My understanding is that webpack is used, but that’s based on the tutorials I 
read. Have I got that right?

thanks,
-steve

> On May 22, 2018, at 10:02 AM, John <[email protected]> wrote:
> 
> For classic jupyter notebook, vpython is copying javascript files to the 
> nbextensions directory by calling the routine
> 
> notebook.nbextensions.install_nbextension()
> 
> from the vpython package directory. 
> (site-packages/vpython/vpython_libraries/) . These javascript files are 
> loaded into the notebook from the nbextensions directory using ipython 
> display method along with requirejs.
> 
> display(Javascript("""require(["nbextensions/vpython_libraries/glowcomm"], 
> function(){console.log("GLOWCOMM LOADED");})"""))
> This works in classic jupyter notebook but not in Jupyterlab . Does 
> jupyterlab use the nbextensions directory or does it is place javascript fles 
> in a different directory. What should be used in place of requirejs to load 
> javascript files?
> 
> 
> 
> 
> On Tuesday, May 22, 2018 at 6:11:57 AM UTC-7, Steve Spicklemire wrote:
> Hi Jupyter folks,
> 
> I'm hoping to carve out some time in the next few weeks to make some serious 
> progress on a jupyterlab compatible version of vpython (http://vpython.org).
> 
> The jupyter notebook interaction of vpython involves opening a communication 
> channel (ipykernel.comm.Comm) between the kernel process and a javascript 
> program running in the browser handling the display. The javascript code is 
> currently embedded in the python package 
> (site-packages/vpython/vpython_libraries/) and transferred into nbextensions 
> on demand and then pulled into the notebook using ipython.display.display.
> 
> It has been suggested that this whole scheme needs to be redesigned under 
> jupyterlab. I'm hoping to begin that design process now, but being new to 
> jupyterlab, I'm not really sure where to begin. I did read through the 
> tutorials for jupyterlab extensions, but I'm not clear what sort of extension 
> would be needed here since it doesn't seem to exactly match the use cases 
> described in the exam extensions. I'd love some input from any jupyterlab 
> veterans about how we should go about planning/building this. Ideally users 
> would be able to take code that works in the jupyter notebook, and run it 
> unchanged in jupyterlab.
> 
> something like:
> 
> -------
> from vpython import *
> 
> s=sphere()
> 
> --------
> 
> without needing any magics or other python code if possible.
> 
> thanks,
> -steve
> 
> 
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