I keep experimenting with Jupyter in the context of telemetry/fault analysis and then hitting a wall with it where:
- I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots.
- There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook.
- The process to "promote" fragments of a notebook into being reusable functions seemed very high-friction: basically you're rewriting it as a normal Python package and then adding that to Jupyter's environment.
- There aren't good boundaries between Jupyter's own Python environment, and that of your notebooks— if you have a dependency which conflicts with one of Jupyter's dependencies, then good luck.
Some or all of these may be wrong or out of date— Jupyter definitely passes the "oooh nifty" smell test, and I'd love to figure out how to make it usable for these longer-term workflows rather than just banging out one-off toys.
- I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots.
- There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook.
- The process to "promote" fragments of a notebook into being reusable functions seemed very high-friction: basically you're rewriting it as a normal Python package and then adding that to Jupyter's environment.
- There aren't good boundaries between Jupyter's own Python environment, and that of your notebooks— if you have a dependency which conflicts with one of Jupyter's dependencies, then good luck.
Some or all of these may be wrong or out of date— Jupyter definitely passes the "oooh nifty" smell test, and I'd love to figure out how to make it usable for these longer-term workflows rather than just banging out one-off toys.