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========================= A Jupyter kernel for bash

Installation

This requires IPython 3.

.. code:: shell

pip install bash_kernel
python -m bash_kernel.install

To use it, run one of:

.. code:: shell

jupyter notebook
# In the notebook interface, select Bash from the 'New' menu
jupyter qtconsole --kernel bash
jupyter console --kernel bash

pipx and "externally managed" environments

A recent-ish `PEP 668 <https://peps.python.org/pep-0668/#guide-users-towards-virtual-environments>`_ recommends that users install Python applications with `pipx` rather than global installs with `pip`. This is strongly suggested/enforced in current Linux distros. Because `bash_kernel` needs an extra step to actually work after installing with `pip` or `pipx`, this causes some inconvenience.

First, one must install the Jupyter ecosystem with pipx, and then inject bash_kernel (and any other bits of the jupyter ecosystem you use, like papermill) into the same pipx venv.

.. code:: shell

    pipx install --include-deps jupyter
    pipx inject --include-apps --include-deps jupyter bash_kernel

One then must manually find the corresponding venv, activate it, and run `python -m bash_kernel.install` *within* that virtual env. If done outside it, this won't work as bash_kernel is not installed in the global environment.

.. code:: shell

    cd ~/.local/pipx/venvs/jupyter/
    source bin/activate
    python -m bash_kernel.install
    deactivate

Of course, one can also install bash_kernel to the global environement thusly:

.. code:: shell

    pip install --break-system-packages juptyer bash_kernel
    python -m bash_kernel.install

Requirements of Bash

Bash kernel directly interacts with bash, and therefore requires a functioning interactive build of bash. In nearly all cases this will be the default, however some distributions remove GNU readline or other interactivity features of bash. Almost always, these features are provided in a separate, more complete bash package, which should be installed. See for example https://github.com/takluyver/bash_kernel/issues/142.

Displaying Rich Content

To use specialized content (images, html, etc) this file defines (in build_cmds()) bash functions that take the contents as standard input. Currently, display (images), displayHTML (html) and displayJS (javascript) are supported.

Example:

.. code:: shell

cat dog.png | display
echo "<b>Dog</b>, not a cat." | displayHTML
echo "alert('Hello from bash_kernel\!');" | displayJS

Updating Rich Content Cells

If one is doing something that requires dynamic updates, one can specify a unique display_id, which should be a string name. On each update, the contents will be replaced by the new value. Example:

.. code:: shell

display_id="id_${RANDOM}"
((ii=0))
while ((ii < 10)) ; do
    echo "<div>${ii}</div>" | displayHTML $display_id
    ((ii = ii+1))
    sleep 1
done

The same works for images and javascript content.

Remember to create always a new id each time the cell is executed, otherwise it will try to display on an HTML element that no longer exists (they are erased each time a cell is re-run).

Programmatically Generating Rich Content

Alternatively one can simply generate the rich content to a file in /tmp (or $TMPDIR) and then output the corresponding (to the mimetype) context prefix "_TEXT_SAVED_*" constant. So one can write programs (C++, Go, Rust, etc.) that generates rich content appropriately, when within a notebook.

The environment variable "NOTEBOOK_BASH_KERNEL_CAPABILITIES" will be set with a comma separated list of the supported types (currently "image,html,javascript") that a program can check for.

To output to a particular "display_id", to allow update of content (e.g: dynamically updating/generating a plot from a command line program), prefix the filename with "()". E.g: a line to display the contents of /tmp/myHTML.html to a display id "id_12345" would look like:

bash_kernel: saved html data to: (id_12345) /tmp/myHTML.html

More Information

For details of how this works, see the Jupyter docs on wrapper kernels <http://jupyter-client.readthedocs.org/en/latest/wrapperkernels.html>, and Pexpect's docs on the replwrap module <http://pexpect.readthedocs.org/en/latest/api/replwrap.html>.