Jupyter
The Jupyter interactive app launches a Jupyter notebook that is accessible through the web interface.
In the app form you can select Python environment, Jupyter notebook type, working directory and some more advanced settings.
For more information about the Python environments on Puhti and Mahti, see the documentation about Python. Note that the modules listed there are not guaranteed to work in the web interface and the installation of Python packages in Jupyter in the web interface works differently.
Currently supported Python environments
- geoconda
- python-data
- pytorch
- tensorflow
- qiskit
Installing packages
It is possible to install packages in the Jupyter notebook using pip. Before launching the Jupyter app, you should set the User packages path in the advanced settings view to the directory where you want to install packages. The default option is to install packages into $HOME/.local, but this is not recommended as the home directory quota is limited.
To install packages to the defined user packages directory, use the following command in the notebook:
import sys
!{sys.executable} -m pip install --user <package>
To install packages to a virtual environment you can use the command:
!{sys.executable} -m pip install <package>
It is recommended to either use a virtual environment or set the Python user packages path to a directory under /scratch or /projappl when launching the app if you need to install packages.
Customizing the environment
Custom Python environments can be created based on the Python modules or the system installed python. The settings for customizing the Python environment are in the advanced settings in the app form.
To use a Python installation from a module that is not provided in the app form you can select Custom and enter your own modules in the Custom Python module field in the form. You can also use it to load different versions of the modules provided by the form. If the Custom Python module field is left blank, the system Python will be used. Note that this requires using virtual environments.
Tykky installations
To use a Tykky installation with Jupyter, first include Jupyter packages in your Tykky installation. Then open Puhti web interface and Jupyter app page. There select the option Custom path from the Python menu.
Then enter the full path to the python interpreter of your Tykky installation. So if you created an installation with the command
conda-containerize new --prefix=/scratch/proj/myInst env.yml then the path to enter would be /scratch/proj/myInst/bin/python.
Virtual environment
You can create a virtual environment by enabling the virtual environment in the app form and providing desired path of your virtual environment to advanced settings. The path should be under either /scratch or /projappl. For example /scratch/<project>/<username>/<venv>.
You can also create the virtual environment with your terminal by navigating to either /scratch or /projappl folder and then creating the environment with a command:
python -m venv --system-site-packages <venv>
Make sure to load the module you are planning to use before creating the virtual environment.
To launch a created virtual environment later you need to select the same Python module and provide the same virtual environment path as when creating the environment. In Jupyter you can check the virtual environment you are currently using by running a command !echo $VIRTUAL_ENV in your notebook.
To install packages in your virtual environment you can run the command !{sys.executable} -m pip install <package> in your Jupyter notebook.
The virtual environments are currently not completely isolated as they use packages from the loaded modules.
Useful Jupyter commands
Remember to run import sys first.
| Functionality | Command |
|---|---|
| Install package to user directory | !{sys.executable} -m pip install --user <package> |
| Install package to virtual environment | !{sys.executable} -m pip install <package> |
| Check current venv | !echo $VIRTUAL_ENV |