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The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

Jupyter: Kernels, protocols, and the IPython reference implementation

Matthias Bussonnier (UC Berkeley BIDS), Paul Ivanov (Bloomberg LP)
11:05am–11:45am Friday, August 25, 2017
Location: Beekman/Sutton North
Average rating: ****.
(4.00, 1 rating)

What you'll learn

  • Explore the current Jupyter architecture and protocol
  • Learn how kernels work


One of the foundations of Jupyter is a protocol that explicitly defines all the actions and results that comprise the workflow of interactive computing across a wide range of programming languages. This abstracts and decouples the process of code execution (performed by a kernel) from code input and results rendering. It allowed the many frontends to be developed independently but also permitted the quick addition of new kernels and languages. IPython, developed by the Jupyter team, is the canonical implementation of this protocol, providing a rich interactive experience in Python.

Matthias Bussonnier and Paul Ivanov walk you through the current Jupyter architecture and protocol and explain how kernels work (decoupled from but in communication with the environment for input and output, such as a notebook document). Matthias and Paul also offer an overview of a number of kernels developed by the community and show you how you can get started writing a new kernel.

Photo of Matthias Bussonnier

Matthias Bussonnier

UC Berkeley BIDS

Matthias Bussonnier is postdoc at UC Berkeley BIDS and a core developer of the Jupyter and IPython project, where he is working in close collaboration with Google to bring real-time collaboration to the Jupyter environment.

Photo of Paul Ivanov

Paul Ivanov

Bloomberg LP

Paul Ivanov is a member of the Jupyter Steering Council and a senior software engineer at Bloomberg LP working on IPython- and Jupyter-related open source projects. Previously, Paul worked on backend and data engineering at Disqus; was a code monkey at the Brain Imaging Center at UC Berkeley, where he worked on IPython and taught at UC Berkeley’s Python bootcamps; worked in Bruno Olshausen’s lab at the Redwood Center for Theoretical Neuroscience; and was a PhD candidate in the Vision Science program at UC Berkeley. He holds a degree in computer science from UC Davis.