Python
Getting Started with Python in ExCL with best practice recommendations.
This page covers a few recommendations and tips for getting started with Python in ExCL following best practices for packaging python projects and using virtual environments. There are many different ways to structure and package python projects and various tools that work with python, so this page is not meant to be comprehensive but to provide a few recommendations for getting started.
Python Virtual Environments with venv
Using virtual environments is the recommended way to isolate Python dependencies and ensure compatibility across different projects. Virtual environments prevent conflicts between packages required by different projects and simplify dependency management. The goal with isolated, project specific python environments is to avoid the situation found in https://xkcd.com/1987/.

If you are a using the fish shell, the simple function show below is a wrapper around venv to activate a python virtual environment if one already exists in .venv
in the current directory or create a new virtual environment and activate it if one does not already exist.
function pvenv --wraps='python3 -m venv --upgrade-deps venv' --description 'Create and activate a python virtual environment in .venv with updated pip and prompt set to the folder\'s name'
if test -e .venv/bin/activate.fish
echo Using existing `.venv`.
source .venv/bin/activate.fish
else
echo Creating new `.venv`.
python3 -m venv --upgrade-deps --prompt (basename $PWD) .venv $argv; and source .venv/bin/activate.fish;
end
end
This pvenv
function is already configured system wide for fish on ExCL systems.
To create the virtual environment without using the wrapper function is also easy.
In bash:
python3 -m venv --upgrade-deps --prompt $(basename $PWD) .venv
source .venv/bin/activate
In fish:
python3 -m venv --upgrade-deps --prompt (basename $PWD) .venv
source .venv/bin/activate.fish
Here is the usage of venv which explains what the various flags do. From venv — Creation of virtual environments — Python 3.13.1 documentation.
usage: venv [-h] [--system-site-packages] [--symlinks | --copies] [--clear]
[--upgrade] [--without-pip] [--prompt PROMPT] [--upgrade-deps]
[--without-scm-ignore-files]
ENV_DIR [ENV_DIR ...]
Creates virtual Python environments in one or more target directories.
positional arguments:
ENV_DIR A directory to create the environment in.
options:
-h, --help show this help message and exit
--system-site-packages
Give the virtual environment access to the system
site-packages dir.
--symlinks Try to use symlinks rather than copies, when
symlinks are not the default for the platform.
--copies Try to use copies rather than symlinks, even when
symlinks are the default for the platform.
--clear Delete the contents of the environment directory
if it already exists, before environment creation.
--upgrade Upgrade the environment directory to use this
version of Python, assuming Python has been
upgraded in-place.
--without-pip Skips installing or upgrading pip in the virtual
environment (pip is bootstrapped by default)
--prompt PROMPT Provides an alternative prompt prefix for this
environment.
--upgrade-deps Upgrade core dependencies (pip) to the latest
version in PyPI
--without-scm-ignore-files
Skips adding SCM ignore files to the environment
directory (Git is supported by default).
Once an environment has been created, you may wish to activate it, e.g. by
sourcing an activate script in its bin directory.
The virtual environment can be exited with deactivate
.
Creating a Python Project in using the Hatch build system with CI support
Python Project Template provides a template for creating a python project using the hatch build system with CI support using ORNL's GitLab instance, complete with development documentation, linting, commit hooks, and editor configuration.
Steps to use the template:
Run
setup_template.sh
to set up the template for the new project.Remove
setup_template.sh
See Python Project Template Documentation for details on the template.
Using UV to create a python virtual environment with a specific version of python.
When a specific version of python is required, uv can be used to create a virtual environment with the specific version of python.
uv venv --python <version>
For example:
uv venv --python 3.11
Use the command below to see the available python versions.
uv python list
See astral-sh/uv - python management and uv docs - installing a specific version for details.
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