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This repository provides a MLflow plugin that allows users to use a database (in particular SQL Server) as the artifact store for MLflow.

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SQL Server plugin for MLflow

This repository provides a MLflow plugin that allows users to use SQL Server as the artifact store for MLflow.

Implementation overview

This repository contains one Python package:

dbstoreplugin: This package includes the DBArtifactRepository class that is used to read and write artifacts from SQL databases. This class sets the attribute is_plugin = True in order to indicate that the class is an MLflow artifact repository plugin. This package also includes the SQLAlchemy database models referenced by DBArtifactRepository. The package's setup.py file defines entrypoints that tell MLflow to automatically associate the mssql URIs with the DBArtifactRepository implementation when the dbstoreplugin library is installed. The entrypoints are configured as follows:

entry_points={
    "mlflow.artifact_repository": [
      "mssql=sqlplugin.store:DBArtifactRepository"
    ]
},

User experience

The proposed plugin structure and development workflow provide the following experience to the end user:

Users can simply install MLflow with the SQL Server plugin via pip install mlflow[sqlserver] and then use MLflow as normal. The SQL Server artifact support will be provided automatically using the previously-described setup entrypoints mechanism.

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This repository provides a MLflow plugin that allows users to use a database (in particular SQL Server) as the artifact store for MLflow.

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