As for debugging. I do not imagine why anyone will...

# datascience

[altavir]

As for debugging. I do not imagine why anyone will use full debugger for the notebook, but some debugging would be nice, so here is a kotlinish-notbookish solution:
• Introduce a wrapper interface DebugContext like this:

interface DebugContext{
  fun <T> trace(value: T): ReadWriteProperty<Any?, T>

  (suspend) fun breakPoint()
}

• The idea is that you can wrap any variable in the context in a delegate and dump all changes to a debug container. When the breakPoint is called, the execution will block/suspend and dump current debug state to console/output widget and wait for user input to unblock.
This could be implemented on a library level based on the notebook API. The usage will look like this:

%%debug
var a by trace(4)
repeat(10){
  a++
  breakPoint()
}

If you like this idea, I can write an issue from it. I personally prefere not to do complex code in the notebook and move all heavy logic to the project.

[Ilya Muradyan]

Have you seen an implementation of debugger in python notebooks?

[Ilya Muradyan]

https://blog.jupyter.org/a-visual-debugger-for-jupyter-914e61716559

[altavir]

No, probably I stopped working a lot with Python before it arrived. It looks interesting, but it seems it will require a lot of effort and actual JVM debugger attached to the process. Does scripting engine support source mapping?