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Replace import
GitHub Actions job with pytest test
#5600
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Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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@pytest.mark.skipif(shutil.which("docker") is None, reason="docker is required to run this test") | ||
def test_import_mlflow(tmp_path): |
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It takes about 30 seconds to run this test on GitHub Actions:
Tue, 05 Apr 2022 05:41:56 GMT tests/test_flavors.py::test_all_flavors_can_be_accessed_from_mlflow PASSED [ 1%]
Tue, 05 Apr 2022 05:42:28 GMT tests/test_import.py::test_import_mlflow PASSED [ 1%]
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
import: | ||
runs-on: ubuntu-latest | ||
steps: | ||
- uses: actions/checkout@v3 | ||
- uses: actions/setup-python@v3 | ||
with: | ||
python-version: "3.7" | ||
- name: Install mlflow | ||
run: | | ||
pip install -e . | ||
- name: Verify mlflow can be imported without errors | ||
run: | | ||
python -c "import mlflow" | ||
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# Just importing mlflow should not create `mlruns` directory | ||
# See: https://github.com/mlflow/mlflow/issues/3400 | ||
if [ -d "./mlruns" ]; then | ||
exit 1 | ||
fi |
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This job takes about 30 seconds:
https://github.com/mlflow/mlflow/runs/5828558499?check_suite_focus=true#logs
breakdown:
- Install mlflow: 28 sec.
- Verify mlflow can be imported without errors: 1 sec.
- Rest: 1 sec.
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LGTM
Signed-off-by: harupy 17039389+harupy@users.noreply.github.com
What changes are proposed in this pull request?
Replace the
import
GitHub Actions job with a pytest test to save the number of GitHub Actions runs.How is this patch tested?
New test
Does this PR change the documentation?
ci/circleci: build_doc
check. If it's successful, proceed to thenext step, otherwise fix it.
Details
on the right to open the job page of CircleCI.Artifacts
tab.docs/build/html/index.html
.Release Notes
Is this a user-facing change?
(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts
: Artifact stores and artifact loggingarea/build
: Build and test infrastructure for MLflowarea/docs
: MLflow documentation pagesarea/examples
: Example codearea/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models
: MLmodel format, model serialization/deserialization, flavorsarea/projects
: MLproject format, project running backendsarea/scoring
: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra
: MLflow Tracking server backendarea/tracking
: Tracking Service, tracking client APIs, autologgingInterface
area/uiux
: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker
: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy
: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows
: Windows supportLanguage
language/r
: R APIs and clientslanguage/java
: Java APIs and clientslanguage/new
: Proposals for new client languagesIntegrations
integrations/azure
: Azure and Azure ML integrationsintegrations/sagemaker
: SageMaker integrationsintegrations/databricks
: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change
- The PR will be mentioned in the "Breaking Changes" sectionrn/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature
- A new user-facing feature worth mentioning in the release notesrn/bug-fix
- A user-facing bug fix worth mentioning in the release notesrn/documentation
- A user-facing documentation change worth mentioning in the release notes