Run Python Scripts on the OSPool
- Run Python Scripts on the OSPool
- Running Base Python on the Open Science Pool
- Running Python Jobs That Use Additional Packages
- Other Considerations
- Getting Help
This guide will show you two examples of how to run jobs that use Python in the Open Science Pool. The first example will demonstrate how to submit a job that uses base Python. The second example will demonstrate the workflow for jobs that use specific Python packages, including how to install a custom set of Python packages to your home directory and how to add them to a Python job submission.
Before getting started, you should know which Python packages you need to run your job.
Running Base Python on the Open Science Pool
Several installations of base Python are available via the Open Science Pool's Software
Module System. To see what Python versions are available on the Open Science Pool
module avail while connected to our login node.
Create a bash script to run Python
To submit jobs that use a module to run base Python, first create a bash executable - for
this example we'll call it
run_py.sh - which will include commands to first
load the appropriate Python module and then run our Python script called
#!/bin/bash # Load Python module load python/3.7.0 # Run the Python script python3 myscript.py
If you need to use Python 2, load the appropriate module and replace the
Create an HTCondor submit file
In order to submit
run_py.sh as part of a job, we need to create an HTCondor
submit file. This should include the following:
run_py.shspecified as the executable
transfer_input_filesto bring our Python script
myscript.pyto wherever the job runs
- include requirements that request OSG nodes with access to base Python modules
All together, the submit file will look something like this:
universe = vanilla executable = run_py.sh transfer_input_files = myscript.py log = job.log output = job.out error = job.error # Require nodes that can access the correct OSG modules Requirements = (HAS_MODULES =?= true) && (OSGVO_OS_STRING == "RHEL 7") request_cpus = 1 request_memory = 2GB request_disk = 2GB queue 1
Once everything is set up, the job can be submitted in the usual way, by running
condor_submit command with the name of the submit file.
Running Python Jobs That Use Additional Packages
It's likely that you'll need additional Python packages (aka libraries) that are not present in the base Python installations made available via modules. This portion of the guide describes how to create a Python "virtual environment" that contains your packages and which can be included as part of your jobs.
Install Python packages
While connected to your login node, load the Python module that you want to use to run jobs:
$ module load python/3.7.0
Next, create a virtual environment. The first command creates a base environment:
$ python3 -m venv my_env
You can swap out
my_envfor a more descriptive name like
This creates a directory
my_env in the current working directory
Then activate the environment and install packages to it.
$ source my_env/bin/activate
Notice how our command line prompt changes to:
The activation process redefines some of the shell variables such as PYTHON_PATH, LIBRARY_PATH etc.
After activation, packages can be installed using
which is a tool to install Python packages.
(my_env)$ pip install numpy ......some download message... Installing collected packages: numpy Installing collected packages: numpy Successfully installed numpy-1.16.3
Install each package that you need for your job using the
pip install command. Once
you are done, you can leave the virtual environment:
The above command resets the shell environmental variables and returns you to the
normal shell prompt (with the prefix
All of the packages that were just installed should be contained in a sub-directory
my_env directory. To use these packages in a job, the entire
will be transfered as a tar.gz file. So our final step is to compress the
directory, as follows:
$ tar czf my_env.tar.gz my_env
Create executable script to use installed packages
In addition to loading the appropriate Python module, we will need to add a few steps to our bash executable to set-up the virtual environment we just created. That will look something like this:
#!/bin/bash # Load Python # (should be the same version used to create the virtual environment) module load python/3.7.0 # Unpack your envvironment (with your packages), and activate it tar -xzf my_env.tar.gz python3 -m venv my_env source my_env/bin/activate # Run the Python script python3 myscript.py # Deactivate environment deactivate
Modify the HTCondor submit file to transfer Python packages
The submit file for this job will be similar to the base Python job submit file shown above
with one addition - we need to include
my_env.tar.gz in the list of files specified by
As an example:
universe = vanilla executable = run_py.sh transfer_input_files = myscript.py, my_env.tar.gz log = job.log output = job.out error = job.error # Require nodes that can access the correct OSG modules Requirements = (HAS_MODULES =?= true) && (OSGVO_OS_STRING == "RHEL 7") request_cpus = 1 request_memory = 2GB request_disk = 2GB queue 1
This guide mainly focuses on the nuts and bolts of running Python, but it's important to remember that additional files needed for your jobs (input data, setting files, etc.) need to be transferred with the job as well. See our Introduction to Data Management on OSG for details on the different ways to deliver inputs to your jobs.
When you've prepared a real job submission, make sure to run a test job and then check
log file for disk and memory usage; if you're using significantly more or less
than what you requested, make sure you adjust your requests.
This page was updated on May 20, 2022 at 18:10 from examples/manage-python-packages.md.