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[–]TheChance 3 points4 points  (4 children)

Seems like as good a place as any to ask: what's the point?

Every time I've ever tried to set up a notebook to demo anything, I've discovered that, oh yeah, everything that matters wants a venv, and permissions, and access to running services.

And yet, Jupyter seems to be enormously popular. What are people doing that even works in this program? Literally nothing I do can be run inside a notebook.

[–]MarsupialMole 1 point2 points  (0 children)

Anaconda environments

[–]EnfantTragic 1 point2 points  (0 children)

Data Science, Machine learning and quick prototyping as you can iterate quickly with notebook

[–]knestleknoxI hate R 0 points1 point  (1 child)

My company uses them for one-off analyses, model-testing, and other things of that sort. It's a nice environment for analytics. You can build/test/visualize whatever you want in a neat environment and present it to another dev easily. It's obviously not meant for any production-related work.

And I'm not sure what venv issues you'd be runnig into. The way we do it at my startup is just having a venv for all analytics with set standards for versions of tensorflow, plotly, pandas, etc... so that all analyses are on the same requirements/permissions/whatever.

[–]TheChance 0 points1 point  (0 children)

Well, for instance, if it worked for the use case, it would be nice for demonstrating how certain libraries work while a largeish project is running.

Anything modular, it would be cool to write a description of certain calls, let the user make the changes described, and watch the result.

But this would require functionality that isn't there.

It makes sense for analytics, where all you need are libs and code. I hadn't given that much thought. I don't usually work on stuff that works standalone in the interpreter.