[FR] Add warning / option for overwriting existing file when downloading artifacts that have the same name/path

[samskalicky]

Issues Policy acknowledgement

• [X] I have read and agree to submit bug reports in accordance with the issues policy

Where did you encounter this bug?

Local machine

Willingness to contribute

Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.

MLflow version

• Client: 2.14.1
• Tracking server: 1.x.y

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):Linux Ubuntu 22.04
• Python version: 3.10
• yarn version, if running the dev UI:

Describe the problem

Downloading artifacts using mlflow.artifacts.download_artifact that have the same name or path result in overwriting one another on disk when specifying the same dst_path. It would be helpful to have a warning msg that a file already exists before copying from server and writing to local disk. Or maybe an option to allow overwriting, and error out if it already exists.

Currently it silently overwrites.

Related to https://github.com/mlflow/mlflow/issues/8942 but that involves uploading artifacts, where this issue is about downloading.

Tracking information

REPLACE_ME

Code to reproduce issue

REPLACE_ME

Stack trace

REPLACE_ME

Other info / logs

REPLACE_ME

What component(s) does this bug affect?

• [X] 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

What interface(s) does this bug affect?

• [ ] 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

What language(s) does this bug affect?

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

What integration(s) does this bug affect?

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