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The default user interface is the newly designed Jupyterlab UI. However, you can switch to the old interface by clicking “Help” in the menu bar and then “Launch Classic Notebook”.

Getting started

The left sidebar contains tabs for a file browser, a list of running notebooks and terminals, a list of open tabs, etc. It can be collapsed and expanded by a click on the tabs icon.

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The official Jupyterlab manual can be found at https://jupyterlab.readthedocs.io/en/stable/user/interface.html

Working with notebooks

A notebook document needs a connected kernel/environment to be executable. The active kernel is shown in the upper right corner. A click on that name opens a menu to change the kernel.

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R : R 3.6 and default libraries

Conda environments

A conda environment combines an interpreter (e.g. for Python or R) and installed libraries under an explicit name. Such an environment can be available centrally on a server, which makes it available for all users of that system, or locally in the user’s home folder. Centrally stored environments are read-only. You can use them, but you cannot add or change libraries. If you need further libraries or specific library versions, you need to create a custom environment in your home folder.

Handling environments in the terminal

Conda paths need to be set once by the following command:

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You can change the active environment with the command „conda activate“. Python’s package manager pip always refers to the activated environment. Conda package manager refers to the activated environment, except you specify another one by the –n flag. 

Create a new environment

conda env create -n envName

conda activate -n envName

conda install library1 library2 (…)

Export an environment

conda activate myEnv

conda env export > myEnv.yaml

Import an environment

conda env create –f myEnv.yaml

Install libraries

conda install library1 –n myEnv

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conda activate myEnv

pip install library1

Handling environments with the graphical packages manager

The graphical package manager is started by clicking “Settings” -> “Conda Packages Manager” in the menu bar.

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