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Jupyter/JupyterLab should be installed on your computer if you have installed Anaconda. but please also verify your Jupyter installation.

Installation of extensions on Linux, macOS, and Windows

Here you will find how to install optional JupyterLab extensions which will be demonstrated during the workshop.

You are not required to install these extensions, but if you wish to you can follow the instructions below.

JupyterLab extensions are npm packages (standard package format for Javascript), and to install the extensions you need to install the nodejs package:

$ conda install nodejs

Widget extension

To use widgets in JupyterLab, you also need to run the following command (even if you installed through conda):

$ jupyter labextension install @jupyter-widgets/jupyterlab-manager

For classic notebooks, if you did not install Python through Anaconda, and if you installed Jupyter using pip and not conda, you will need to execute this command in a terminal in order to activate widgets in Jupyter:

 $ conda install nodejs
 $ jupyter nbextension enable --py widgetsnbextension

Diffing/merging notebooks

The nbdime packages provides tools for diffing and merging Jupyter notebooks and is integrated with Git.

It can be installed by:

$ pip install nbdime

and then activated by

$ nbdime extensions --enable

Git extension

jupyterlab-git is a JupyterLab extension for version control using Git.

To install it, run these commands:

$ jupyter labextension install @jupyterlab/git
$ pip install jupyterlab-git
$ jupyter serverextension enable --py jupyterlab_git

GitHub extension

jupyterlab/github is a JupyterLab extension for accessing GitHub repositories.

To install it, run this command:

$ jupyter labextension install @jupyterlab/github


Python will be the main language used during the CodeRefinery workshop, but if you use R and want to experiment with R in Jupyter, install the r-essentials package:

$ conda install -c r r-essentials

Matlab/Octave/Julia kernels

Matlab, Octave and Julia can also be used as kernels to Jupyter, although this will not be covered in the workshop.

To install the Octave kernel, run

$ pip install octave_kernel
$ python -m octave_kernel.install

See this page for further information.

To enable Matlab in Jupyter, we refer to this page and this page which contain detailed instructions.

If you want to play around with IJulia, the Julia kernel for Jupyter, see instructions here.

How to verify the installation

To see whether JupyterLab is working as expected, type the command

$ jupyter-lab

and see if it opens up a new tab in your browser showing the JupyterLab interface.

Please also verify which Python version JupyterLab sees. Ideally it can see Python 3.

On Windows, the JupyterLab App can also be launched by clicking on the JupyterLab icon in the Anaconda menu.