The Strelka Computer Cluster has both Python 2 and 3 installed.  Most Python programs only run as a single process, so running on a cluster won't necessarily speed up execution without parallelizing the code.  If you need to run the same code repeatedly or with different inputs, you can launch many single-process jobs on the cluster at the same time.  Alternatively, it is possible to parallelize your code using modules such as multiprocessing, Dask, or mpi4py.  Cornell University Center for Advanced Computing has information on Python for High Performance which may be useful.  

Python 3

Run Python 3.6:

python3

Use pip to install Python packages in your home directory (in ~/.local/):

pip3 install --user <name of package>

Python 2

Run Python 2.7:

python2

Use pip to install Python packages in your home directory (in ~/.local/):

pip2 install --user <name of package>

Jupyter Notebooks

It is possible to run Python in a Jupyter notebook on Strelka.  For more information see Running Jupyter on Strelka

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