IPython provides tools for interactive and parallel computing that are widely used in scientific computing. We will show some uses of IPython for scientific applications, focusing on exciting recent developments, web-based notebook with code, graphics, and rich HTML.
This tutorial will be based on IPython in depth tutorial but will not introduced advance notion of IPython parallel.
Hopefully IPython 1.0 should have been released when this tutorial will be given, we will partly focus on new feature incuded since previous stable release which was almost a year old. The road from 0.13.x to 1.0 should have seen the integration of nbconvert into IPython core as well as some way to customise and write extension for the notebook.
In this advance tutorial we will mostly focus on the notebook format and capability of the IPython web notebook.
We will digg a little deeper into the stucture of ipynb files and see how this is relevant when using the display protocol and how to fully use it's power when writing python code. As the document format also support arbitrary metadata, we will look at how this could be use to customise the behavior of the notebook and the conversion process to different format.
It would be greate if you could come with some copy[*] of your own notebook to play with.
Tutorial material will most probably be hosted here :
With an EuroSciPy2013 Tag,
We remind to reader that static view of notebook can be seen without having to install IPython on http://nbviewer.ipython.org
Extra Requirement / Recommended:
view JS documentation locally :
Developper tool for your browser
Full LaTeX stack if ou are interested by ipynb > tex > pdf conversion.
[*] we don't want you to loose data, so please make a backup ;-)