Setup Python
Pip packages¶
The actions/setup-python actions installs python with a specific version and could cache downloaded Python packages. (But not the installed environment)
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.x'
cache: 'pip'
- run: pip install -r requirements.txt
Cache venv environment¶
The following workflow caches the virtual environment folder1, which is faster than caching the whole Python environment.
- name: Setup Python
uses: actions/setup-python@v5
id: setup-python
with:
python-version: '3.x'
- name: Cache virtualenv
uses: actions/cache@v4
id: cache-venv
with:
key: ${{ runner.os }}-venv-${{ steps.setup-python.outputs.python-version }}-${{ hashFiles('requirements.txt') }}
path: .venv
- name: Install Python dependencies
run: |
python -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt
echo ".venv/bin" >> $GITHUB_PATH
echo "VIRTUAL_ENV=.venv" >> $GITHUB_ENV
echo "PYTHON=${VIRTUAL_ENV}/bin/python" >> $GITHUB_ENV
echo "JULIA_PYTHONCALL_EXE=${VIRTUAL_ENV}/bin/python">> $GITHUB_ENV
Use uv¶
uv is a drop-in replacement for pip, an extremely fast Python package and project manager written in Rust.
The GitHub actions workflow:
name: UV example
jobs:
python-linux:
env:
UV_SYSTEM_PYTHON: 1
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.x'
- name: Set up uv
run: curl -LsSf https://astral.sh/uv/install.sh | sh
- name: Install requirements
run: uv pip install -r requirements.txt
Conda packages¶
The mamba-org/setup-micromamba action installs the micromamba package manager and conda package dependencies. It also caches the Python runtime environment.
- uses: mamba-org/setup-micromamba@v1
with:
environment-file: environment.yml
init-shell: bash
cache-environment: true
post-cleanup: 'all'
- name: Run custom command in micromamba environment
shell: micromamba-shell {0}
run: python --version