Some example use cases in media production and pipelines
Beyond Interactive: Notebook Innovation at Netflix
https://netflixtechblog.com/notebook-innovation-591ee3221233
Snippet - “To understand why the Jupyter notebook is so compelling for us, consider the core functionality it provides:
a messaging protocol for introspecting and executing code which is language agnostic
an editable file format for describing and capturing code, code output, and markdown notes
a web-based UI for interactively writing and running code as well as visualizing outputs”
Integrate Jupyter Notebook into Data Pipelines - How to schedule and automate Jupyter using Papermill.
https://towardsdatascience.com/integrate-jupyter-into-your-data-pipeline-9a02fab3cee5
Snippet - “The biggest treasure for me is learning that Jupyter with nteract and papermill plugged in allow developers to parameterize, execute (even concurrently) and analyze your notebooks,
and it can further be scheduled by simply adding some Cron strings (or using any event consuming tool)!”
Powering Documentation with Jupyter Notebooks
https://medium.com/imandra/powering-documentation-with-jupyter-notebooks-eb3c7ae10069
Snippet - “This post is a quick rundown of why we decided to produce our documentation, the journey of getting there, and the various pieces involved.”
(Note: uses Imandra, a powerful reasoning engine backed by Jupyter notebooks)
USD Camera - As we all know, there is an Stage camera but having a tangible, functional Camera that we can structure and share has real meaning and value for productions. In this diagram, there is a working camera that is one abstract layer above the various camera roles that are then references to the base USD Camera. Departmental cameras may be overloaded, etc.. with specific discipline-focused attributes.
Ex. 1
Ex. 2
