Summary
Keypoints
- Load and run
 Use python from module system
Start a Python shell session either with
pythonoripythonrun scripts with
python3 <script.py>
- Packages
 Check for preinstalled packages
from the Python shell with the
importcommandfrom BASH shell with the
pip listcommand at both centersml help python/3.11.8at UPPMAXmodule -r spider '.*Python.*'at HPC2N and LUNARC
Installation with PYPI
You install own packages with the
pip install --usercommand
At UPPMAX Conda is also available
Conda is an installer of packages but also bigger toolkits
Rackham: Pip or secondary conda
Bianca: conda and secondary wharf + (pip or conda)
- Isolated environments
 With a virtual environment you can tailor an environment with specific versions for Python and packages, not interfering with other installed python versions and packages.
Make it for each project you have for reproducibility.
There are different tools to create virtual environments.
HPC2N has
virtualenvandvenvinstall packages with
pip.the flag
--system-site-packagesincludes preinstalled packages as well
UPPMAX has
venvandCondavenv is very similar to
virtualenvConda creates isolated environments as well
requires that you install all packages needed.
LUNARC has
virtualenv,venv, andconda
- Batch mode
 The SLURM scheduler handles allocations to the calculation nodes
Batch jobs runs without interaction with user
A batch script consists of a part with SLURM parameters describing the allocation and a second part describing the actual work within the job, for instance one or several Python scripts.
Remember to include possible input arguments to the Python script in the batch script.
- Interactive work on calculation nodes
 Start an interactive session on a calculation node by a SLURM allocation (similar flags)
At HPC2N:
salloc… not really interactiveAt UPPMAX:
interactive…At LUNARC:
interactive…
Follow the same procedure as usual by loading the Python module and possible prerequisites
Not really clear? (5 min)
Discuss in breakout rooms
Learn from each other
See also
For other topics, see python documentation.
A nice introduction to packages can be found here: https://aaltoscicomp.github.io/python-for-scicomp/dependencies/
CodeRefinery develops and maintains training material on software best practices for researchers that already write code.
This material addresses all academic disciplines and tries to be as programming language-independent as possible. https://coderefinery.org/lessons/