Table Of Contents Toc
Mastering IPython 4.0

Mastering IPython 4.0

By : Thomas Bitterman, Dipanjan Deb
3 (3)
Buy this Book
close
close
Mastering IPython 4.0

Mastering IPython 4.0

3 (3)
By: Thomas Bitterman, Dipanjan Deb
Buy this Book

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)
close
close
close
Preface
Icon
Preface
Icon
What this book covers
Icon
What you need for this book
Icon
Who this book is for
Icon
Conventions
Icon
Reader feedback
Icon
Customer support
Lock Free Chapter
1
1. Using IPython for HPC
Icon
1. Using IPython for HPC
Icon
The need for speed
Icon
FORTRAN to the rescue – the problems FORTRAN addressed
Icon
Choosing between IPython and Fortran
Icon
An example case – Fast Fourier Transform
Icon
High Performance Computing
Icon
Going parallel
Icon
Summary
2
2. Advanced Shell Topics
Icon
2. Advanced Shell Topics
Icon
What is IPython?
Icon
Installing IPython
Icon
All-in-one distributions
Icon
What happened to the Notebook?
Icon
Starting out with the terminal
Icon
IPython beyond Python
Icon
Magic commands
Icon
Cython
Icon
Configuring IPython
Icon
Debugging
Icon
Read-Eval-Print Loop (REPL) and IPython architecture
Icon
Alternative development environments
Icon
Summary
3
3. Stepping Up to IPython for Parallel Computing
chevron up
Icon
3. Stepping Up to IPython for Parallel Computing
Icon
Serial processes
Icon
Threading
Icon
Using multiple processors
Icon
The IPython parallel architecture
Icon
Getting started with ipyparallel
Icon
Parallel magic commands
Icon
Types of parallelism
Icon
Data parallelism
Icon
Application steering
Icon
Summary
4
4. Messaging with ZeroMQ and MPI
Icon
4. Messaging with ZeroMQ and MPI
Icon
The storage hierarchy
Icon
ZeroMQ
Icon
MPI
Icon
ZeroMQ and IPython
Icon
Summary
5
5. Opening the Toolkit – The IPython API
Icon
5. Opening the Toolkit – The IPython API
Icon
Performance profiling
Icon
The AsyncResult class
Icon
The Client class
Icon
The View class
Icon
Summary
6
6. Works Well with Others – IPython and Third-Party Tools
Icon
6. Works Well with Others – IPython and Third-Party Tools
Icon
R
Icon
Octave
Icon
Hy
Icon
Summary
7
7. Seeing Is Believing– Visualization
Icon
7. Seeing Is Believing– Visualization
Icon
Matplotlib
Icon
Bokeh
Icon
R
Icon
Python-nvd3
Icon
Summary
8
8. But It Worked in the Demo! – Testing
Icon
8. But It Worked in the Demo! – Testing
Icon
Unit testing
Icon
unittest
Icon
pytest
Icon
nose2
Icon
Summary
9
9. Documentation
Icon
9. Documentation
Icon
Inline comments
Icon
Docstrings
Icon
reStructuredText
Icon
Docutils
Icon
Sphinx
Icon
Summary
10
10. Visiting Jupyter
Icon
10. Visiting Jupyter
Icon
Installation and startup
Icon
The Dashboard
Icon
Creating a notebook
Icon
Interacting with Python scripts
Icon
Working with cells
Icon
Being graphic
Icon
Format conversion
Icon
Summary
11
11. Into the Future
Icon
11. Into the Future
Icon
Some history
Icon
The Jupyter project
Icon
IPython
Icon
The rise of parallelism
Icon
Growing professionalism
Icon
Summary
12
Index
Icon
Index

Getting started with ipyparallel

We will start with a simple parallel "Hello world" program using ipcluster.

ipcluster

To use IPython for parallel computing, you will need a controller and one or more engines. The easiest way to get them is to start them on your localhost using the ipcluster command:

ipcluster start –n 4

It will start a controller and four engines.

This can be somewhat fraught with subtle errors, however, as the engines do not necessarily have the same environment as the command line that started them. You may have more luck starting the entire thing from inside an IPython session, using the ! escape for system commands, shown as follows:

In [5]: !ipcluster start -n 4 &
In [6]: 2015-10-26 15:52:53.738 [IPClusterStart] Using existing profile dir: '/nfs/02/wit0096/.ipython/profile_default'
2015-10-26 15:52:53.828 [IPClusterStart] Removing pid file: /nfs/02/wit0096/.ipython/profile_default/pid/ipcluster.pid
2015-10-26 15:52:53.828 [IPClusterStart] Starting ipcluster with ...
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Mastering IPython 4.0
End of Section 3
Next Section
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options
font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected
Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful
Order Page Read Now

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon