Azure/azure-sdk-for-python azure-ai-ml

1.5.0 (2023-03-20)

Added support for tags on Compute Resources.
Added support for promoting data asset from a workspace to a registry
Added support for registering named asset from job output or node output by specifying name and version settings.
Added support for data binding on outputs inside dynamic arguments for dsl pipeline
Added support for serverless compute in pipeline, command, automl and sweep job
Added support for job_tier and priority in standalone job
Added support for passing locations via command function and set it to JobResourceConfiguration.locations
Added support for modifying SSH key values after creation on Compute Resources.
Added WorkspaceConnection types s3, snowflake, azure_sql_db, azure_synapse_analytics, azure_my_sql_db, azure_postgres_db
Added WorkspaceConnection auth type access_key for s3
Added DataImport class and DataOperations.import_data.
Added DataOperations.list_materialization_status - list status of data import jobs that create asset versions via asset name.

Fix experiment name wrongly set to 'Default' when schedule existing job.
Error message improvement when a local path fails to match with data asset type.
Error message improvement when an asset does not exist in a registry
Fix an issue when submit spark pipeline job with referring a registered component
Fix an issue that prevented Job.download from downloading the output of a BatchJob

Added dependency on azure-mgmt-resource
Added dependency on azure-mgmt-resourcegraph
Added dependency on opencensus-ext-azure<2.0.0
Update job types to use MFE Dec preview rest objects.
Added classifiers for Python version 3.11.
Added warning for reserved keywords in IO names in pipeline job nodes.
Added telemetry logging for SDK Jupyter Notebook scenarios with opt-out option (see README.md)