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Episode #44: Project Jupyter and IPython

Published Tues, Feb 2, 2016, recorded Tues, Jan 26, 2016.


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:

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



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