Bokeh / JupyterLab integration

Updated high level design principles:

• mime bundle for loading BokehJS

  The output_notebook() function generates a mime bundle looks like

  {'application/javascript': js, 
    'application/vnd.bokeh.bootstrap_bokehjs': ''}
  

  In the classic notebook, it ignores the bokeh mimetype and runs the JS. In JLab, the Bokeh mimetype has a higher precedence, so it ignores the JS mimetype.

  • For the classic notebook the JS will load the Bokeh mini-extension to register for the show mime type. Additionally BokehJS will be loaded from CDN or for inline resources, from the JS in the bundle itself.

  • For JLab the Bokeh mini-extension will be previously installed via usual JLab mechanisms. The extension will load BokehJS from CDN or for inline resources, from the locally installed Bokeh package. (via a REST endpoint??)

• mime bundle for showing standalone docs and applications

  The show(...) function generates a mime bundle that looks like

  'application/vnd.bokeh.show`: JSON
  

  Where JSON is the serialized Bokeh Document and any additional metadata (versions, comm ids etc)

[bryevdv]

@jasongrout has summarized things perfectly above. I will try to run some preliminary experiments to validate this design approach.

Please also know I’m not trying to be snarky, or short with anyone. If I have seemed so (or been so) I apologize. I genuinely appreciate any and all help, because the perception below is the source of my extreme frustration and stress right now:

[rsinha25]

@canavandl , it works like a charm. Kudos on the amazing work. (y)