Tweet
Tweet

Slide 1

Slide 1 text

Fernando Pérez (@fperez_org) UC Berkeley & LBNL Project Jupyter: From interactive Python to Open Science

Slide 2

Slide 2 text

Why? Open Source in Science?

Slide 3

Slide 3 text

Technical: better tools

Slide 4

Slide 4 text

2001: physics grad student

Slide 5

Slide 5 text

Python FTW!

Slide 6

Slide 6 text

Thanks to a blog post by D. Beazley about sys.displayhook in Python 2 Interactivity: Humans in the loop!

Slide 7

Slide 7 text

Nathan Gray: Lazy Python/deep_reload Janko Hauser: Interactive Python Prompt (IPP) Others were thinking about the same…

Slide 8

Slide 8 text

Dec 10, 2001, on comp.lang.python From the get-go, a collaborative effort!

Slide 9

Slide 9 text

Ethical: access & collaboration

Slide 10

Slide 10 text

Medellín, Colombia Image Credits: latinorebels.com wired.com

Slide 11

Slide 11 text

IPython sprint @ SciPy India 2010 Prabhu Ramachandran, IIT Mumbai, Enthought

Slide 12

Slide 12 text

What I can not create, I do not understand Richard Feynman Scientific: black boxes don’t belong in science

Slide 13

Slide 13 text

Most important in the long run: Community!

Slide 14

Slide 14 text

SciPy 2003 @ CalTech Eric Jones John Hunter, 1968-2012 SciPy: Scientists collaborating across disciplinary boundaries for the fun of building better tools, rather than competing for papers.

Slide 15

Slide 15 text

IPython: life-long partnerships SciPy 2008, Caltech PyCon 2012, Santa Clara

Slide 16

Slide 16 text

Team today: where all the credit goes And over 500 contributors!

Slide 17

Slide 17 text

Brett Cannon said it best

Slide 18

Slide 18 text

What: Human-centered, interactive, computing and science

Slide 19

Slide 19 text

At the terminal or the notebook

Slide 20

Slide 20 text

Jupyter: beyond Python u a l j i ~90 different kernels: https://github.com/jupyter/jupyter/wiki/Jupyter-kernels

Slide 21

Slide 21 text

What do we build? ❖ Low-level standards: ❖ Messaging protocol, notebook format ❖ Reusable libraries that implement them ❖ User-facing applications ❖ IPython, Jupyter Notebook/Lab, JupyterHub, … ❖ Services that make them accessible ❖ nbviewer, try.jupyter All in support of an open ecosystem

Slide 22

Slide 22 text

protocol and format ❖ Core foundations ❖ Capture lasting, important elements of human-centered computational processes ❖ But meant for machines to digest well! ❖ Archival, reusable, multi-purpose 100% open: work with us, don’t reinvent at this level!!

Slide 23

Slide 23 text

Where next

Slide 24

Slide 24 text

Exciting developments … lots more! JupyterLab nbdime

Slide 25

Slide 25 text

Executable books

Slide 26

Slide 26 text

Berkeley’s Foundations of Data Science ❖ Interactive textbook is Jupyter Notebooks ❖ Course deployment is JupyterHub ❖ Based on original effort by Jess Hamrick (2017 PhD) ❖ Ryan Lovett, Yuvi Panda, Vinitra Swamy, Gunjan Baid, Chris Hench, Claudia von Vacano… data.berkeley.edu, data8.org inferentialthinking.com

Slide 27

Slide 27 text

Fastest growth in Berkeley history We estimate ~1200 students this semester. First class was yesterday!

Slide 28

Slide 28 text

How do we keep doing this?

Slide 29

Slide 29 text

A sustainable future for Jupyter & friends? When [platforms] try to extract too much value for the platform owner, they ultimately fail… Platforms must create more value than they capture if their ecosystem is to survive. Tim O’Reilly - WTF? What’s the Future and Why It’s Up To Us

Slide 30

Slide 30 text

Industry platforms

Slide 31

Slide 31 text

NumFOCUS.org

Slide 32

Slide 32 text

Funding and partnerships

Slide 33

Slide 33 text

A personal note ❖ IPython was born out of deep, hard failure ❖ The SciPy community saved me! ❖ Impostor syndrome is still very real ❖ Scientist, doing software, crossing disciplinary boundaries…

Slide 34

Slide 34 text

I trust this community to continue to be as welcoming and open as it can be innovative. Let’s keep building tools that contribute to an open, collaborative, accessible and fair society. 2018!

Slide 35

Slide 35 text

Thank You!