Databricks SDK for Python v0.116.0: New APIs and Breaking Changes
sdkaidatabricksengineer
breaking patch
Databricks SDK for Python v0.116.0 introduces new packages for AI Search and Bundle Deployments, along with numerous field additions across services like Catalog, ML, and Vector Search. This release also includes breaking changes with the removal of the `databricks.sdk.service.bundle` package and the associated workspace-level service. These updates primarily affect developers using the Python SDK to interact with Databricks services, offering expanded capabilities while requiring adjustments for bundled application deployments.
- →Remove databricks.sdk.service.bundle package
- →Remove w.bundle workspace-level service
- →Add databricks.sdk.service.aisearch and databricks.sdk.service.bundledeployments packages
- →Add w.ai_search workspace-level service
- →Add w.bundle_deployments workspace-level service
Breaking changes (2) ›
- Remove databricks.sdk.service.bundle package
- Remove w.bundle workspace-level service
Enhancements (30) ›
- Add databricks.sdk.service.aisearch and databricks.sdk.service.bundledeployments packages
- Add w.ai_search workspace-level service
- Add w.bundle_deployments workspace-level service
- Add running_instances field for databricks.sdk.service.apps.ApplicationStatus
- Add custom_max_retention_hours field for databricks.sdk.service.catalog.CatalogInfo
- Add environment_settings field for databricks.sdk.service.catalog.ConnectionInfo
- Add custom_max_retention_hours field for databricks.sdk.service.catalog.CreateCatalog
- Add environment_settings field for databricks.sdk.service.catalog.CreateConnection
- Add custom_max_retention_hours field for databricks.sdk.service.catalog.CreateSchema
- Add custom_max_retention_hours field for databricks.sdk.service.catalog.SchemaInfo
- Add custom_max_retention_hours field for databricks.sdk.service.catalog.UpdateCatalog
- Add environment_settings field for databricks.sdk.service.catalog.UpdateConnection
- Add custom_max_retention_hours field for databricks.sdk.service.catalog.UpdateSchema
- Add stream_source field for databricks.sdk.service.ml.DataSource
- Add ingestion_config field for databricks.sdk.service.ml.KafkaConfig
- Add clustering_columns, enable_auto_clustering and table_properties fields for databricks.sdk.service.pipelines.TableSpecificConfig
- Add branch_id field for databricks.sdk.service.postgres.Branch
- Add catalog_id field for databricks.sdk.service.postgres.Catalog
- Add database_id field for databricks.sdk.service.postgres.Database
- Add endpoint_id field for databricks.sdk.service.postgres.Endpoint
- Add project_id field for databricks.sdk.service.postgres.Project
- Add role_id field for databricks.sdk.service.postgres.Role
- Add synced_table_id field for databricks.sdk.service.postgres.SyncedTable
- Add allowed_databricks_destinations field for databricks.sdk.service.settings.EgressNetworkPolicyNetworkAccessPolicy
- Add facets, query_columns and sort_columns fields for databricks.sdk.service.vectorsearch.QueryVectorIndexRequest
- Add facet_result field for databricks.sdk.service.vectorsearch.QueryVectorIndexResponse
- Add facet_column_count and facet_columns fields for databricks.sdk.service.vectorsearch.ResultManifest
- Add dangerously_force_discard_all field for databricks.sdk.service.workspace.UpdateRepoRequest
- Add accelerated_sync field for databricks.sdk.service.database.SyncedTableSpec
- Add accelerated_sync field for databricks.sdk.service.postgres.SyncedTableSyncedTableSpec
Read the original announcement →
https://github.com/databricks/databricks-sdk-py/releases/tag/v0.116.0