Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. Python combines remarkable power with very clear syntax. It has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++.

Python is available as a module on Apocrita.

Python Versions

There are multiple versions of Python available as modules including Python 2 and Python 3, Python 2 is still very common but is now in legacy mode, Python 3 is under active development and has a large number of improvements.

While some code will work in both versions there are a number of incompatibilities so the version of Python you need may depend on the code you are running. For new code bases Python 3 is strongly recommended.


To run the latest installed version of Python (the latest Python 3), simply load the Python module:

module load python

then run Python with a script file:


Python Command

We recommend using the Python command for the specific Python version you require (e.g. python2.7) rather than using the default python, as the default may change.

Example jobs

Serial job

Here is an example job running on 1 cores.

#$ -cwd
#$ -j y
#$ -pe smp 1
#$ -l h_rt=4:0:0
#$ -l h_vmem=2G

module load python

Serial job - Virtualenv

To use a Python virtualenv in a job script you need to activate the virtualenv:

#$ -cwd
#$ -j y
#$ -pe smp 1
#$ -l h_rt=4:0:0
#$ -l h_vmem=2G

# Activate virtualenv
source <envname>/bin/activate

# Run Python script

Installing Python Packages

Whilst packages can be installed locally using pip and easy_install we recommend using virtualenvs to ensure clean environments.


You can use virtualenv to set up your own virtual Python environment over which you have full control. This allows you to use a specific Python version and its own set of packages. Once the virtual environment is set up, you need activate it when you log in and then you can use python, pip and easy_install.

# virtualenv is installed as part of the python module
$ module load python
# Set up an environment called <envname>
$ virtualenv <envname>
# Activate the environment
$ . <envname>/bin/activate
# Use Python / pip etc. in the environment
(<envname>)$ pip install <module>
# Run Code
(<envname>)$ python
# Stop using the environment
$ deactivate

Setting up numpy

Using virtualenv, it is straight-forward to install a personal copy of numpy:

$ module load virtualenv
$ virtualenv numpy
$ source numpy/bin/activate
(numpy)$ pip install numpy