Python 2 support
Only Python 3 is provided, as Python 2 was officially declared end-of-life by the January 1st, 2020.
While Python 3 can be found in the system /usr/bin/python3, this version does not come with many of the extra modules you may need. In those cases, you may want to use the python3 module or the conda module (still under development).
The python3 module
This is how Python has been made available on previous ECMWF computing platforms. Newer versions are provided twice a year, and they come with more than 200 extra Python packages. You can get the default version by:
module load python3
virtual environments
If you need to customise your Python environment, you may create a virtual environtment based on the installations provided. This may be useful if you need to use a newer version of a specific python package, but still want to benefit from the rest of the managed Python environment:
module load python3 mkdir -p $PERM/venvs cd $PERM/venvs python3 -m venv --system-site-packages myvenv
Then you can activate it when you need it with:
source $PERM/venvs/myenv/bin/activate
The conda module
We also provide a conda module which will allow you to create your own conda environments tailored to your requirements. You can start using conda with:
module load conda
modules and conda incompatibilities
While conda may be seen as a way to set up custom Python environments, it also manages software beyond that, installing other packages and libraries not necessarily related to Python itself.
Because those may conflict with the software made available through modules, loading the conda module effectively disables all the other modules that may be loaded in your environment.
Predefined conda environments
Experimental
Still under heavy development, the list of packages available in those environments may not be complete
Although you can always create your own environments, ECMWF provides pre-defined environments with the same extras as the traditional Python3 module. You can see the list of predefined environments, as well as your own, by running:
conda env list