Prevent clean_up_envs from deleting local development environment

[harupy]

🛠 DevTools 🛠

Install mlflow from this PR

pip install git+https://github.com/mlflow/mlflow.git@refs/pull/11249/merge

Checkout with GitHub CLI

gh pr checkout 11249

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

clean_up_envs accidentally removed my local dev environment. This PR makes a change to prevent that.

How is this PR tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests

Does this PR require documentation update?

• No. You can skip the rest of this section.
• Yes. I've updated:
  • Examples
  • API references
  • Instructions

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.

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/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
• 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/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/breaking-change - The PR will be mentioned in the "Breaking Changes" 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

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[WeichenXu123]

LGTM, Good improvement for testing!

[harupy]

/ai I want some examples strings that matches this regular expression

[mlflow]

@harupy

This regex matches any string that starts with "mlflow-" followed by at least 32 alphanumeric characters (i.e., letters a-z, A-Z, or numbers 0-9). Here are a few example strings that would match:

1. mlflow-12345678901234567890123456789012
2. mlflow-abcdefghijklmnopqrstuvwxzyz123456
3. mlflowabcdefghijklmnopqrstuvwxyzabcdefg
4. mlflow-09876543210987654321098765432100

Please note that any extra characters after the initial 32 alphanumeric characters will still match.

Click here to see the usage data

{
  "prompt_tokens": 62,
  "completion_tokens": 129,
  "total_tokens": 191,
  "estimated_cost_in_usd": 0.0096
}