imagej / imagej/imagej-scripting

How to reconcile tutorials here with the notebooks in the tutorials repository

Open
#24 8 comments 0 reactions 0 assignees View on GitHub
to do
Dominant language
Python
Stars
27
Forks
15
PR merge metrics
No merged PRs in 30d

Description

I am developing a (planned to be) comprehensive set of ImageJ tutorials as (Beaker for now, but hopefully later Jupyter too) notebooks, in the [imagej/tutorials](https://github.com/imagej/tutorials) repository (on the `dev-manual` branch as of this writing, but that's soon to change). It is awesome to see more tutorials being developed and added here as script templates, but I am wondering what our general strategy should be for reconciling these two resources. Personally, I would like it if everything were somehow unified.

Maybe all the notebooks could be converted to scripts too and committed here? Or probably better, we could add a feature to the Script Editor to open Beaker/Jupyter notebooks as plain scripts directly? And add them as URL resources to the menus? In that way, there would be no potential for "skew" and all notebooks could be made automatically available from inside ImageJ. The hitch is that this notebook-to-script conversion would need to be quite smart about `@` parameters. When we get @hadim's SciJava Jupyter kernel going, they could be baked in to the notebooks directly; otherwise, it is more complicated unfortunately.

@hadim @bnorthan @imagejan What do you guys think? Should we just give up and keep maintaining these two separate sets of things? Or do you see a way they could work together?

Contributor guide

No contributing guide indexed for this repository

Research direction

Start by comparing the script templates in this repository with the notebooks in imagej/tutorials, including the dev-manual branch mentioned in the issue. Review the Script Editor, URL resources, @ parameters, and SciJava Jupyter kernel discussion; done means agreeing on and documenting one maintainable reconciliation strategy.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter, jupyter-notebook
Domain
documentation, tooling
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.