Fix pytest options to show skipped tests and how to unskip them rather than deselecting them #4966
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harupy
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Oct 30, 2021
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| # Register markers to suppress `PytestUnknownMarkWarning` | ||
| config.addinivalue_line("markers", "large") | ||
| config.addinivalue_line("markers", "requires_ssh") | ||
| config.addinivalue_line("markers", "lazy_import") | ||
| config.addinivalue_line("markers", "notrackingurimock") | ||
| config.addinivalue_line("markers", "allow_infer_pip_requirements_fallback") |
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pytest raises the following warning for unregistered markers:
/home/runner/work/mlflow/mlflow/tests/pyfunc/test_model_export_with_class_and_artifacts.py:650: PytestUnknownMarkWarning:
Unknown pytest.mark.large - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/mark.html
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This warning is actually not harmful but makes it difficult to find other warnings.
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Nov 1, 2021
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| def pytest_runtest_setup(item): | ||
| markers = [mark.name for mark in item.iter_markers()] | ||
| marked_as_large = "large" in markers | ||
| large_option = item.config.getoption("--large") | ||
| large_only_option = item.config.getoption("--large-only") | ||
| if marked_as_large and not (large_option or large_only_option): | ||
| pytest.skip("use `--large` or `--large-only` to run this test") | ||
| if not marked_as_large and large_only_option: | ||
| pytest.skip("remove `--large-only` to run this test") | ||
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| if "requires_ssh" in markers and not item.config.getoption("--requires-ssh"): | ||
| pytest.skip("use `--requires-ssh` to run this test") | ||
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| if "lazy_import" in markers and not item.config.getoption("--lazy-import"): | ||
| pytest.skip("use `--lazy-import` to run this test") |
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With this fix, the pytest output looks like this:
$ pytest tests/xgboost
...
tests/xgboost/test_xgboost_autolog.py::test_xgb_autolog_log_models_configuration[False] SKIPPED (use `--large` or `--large-only` to run this test) [ 55%]
tests/xgboost/test_xgboost_autolog.py::test_xgb_autolog_does_not_break_dmatrix_instantiation_with_data_none PASSED [ 57%]
tests/xgboost/test_xgboost_model_export.py::test_model_save_load SKIPPED (use `--large` or `--large-only` to run this test) [ 59%]
tests/xgboost/test_xgboost_model_export.py::test_signature_and_examples_are_saved_correctly SKIPPED (use `--large` or `--large-only` to run this test) [ 61%]
tests/xgboost/test_xgboost_model_export.py::test_model_load_from_remote_uri_succeeds SKIPPED (use `--large` or `--large-only` to run this test) [ 63%]
tests/xgboost/test_xgboost_model_export.py::test_model_log SKIPPED (use `--large` or `--large-only` to run this test) [ 65%]
This looks a bit too verbose, but this clarifies which tests were skipped.
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
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Signed-off-by: harupy hkawamura0130@gmail.com
What changes are proposed in this pull request?
Fix
pytestoptions to show skipped tests and how to unskip them for the first-time contributors or new team members who are not familiar with options for running tests:How is this patch tested?
Existing tests
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