Project Jupyter, evolved from the IPython environment, provides a platform for interactive computing that is widely used today in research, education, journalism and industry. The core premise of the Jupyter architecture is to design tools around the experience of interactive computing, building an environment, protocol, file format and libraries optimized for the computational process when there is a human in the loop, in a live iteration with ideas and data assisted by the computer.
In this talk, I will discuss what are the basic ideas that underpin Jupyter, and how they provide "lego blocks" that enable the project team, and the broader community, to develop a variety of tools and approaches to problems in interactive computing, data science, visualization and more.
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PLOTCON NYC: The Architecture of Jupyter: Protocols for Interactive Data Exploration and Visualization Across Languages
1. Fernando Pérez
(@fperez_org & fperez@lbl.gov)
LBL & UC Berkeley
interactive data
exploration and
visualization across
languages
The Architecture of
Jupyter
4. Every research discipline is now awash in data
Physics: LHC
Sociology: The Web
Biology: Sequencing
Economics: POS
terminals
Neuroscience: EEG, fMRI
Astronomy: LSST
Personalized, data-driven
medicine
19. Jupyter Kernel Gateway
❖ Web server for spawning and communicating with
kernels over HTTP/Websocket
❖ Defaults to letting web clients talk the Jupyter protocol
❖ Extensible with other modes / personalities
Slides/credit: Peter Parente, @parente
22. Notebooks as dashboards
❖ Same file format
❖ Metadata based
❖ Live dashboard with
Jupyter kernel
❖ Web view with hidden
details (code, setup,
etc)
https://github.com/jupyter-incubator/dashboards
29. Berkeley’s Foundations of Data Science
❖ New curriculum aimed at all
freshmen at UC Berkeley
❖ Interactive textbook is
Jupyter Notebooks
❖ Course deployment is
JupyterHub
❖ Off Jess Hamrick’s work
data.berkeley.edu, data8.org