sphinx_exec_jupyter

The sphinx-exec-jupyter Sphinx extension allows you to execute code in a Jupyter kernel and embed the output directly into your Sphinx documentation.

This extension adds at least one directive (see sphinx_exec_jupyter.holoviews for more):

.. exec-jupyter::

Execute a Jupyter notebook cell and embed the output into the documentation. The Python expression on the last line of the directive body is displayed.

Examples

..  exec-jupyter::

    import pandas as pd

    pd.DataFrame(dict(
        A=[1, 2, 3],
        B=[4, 5, 6],
    ))

results in:

import pandas as pd

pd.DataFrame(dict(
    A=[1, 2, 3],
    B=[4, 5, 6],
))

	A	B
0	1	4
1	2	5
2	3	6

sphinx_exec_jupyter.holoviews

If you installed sphinx-exec-jupyter with the holoviews extra (e.g. pip install sphinx-exec-jupyter[holoviews]), the sphinx_exec_jupyter.holoviews sub-extension is loaded automatically.

This extension adds a setting and one more directive:

holoviews_backends

Type:

list[str]

Default:

['bokeh']

A list of backends to use for rendering HoloViews plots.

.. holoviews::

Embed a HoloViews plot into the documentation. The Python expression on the last line of the directive body is displayed.

:backends: backend1,backend2,... (comma separated list of backends)

The list of backends to use for rendering the plot. Defaults to holoviews_backends.

Examples

No options (defaults to bokeh):

..  holoviews::

    hv.Curve([1, 2, 3, 2, 1])

results in:

hv.Curve([1, 2, 3, 2, 1])

With multiple backends specified (needs the sphinx_design extension to be loaded):

..  holoviews::
    :backends: bokeh,matplotlib,plotly

    hv.Curve([1, 2, 3, 2, 1])

results in:

bokeh

hv.Curve([1, 2, 3, 2, 1])

matplotlib

hv.Curve([1, 2, 3, 2, 1])

plotly

hv.Curve([1, 2, 3, 2, 1])