Free some disk space in python job

[harupy]

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

Fix the following error in tests/tracking/test_mlflow_artifacts.py::test_mlflow_artifacts_example:

https://github.com/mlflow/mlflow/actions/runs/5651381939/job/15309401913?pr=9153#step:10:3534

artifacts-server_1     | 2023/07/25 01:40:13 ERROR mlflow.server: Exception on /api/2.0/mlflow-artifacts/artifacts/experiments/0/0c10998073be4e8b936d401bad8abf6b/artifacts/a.txt [PUT]
artifacts-server_1     | Traceback (most recent call last):
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/boto3/s3/transfer.py", line 292, in upload_file
artifacts-server_1     |     future.result()
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/s3transfer/futures.py", line 103, in result
artifacts-server_1     |     return self._coordinator.result()
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/s3transfer/futures.py", line 266, in result
artifacts-server_1     |     raise self._exception
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/s3transfer/tasks.py", line 139, in __call__
artifacts-server_1     |     return self._execute_main(kwargs)
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/s3transfer/tasks.py", line 162, in _execute_main
artifacts-server_1     |     return_value = self._main(**kwargs)
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/s3transfer/upload.py", line 758, in _main
artifacts-server_1     |     client.put_object(Bucket=bucket, Key=key, Body=body, **extra_args)
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/botocore/client.py", line 534, in _api_call
artifacts-server_1     |     return self._make_api_call(operation_name, kwargs)
artifacts-server_1     |   File "/usr/local/lib/python3.8/site-packages/botocore/client.py", line 976, in _make_api_call
artifacts-server_1     |     raise error_class(parsed_response, operation_name)
artifacts-server_1     | botocore.exceptions.ClientError: An error occurred (XMinioStorageFull) when calling the PutObject operation: Storage backend has reached its minimum free drive threshold. Please delete a few objects to proceed.

How is this patch tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests (describe details, including test results, below)

Does this PR change the documentation?

• No. You can skip the rest of this section.
• Yes. Make sure the changed pages / sections render correctly in the documentation preview.

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

(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 logging
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/gateway: AI Gateway service, Gateway client APIs, third-party Gateway integrations
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

Interface

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

Language

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

Integrations

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

• rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
• rn/documentation - A user-facing documentation change worth mentioning in the release notes

[mlflow-automation]

Documentation preview for b725c7c will be available here when this CircleCI job completes successfully.

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• The preview is updated when a new commit is pushed to this PR.
• This comment was created by https://github.com/mlflow/mlflow/actions/runs/5651762441.

[harupy]

Change to always run docker-compose logs

[dbczumar]

LGTM!