Python is an interpreted high-level programming language for general-purpose programming. It’s design philosophy emphasizes code readability using significant whitespace. Python features a dynamic type system and automatic memory management. It supports multiple programming paradigms, including object-oriented, imperative, functional and procedural, and has a large and comprehensive standard library. Documentation for Python can be found on its official website. Currently, versions 2.7 and 3.0 of Python are available on the cluster.
python. Python files end in *.py, and can be run from the command line using
python filename.pywhere filename is the name of the Python file.
Once the virtual environment is created, it can be launched at any time by ensuring that the python3 module is loaded, using the command
module load python3/anaconda/5.2.0 conda create -n python-environment python-essentials python-base source activate python-environment
and then launching the environment by using
module load python3/anaconda/5.2.0
Next, you can install any packages you need inside this environment. These packages will only be available
within this environment. Python packages and dependencies can be installed in your virtual environment by either
using pip or the conda package manager.
source activate python-environment
where package-name is the name of the package you wish to install. For example, to install SQLAlchemy, a Python
SQL database library, you can use the command
pip install package-name
Once downloaded, you will be able to use the SQLAlchemy library in your Python programs within the created
pip install SQLAlchemy
where package-name is the name of the package you wish to install. Many conda packages are used in scientific
computing and data analysis. For example, NumPy, a useful scientific computing package for Python that contains
an N-dimensional array object, tools for integrating C++ and Fortran code, and useful linear algebra and random
number capabilities, can be installed through Conda using the command
conda install package-name
To exit the Python virtual environment, use the command
conda install NumPy
3. Prepare the submission script, which is the script that is submitted to the Slurm scheduler as a job in order to run the Python script. The linked repository provides the script job.sh as an example.
import random print("Hello World!") a = 10 b = 3 print("a is %d" % a) print("b is %d" % b) print("a*b is %d" % (a*b)) print("Random list: ") rand_list =  for x in range(10): rand_list.append(random.randint(1,100)) print(rand_list) print("List sorted: ") print(sorted(rand_list))
#!/bin/sh #SBATCH --job-name=py_test #SBATCH -o py_out%j.out #SBATCH -e py_err%j.err #SBATCH -N 1 #SBATCH --ntasks-per-node=1 echo -e '\nsubmitted Python job' echo 'hostname' hostname # creates a python virtual environment module load python3/anaconda/5.2.0 source activate python-environment # run python script python3 test.py # exit the virtual environment source deactivate
4. Submit the job using:
5. Examine the results.