Rewrite server extension to run Panel applications in kernels

[philippjfr]

This PR reimplements the panel preview server extension in its entirety to execute Panel applications in custom kernels. It does this by querying the notebook for its kernel spec and then requesting a kernel from Jupyter. In this kernel it executes the following:

from panel.io.jupyter_server_extension import PanelExecutor
executor = PanelExecutor('{{ path }}', '{{ token }}', '{{ root_url }}')
executor.render()

Internally the PanelExecutor creates a bokeh ServerSession and connects it to a Jupyter Comm. The PanelHandler will then serve the result of executor.render() and a request to open a WebSocket will be sent to the PanelWSHandler. This in turns forwards any messages it receives via the kernel.shell_channel to the Comm. This way we proxy any WS messages being sent to and from the server to the kernel.

The major benefit of this is:

• Panel preview now actually uses the appropriate kernel (and therefore environment) that it was intended for.

Drawbacks:

• Spinning up a kernel per session is expensive (we may be able to fix this by keeping only one kernel per kernelspec).

ToDo

• Fixes Render With Panel work with Different Kernels/Conda Environments in JupyterLab #3436 (comment)
• Add kernel selector via query parameter?
• Ensure kernels are cleaned up eventually
• Support autoreload
• Add tests

[codecov]

Codecov Report

Merging #3763 (1f5b97a) into master (e1d3bfc) will decrease coverage by 0.50%.
The diff coverage is 16.11%.

@@            Coverage Diff             @@
##           master    #3763      +/-   ##
==========================================
- Coverage   84.21%   83.70%   -0.51%     
==========================================
  Files         213      214       +1     
  Lines       31016    31267     +251     
==========================================
+ Hits        26121    26173      +52     
- Misses       4895     5094     +199     

Flag	Coverage Δ
ui-tests	33.89% <16.31%> (-0.10%)	⬇️
unitexamples-tests	76.56% <5.67%> (-0.57%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
panel/auth.py	39.34% <0.00%> (ø)
panel/io/jupyter_server_extension.py	0.00% <0.00%> (ø)
panel/tests/conftest.py	94.32% <86.66%> (-1.41%)	⬇️
panel/io/resources.py	87.10% <100.00%> (ø)
panel/io/state.py	69.16% <100.00%> (+0.06%)	⬆️
panel/tests/ui/io/test_jupyter_server_extension.py	100.00% <100.00%> (ø)
panel/util.py	86.41% <100.00%> (ø)

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[MarcSkovMadsen]

I can't see there is a high probability of someone spinning up lots of kernels unless they have Jupyter lab for ever running.

But maybe in a Jupyter Hub environment this could become an issue?

Our JupyterHub closes the session/ server after 1 hour of inactivity though.