

Project Jupyter: jupyter.org

Min RK: @minrk

Matthias Bussonnier: @mbussonn

Complexity graph:

grokcode.com/864/snakefooding-python-code-for-complexity-visualization

Jess Hamrick deployment:

developer.rackspace.com/blog/deploying-jupyterhub-for-education

My Binder: mybinder.org

Try Jupyter: try.jupyter.org

Lorena Barba's AeroPython course: github.com/barbagroup/AeroPython

Jessica Hamrick's Ansible scripts: github.com/compmodels/jupyterhub-deploy

Jake Vanderplas blogging with notebooks: jakevdp.github.io

Peter Norvig's regex golf notebook:

nbviewer.jupyter.org/url/norvig.com/ipython/xkcd1313.ipynb

SageMathCloud: cloud.sagemath.com

First version of IPython: gist.github.com/fperez/1579699

Historical perspective:

blog.fperez.org/2012/01/ipython-notebook-historical.html



One of the fastest growing areas in Python is scientific computing. In scientific computing with Python, there are a few key packages that make it special. These include NumPy / SciPy / and related packages. The one that brings it all together, visually, is IPython (now known as Project Jupyter). That's the topic on episode 44 of Talk Python To Me.You'll learn about "the big split", the plans for the recent $6 million in funding, Jupyter at CERN and the LHC and more with Min RK & Matthias Bussonnier.Links from the show: