Monitor errors and performance issues with

Project Jupyter and IPython

Episode #44, published Tue, Feb 2, 2016, recorded Tue, Jan 26, 2016.

This episode is carbon neutral.
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:
Min RK: @minrk
Matthias Bussonnier: @mbussonn
Complexity graph:
Jess Hamrick deployment:
My Binder:
Try Jupyter:
Lorena Barba's AeroPython course:
Jessica Hamrick's Ansible scripts:
Jake Vanderplas blogging with notebooks:
Peter Norvig's regex golf notebook:
First version of IPython:
Historical perspective:

Want to go deeper? Check out our courses

Min and Matthias
Min and Matthias
Episode sponsored by
Ads served ethically
Become a friend of the show
Stay in the know and get a chance to win our contests.
See our privacy statement about email communications.