Jon Bannister - Notebooker: From research to production in a snap using Jupyter |JupyterCon 2020

Brief Summary
Jupyter Notebooks are awesome tools for research and development, but as soon as you're happy with the outcome the usual process is to throw a messy notebook to a developer and ask them to reproduce it but... not in Jupyter. In this talk, I will explain how we've managed to circumvent the re-implementation step and use the notebooks in production - and how you can do the same.

Outline
Background required: not much!

reviewability - how can I review the code?
templating - how can I re-use a notebook?
parametrization - how to execute the exact same notebook for e.g. 100 different stocks?
testablity - how can we be sure it works?
executable - how can we execute the notebook reliably i.e. on-demand or scheduled?
browseable - how can we view or search for results?
secured - how can we prevent unauthorised access to sensitive results?
usability - how can we make sure that non-technical users can deploy without getting stuck?
I'll go over each point and discuss a) the open source tooling available to address each and b) how I chose to address it in Notebooker. As part of this talk I will heavily mention some key elements, namely jupytext and papermill, which are the foundations upon which Notebooker was built.

In the talk I'm mostly hoping to share my experience as a developer who has had notebooks thrown in his direction for productionisation in the past and spread the knowledge of helpful libraries to attendees who may be facing the same issue. I'd also love to invite contributors who like the Notebooker project to join in.
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JupyterCon2020
JupyterCon 2020


JupyterCon2020
JupyterCon 2020


JupyterCon2020
JupyterCon 2020