This curriculum page tracks work on notebooks for coursework at UW; emphasis on Jupyter notebooks and Python. Desired features:
- students authenticate to their copy of the Notebook via their usual campus login
- students have a read/clone view of the instructor(s) Master notebook
- student work is easily shared with and reviewed by the instructor(s)
- data files persist in all cases, even if the notebook is shut down
- the notebook is running an engine that executes code (not just a static view of already-executed material)
- instructor has simple administrative interface to the Master and granting students access
- Master is under source control; can be modified directly or via pull request
- Notebook supports markdown, LaTeX, animation, checkpoint/rollback, other ‘nice’ features
- Notebook has a How To pre-installed with…
- curl, !shell execution and other common tasks by example
- file access: open / read / write also by example
- administrative tasks for the host system and notebook e.g. % sudo yum update
- data access to non-local resources: Cloud storage, API calls etc by example
- As always: Key files that arrive in GitHub repos are still available after deletion via versioning. Don’t do it!
- Our glossary may help with unfamiliar terms.
- Search cloudmaven for ‘tunneling’ for more on connecting to notebooks through security barriers.
- Jupyter themes
- An example Jupyter notebook hosted on Azure
The following is a discussion between Professors A, B, M, and R together with a program manager apparently named Kilroy.
Prof A: Are we doing anything to manage Jupyter notebooks for coursework at the university? I would like to be able to set homework and projects up for the students together with associated data. Students log in using their University ID and go from there, writing and executing test code in a matter of minutes. I can see their work so that work must persist after the students log off; and this implies the organizing structure is around the course, not the students. JupyterLab has some of this already built in as a starting point.
Kilroy: Awesome, let’s do it. Before other faculty chime: Microsoft Azure is hosting Jupyter notebooks as a free service. The features are evolving but the notebook content does persist (in Master or Clone versions) with ownership via Windows LiveID. This is awesome. Data files may need re-loading via curl; and data volume is limited. Management for a large class could get tricky; this isn’t a slam dunk yet. A bonus: The Azure stack is more accessible by proximity. We could also create a dedicated cloud-based Notebook service: inexpensive for a single class provided not a lot of horsepower is needed. We can enlist University IT to help build this in a robust way from a POC. NetID authentication is already done.
Prof B: Would GitHub work for this? Perhaps there are FERPA compliance issues; but the good thing is that version control is already in place. (Here is a link.)
Prof M: We use GitLab, a locally-installed version of GitHub. This gives us unlimited private repositories, i.e. one repo per student x course. They pull content from an upstream repo that the instructors populate; and they submit assignments by push.
Prof R: A valuable aspect of the Azure notebook server or Binder is that students run the notebooks without having to install the Jupyter software stack (Python etcetera) on their own machine, not to mention dependencies and things break. GitHub / GitLab (my understanding) is static-only so that goes against the interactivity of student contribution. We’re running into these issues in the process of writing a book; so we’d really support running a server.
Prof B: Agreed. Pre-rendered (static) notebooks match well to GitHub; but having the full-blown server working provides the feature set we want at the cost of more effort.
Prof R: Another idea is to use a machine image such as a Docker file. Students spin this up quickly on a VM, do their work and save the revised image; which could be viewed by the instructor for evaluation. Also a bit tangential here are some related references:
- Pacific Inst of Math Sciences: Jupyter server
- This may prove to be available only to PIMS researchers, not for general audiences
- NERSC supercomputer notebook interface
- TACC supercomputer notebook hosting
- SDSC supercomputer notebook repo
== Berkeley work on Jupyter + Kubernetes ==
The BIDS Jupyter teams at UC Berkeley have been working with our colleague AC on a JupyterHub+Kubernetes deployment for Data Science Undergraduate education; with adaptation as well for faculty/grad/postdoc workshops and for research use cases.
- Zero to JupyterHub with Kubernetes Docs
- Zero to JupyterHub with Kubernetes GitHub
- More GitHub on the same
- Still more
This extends work from January 2017 on a workshop that involved AR (UW); cf the PEARC17 contribution
RV notes: Berkeley has picked up binder. No automatic badges etc yet but repo pointer syntax looks like this: https://beta.mybinder.org/v2/gh/clawpack/riemann_book/master