Lightning Talks and Closing Address
summary
Video lists concrete tools and outcomes: a pip-installable envy-stripout that installs a git filter to strip notebook outputs (works to keep repos clean but breaks plain git diff), CI helpers as shell scripts that automate conda/travis matrices across dozens of repos, a claimed corpus of roughly 500 notebooks, experimental approaches to preserve outputs (a companion file, NV explode, nbdime), a Docker+DAG prototype that makes near‑real‑time recomputation efficient, and an rwatch module that hooks callbacks on object reads (demoable but can crash execution).
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chapters (19)
- 0:00Three-day data science journey
- 1:51Open source and Python 3
- 4:19Sponsors and volunteers
- 8:12Flower delivery logistics
- 9:58NumFOCUS backbone
- 11:20Volunteering opportunities
- 12:44Attendee feedback
- 14:35Lightning talks kickoff
- 15:19Managing Jupyter notebooks
- 20:30Astropy CI helpers
- 24:25London Kaggle meetup
- 27:41Jupyter notebooks in research
- 30:14Pen stroke analysis
- 36:04Storing notebooks in Git
- 36:49Bayesian statistics tribute
- 40:10Medium data real-time analysis
- 43:01Closing remarks
- 43:48Python read-watches
- 49:17Event wrap-up
