Brought to you by NumFOCUS Foundation and O’Reilly Media
The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

Binder: Lowering the bar to sharing interactive software

Tim Head (Wild Tree Tech)
5:00pm–5:40pm Thursday, August 23, 2018
Community, JupyterHub deployments, Reproducible research and open science
 Location: Nassau Level: Beginner
Average rating: ****.
(4.33, 3 ratings)

Who is this presentation for?

  • Data scientists, CTOs, researchers, educators, trainers, and journalists

Prerequisite knowledge

  • A basic understanding of Git repositories, dependencies (and at least one dependency specification format), development environments, and containers

What you'll learn

  • Learn what Binder is and the technology stack behind it, how to create Binder-ready repositories, and how to become part of the Binder community

Description

The Binder project drastically lowers the bar to sharing and reusing software. Users wanting to try out someone else’s work need only click a single link to do so. In addition, preparing a Binder-ready project is much easier than having to support many different platforms and for many projects involves little additional work.

Tim Head offers an overview of the Binder project and explores the concepts and ideas behind it. Tim then showcases examples from the community to show off the power of Binder. Three pieces of software power Binder: repo2docker, BinderHub, and JupyterHub. Using an example repository, Tim walks you through the steps required to make a repository Binder-ready and details what happens when a user launches it. At each step, you’ll learn the role that each of the three software components play and how they interact. And since Binder is a project created by its community, Tim shares pathways for getting involved with the community and highlights plans for future developments and features of Binder.

Photo of Tim Head

Tim Head

Wild Tree Tech

Tim Head is CEO of Wild Tree Tech, a freelance consultancy specializing in building full stack data science solutions and teaching artificial intelligence skills. Customers include a large international organization based in Geneva, startups, NGOs, open source projects, and research groups. Tim is a mentor for Mozilla’s Open Leadership program. He is a known good actor in the Python data ecosystem and has contributed to the development of Project Jupyter and other PyData projects for several years. He has extensive experience using and developing Python and C++ for data science applications, is one of the maintainers of scikit-optimize, a Python library for blackbox optimization, and has contributed to scikit-learn. Tim has given many talks at small and large international conferences like PyCon and EuroSciPy and co-organizes the PyData meetup in Zurich. He holds a PhD in experimental particle physics from the University of Manchester.