IPython in depth tutorial

Try it out on Binder!

In its current form, this tutorial is meant to be executed with Jupyter notebook 5.0, using IPython 6.0 or newer on Python 3, the latest IPython version compatible with Python 2 is IPython 5.x that may not have the exact same behavior and all the features presented in this tutorial.

You can find our installation instructions for IPython and Jupyter notebook

To get the tutorial, checkout the ipython-in-depth repo:

git clone https://github.com/ipython/ipython-in-depth

Or download current master and unzip it.

At the command line, you can do this with (depending on whether your system uses wget or curl):

wget https://github.com/ipython/ipython-in-depth/zipball/master -O ipython-in-depth.zip

or

curl -L https://github.com/ipython/ipython-in-depth/zipball/master -o ipython-in-depth.zip

And then:

unzip ipython-in-depth.zip

Change directory inside the directory newly created:

cd ipython-in-depth

You can then start the Jupyter notebook server at a terminal with:

jupyter notebook

Docker images

The tutorial do reference a couple of docker images that are quite heavy (several GB). Please do not download them on conference wifi. You may want to populate the Docker Cache you may want to use the following command ahead of time:

$ docker pull jupyter/datascience-notebook

The image contains a installation of the Jupyter notebook with R, Julia, Python2, Python3 and a couple of libraries for each language.