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CI: Install dvc via uv in the "GMT Tests" workflow #3695

Merged
merged 11 commits into from
Dec 19, 2024
15 changes: 13 additions & 2 deletions .github/workflows/ci_tests.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -133,7 +133,6 @@ jobs:
xarray${{ matrix.xarray-version }}
netCDF4
packaging
dvc
make
pip
python-build
Expand All @@ -154,9 +153,21 @@ jobs:
env:
GH_TOKEN: ${{ github.token }}

- name: Install uv
uses: astral-sh/[email protected]

- name: Install dvc
run: |
uv venv
source .venv/bin/activate
uv pip install dvc
uv pip list

# Pull baseline image data from dvc remote (DAGsHub)
- name: Pull baseline image data from dvc remote
run: dvc pull --no-run-cache --verbose && ls -lhR pygmt/tests/baseline/
run: |
source .venv/bin/activate
uv run dvc pull --no-run-cache --verbose && ls -lhR pygmt/tests/baseline/
Comment on lines +159 to +170
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Maybe we can combine the "Install dvc" and "Pull baseline image data from dvc remote" steps into one step "Setup DVC and pull baseline image data from dvc remote", so we don't have to source .venv/bin/activate twice.

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Let's just keep this as is, since I'm assuming this will be a temporary workaround until conda-forge's dvc supports Python 3.13. We might want to revert the changes here after a few months, so best to have two separate steps.


# Install the package that we want to test
- name: Install the package
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