[smacke]

We have a couple of papers that go into some of the details.

https://smacke.net/papers/nbsafety.pdf https://smacke.net/papers/nbslicer.pdf

It looks like you are using a static approach for dependency inference. There are a lot of benefits to static approaches, but they can only get you so far. My JupyterCon presentation includes a bunch of examples where dynamic approaches are a must: https://t.ly/78rS

Besides that, there are a bunch of interesting design decisions about when to add edges between cells, when to break them, what metadata to annotate edges with, etc.

I'm hoping to abstract a way a bunch of the complexity by developing something like a runtime version of a language server protocol (working name "language kernel protocol") so that any editor that implements the protocol would get reactivity for free when running a kernel that likewise implements the protocol. I have an early version of this which is how IPyflow works for both Jupyter and JupyterLab; VSCode would be a great editor to add support for next.