So I got the Jupyter Kotlin kernel running fairly ...

# datascience

[Florian Magin]

So I got the Jupyter Kotlin kernel running fairly quickly but I am now running in some issues that might be related to the kernel internals: I start IkotlinKt.main like the python code in jupyter would, but I call it from java code. This allows me to attach a jupyter-console to the kernel and access all the packages. But the classes inside the REPL do not share the static class variables with the java code that started the kotlin kernel via IkotlinKt.main .
My guess is that this is accidental because this would never be relevant if you the kernel is supposed to be started by Python anyway. Does someone have a quick pointer of the relevant documentation or code concerning those internals?

[Ilya Muradyan]

Classpath and classloader used are set in compiler configuration and evaluator configuration in repl.kt file. Classes from kernel project cannot be accessed from repl directly: declare them in jupyter-lib project instead

[Florian Magin]

Is there any way to access them from the repl? I am not sure what you mean with

declare them in jupyter-lib project instead

[Florian Magin]

The feature that the REPL has full access to all the classes and static values of the java code that starts IkotlinKt.main is essential for what I want to achieve. If this requires some changes in jupyter kotlin kernel I will look into or use some lower level methods to start the kernel

[Ilya Muradyan]

There is a -classpath argument of main. You may add your classes/jars to it to access symbols in them.

[Florian Magin]

I ran into that earlier and am calling it with that argument now, but this is not the issue I am currently talking about

[Florian Magin]

with that I can import a class, but it seems like if I import a specific class inside my java code, set a static variable on it, start the kotlin kernel and attach to it via jupyter-console the static variable will not be set