As far as I can tell, I think you would have to improve the latency in the Jupyter messaging code if you want to get better interactivity.
I myself implemented/distributed a few notebooks with my InspectDR plotting tool. When you run it directly, InspectDR is quite fast. To see for yourself, simply plot one of the samples provided in the “https://github.com/ma-laforge/InspectDR.jl/tree/master/sample” directory.
If you run one of these examples, you can easily convince yourself that the response time is quite good. Simply use the mouse wheel to zoom in/out - or possibly shift+click+mousemove to drag the contents of the plot window.
If you take a look at some of my notebook examples, say the one provided in the following link:
You will notice that the update rate is significantly slower from the notebook when compared to the native response time of the GTK app. (Please refer to the “Interact/Reactive Control: Inspect/Gtk GUI” section at the end of the notebook).
I have to admit that my argument above is not 100% accurate. The code path used to handle mouse events is not the exact same as the one used to handle Jupyter/interact code. However, the point is that I put alot of effort in making the code for InspectDR fast - and I still get very slow interact code.