Applications/Python
Contents
Application Details
- Description: Python is a high-level interpreted programming language for general-purpose programming, supported by a large number of libraries for many tasks
- Versions: Python 2.7.11 and 3.5.1
- Module names: python/2.7.11 python/3.5.1
- License: Free to use - Python Software Foundation License
Usage Examples
Python is provided by the Anaconda package too
Interactive
Interactive with command line:
[username@c170 ~]$ module add python/anaconda/4.0/2.7 [username@c170 ~]$ python Python 2.7.5 (default, Nov 20 2015, 02:00:19) [GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>>
Interactive with command line with IPython:
[username@c170 ~]$ ipython Python 2.7.13 |Anaconda custom (64-bit)| (default, Dec 20 2016, 23:09:15) Type "copyright", "credits" or "license" for more information. IPython 5.1.0 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details. In [1]:
Batch Submission
#!/bin/bash #SBATCH -J PythonTest # Job name, you can change it to whatever you want #SBATCH -N 1 # Number of nodes #SBATCH --ntasks-per-node 1 # Number of cores per node #SBATCH -o %N.%j.out # Standard output will be written here #SBATCH -e %N.%j.err # Standard error will be written here #SBATCH -p compute # Slurm partition, where you want the job to be queued module purge module add python/3.5.1 python PythonTest.py
This is then submitted as follows:
[username@login01 ~]$ sbatch Pythontest.job Submitted batch job 289522
Virtual Environments
A Python Virtual Environment allows users to create a custom environment/s in which they can have the packages, and versions of said packages that they require without having to have elevated user privileges on the system.
There are many benefits to using a virtual environment on a system. Here is a short non-exhaustive list of a few of the key benefits:
- Control over packages and package versions
- An arbitrary number of virtual environments can be created for different tasks
- Reproducibility - A user can replicate a python environment on any system, so as to be able to run or re-run a particular task or job under the same conditions
Creation of Virtual Environment Using Python 2.7.11 or 3.5.1 on Viper
To create a virtual environment you would issue the following command:
IMPORTANT NOTE: By default the virtual environment does not use the system python packages. However because of the way viper is configured it will see system packages because of the PYTHONPATH environment variable. So it is advised if you would like a clean environment (meaning no system packages being included) to set this variable to empty as follows: export PYTHONPATH=
[user@c001 ~ ]$ virtualenv foo
Further Information
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