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.github/workflows: use rye in CI
Use rye instead of poetry in CI.
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.github/workflows/python-app.yml
vendored
28
.github/workflows/python-app.yml
vendored
@ -16,30 +16,26 @@ jobs:
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steps:
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v4
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- name: Install poetry
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- name: Install rye
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run: pipx install poetry
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uses: eifinger/setup-rye@v4
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- uses: actions/setup-python@v5
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with:
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with:
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python-version: '3.11'
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version: 'latest'
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cache: 'poetry'
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- run: rye sync
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- run: poetry install
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- name: Lint
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- name: Lint with flake8
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run: |
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run: |
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# stop the build if there are Python syntax errors or undefined names
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# stop the build if there are Python syntax errors or undefined names
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poetry run flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
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rye lint
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# exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
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poetry run flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
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- name: Test with pytest
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- name: Test with pytest
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run: poetry run pytest
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run: rye test
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- name: Test CLI
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- name: Test CLI
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run: |
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run: |
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# Basic test
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# Basic test
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poetry run csv-metadata-quality -i data/test.csv -o /tmp/test.csv
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rye run csv-metadata-quality -i data/test.csv -o /tmp/test.csv
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# Test with unsafe fixes
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# Test with unsafe fixes
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poetry run csv-metadata-quality -i data/test.csv -o /tmp/test.csv -u
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rye run csv-metadata-quality -i data/test.csv -o /tmp/test.csv -u
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# Test with experimental checks
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# Test with experimental checks
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poetry run csv-metadata-quality -i data/test.csv -o /tmp/test.csv -e
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rye run csv-metadata-quality -i data/test.csv -o /tmp/test.csv -e
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# Test with AGROVOC validation
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# Test with AGROVOC validation
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poetry run csv-metadata-quality -i data/test.csv -o /tmp/test.csv --agrovoc-fields dcterms.subject
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rye run csv-metadata-quality -i data/test.csv -o /tmp/test.csv --agrovoc-fields dcterms.subject
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# Test with AGROVOC validation (and dropping invalid)
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# Test with AGROVOC validation (and dropping invalid)
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poetry run csv-metadata-quality -i data/test.csv -o /tmp/test.csv --agrovoc-fields dcterms.subject -d
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rye run csv-metadata-quality -i data/test.csv -o /tmp/test.csv --agrovoc-fields dcterms.subject -d
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