[SiempreViernes]

You can get a jupyter extension[1] that allows you to add tags and dependencies and this way construct the dependency graph as you go along. Of course, you have to do it manually and the interface is a bit clunky, but it does what it says.

In practice I think taking care not to accidentally shadow variables is much more important: this dependency business only makes sense once you have a clear idea of what you need and by that point you are mostly done anyway.

[1] https://jupyter-contrib-nbextensions.readthedocs.io/en/lates...

[jacobolus]

I don’t understand what you are trying to say in your second paragraph, but I highly recommend you spend a few weeks playing with http://observablehq.com instead of speculating about the differences.

In practice, I find it to be dramatically better than previous notebook environments for data analysis, exploratory programming / computational research, prototyping, data visualization, and writing/reading interactive documents (blog posts, software library documentation, expository papers ...). It has a lower barrier to starting new projects, a lower-friction flow throughout

I find it better at every stage of my thinking process from blank page up through final code/document, and would recommend it vs. Jupyter or Matlab or Mathematica in every case unless some specific software library is needed which is unavailable in Javascript. The only other tool I really need is pen and paper, though I also use http://desmos.com/calculator and Photoshop a fair bit.