Installing Jupyter Notebook Extensions

To install the jupyter_contrib_nbextensions notebook extensions, three steps are required. First, the Python pip package needs to be installed. Then, the notebook extensions themselves need to be copied to the Jupyter data directory. Finally, the installed notebook extensions can be enabled, either by using built-in Jupyter commands, or more conveniently by using the jupyter_nbextensions_configurator server extension, which is installed as a dependency of this repo.

The Python package installation step is necessary to allow painless installation of the nbextensions together with additional items like nbconvert templates, pre-/postprocessors, and exporters.

1. Install the python package

PIP

All of the nbextensions in this repo are provided as parts of a python package, which is installable in the usual manner, using pip or the setup.py script. You can install directly from the current master branch of the repository

pip install https://github.com/ipython-contrib/jupyter_contrib_nbextensions/tarball/master

All the usual pip options apply, e.g. using pip’s --upgrade flag to force an upgrade, or -e for an editable install.

Conda

There are conda packages for the notebook extensions and the notebook extensions configurator available from conda-forge. You can install both using

conda install -c conda-forge jupyter_contrib_nbextensions

This also automatically installs the Javascript and CSS files (using jupyter contrib nbextension install --sys-prefix), so the second installation step below can therefore be skipped.

Installation from cloned Repo

You can also install from a cloned repo, which can be useful for development. You can clone the repo using

git clone https://github.com/ipython-contrib/jupyter_contrib_nbextensions.git

Then perform an editable pip install using

pip install -e jupyter_contrib_nbextensions

2. Install javascript and css files

This step copies the nbextensions javascript and css files into the jupyter server’s search directory. A jupyter subcommand is provided which installs all of the nbextensions files:

jupyter contrib nbextension install --user

The command is essentially a wrapper around the notebook-provided jupyter nbextension, and can take most of the same options, such as --user to install into the user’s home jupyter directories, --system to perform installation into system-wide jupyter directories, --sys-prefix to install into python’s sys.prefix, useful for instance in virtual environments, and --symlink to symlink the nbextensions rather than copying each file (recommended).

An analogous uninstall command is also provided, to remove all of the nbextension files from the jupyter directories.

3. Enabling/Disabling extensions

To use an nbextension, you’ll also need to enable it, which tells the notebook interface to load it. To do this, you can use a Jupyter subcommand:

jupyter nbextension enable <nbextension require path>

for example,

jupyter nbextension enable codefolding/main

To disable the extension again, use

jupyter nbextension disable <nbextension require path>

Alternatively, and more conveniently, you can use the jupyter_nbextensions_configurator server extension, which is installed as a dependency of this repo, and can be used to enable and disable the individual nbextensions, as well as configure their options.

jupyter_nbextensions_configurator

4. Migrating from older versions of this repo

The jupyter contrib nbextensions command also offers a migrate subcommand, which will

  • uninstall the old repository version’s files, config and python package
  • adapt all require paths which have changed. E.g. if you had the collapsible headings nbextension enabled with its old require path of usability/collapsible_headings/main, the migrate command will alter this to match the new require path of collapsible_headings/main.

For complex or customized installation scenarios, please look at the documentation for installing notebook extensions, server extensions, nbconvert pre/postprocessors and templates on the Jupyter homepage. More information can also be found in the Wiki.

See also installing Jupyter