Increase timeout of python job

[harupy]

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

Increase the timeout of the python job. On master, we see several timed-out jobs:

• https://github.com/mlflow/mlflow/actions/runs/5179183809/jobs/9331694464
• https://github.com/mlflow/mlflow/actions/runs/5176810425/jobs/9326106581

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/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

[serena-ruan]

Instead of increasing the timeout time, could we split the job to run against different folders tests in parallel?

[harupy]

Instead of increasing the timeout time, could we split the job to run against different folders tests in parallel?

We could if we had more github action runners. We currently only have 20 (free plan). Splitting a job is not free because we must install dependencies to run tests. If we have one job, we can install them once, but if we have two, we need to install them twice. This diff can be amplified by the number of developers we have.

[serena-ruan]

LGTM!

[mlflow-automation]

Failed to find a documentation preview for 80bd562.

More info

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• This comment was created by https://github.com/mlflow/mlflow/actions/runs/5184103230.