Databricks SDK for Python v0.132.0 Adds New API Fields
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Databricks SDK for Python v0.132.0 introduces new API fields across its Apps, ML, and Pipelines services. These enhancements provide developers with extended programmatic control over application configurations, machine learning functions, and pipeline responses. Users of the Python SDK can now manage Git sources, custom UDFs, and serverless compute IDs directly through the API. This update streamlines automation and integration for Databricks platform users.
- →Add default_git_source, git_source and source_code_path fields for databricks.sdk.service.apps.App
- →Add auto_deploy and caller_credential_id fields for databricks.sdk.service.apps.GitRepository
- →Add custom_udf field for databricks.sdk.service.ml.Function
- →Add effective_serverless_compute_id field for databricks.sdk.service.pipelines.GetPipelineResponse
Enhancements (4) ›
- Add default_git_source, git_source and source_code_path fields for databricks.sdk.service.apps.App
- Add auto_deploy and caller_credential_id fields for databricks.sdk.service.apps.GitRepository
- Add custom_udf field for databricks.sdk.service.ml.Function
- Add effective_serverless_compute_id field for databricks.sdk.service.pipelines.GetPipelineResponse
Read the original announcement →
https://github.com/databricks/databricks-sdk-py/releases/tag/v0.132.0
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