v0.12.0 (2026-06-05)

What’s new

Added

• Spark Declarative Pipeline Orchestrator
• PipelineNode.sources - a named dict of data sources replacing the single source field. All existing source: YAML is automatically migrated to sources: {df: ...}.
• null_equals_null option for cdc_merge_options [#586]

Updated

• All laktory-injected Spark conf / pipeline configuration keys now use laktory. namespace prefix (laktory.executor, laktory.requirements, laktory.config_filepath, laktory.pipeline_name)
• PipelineNode.execute() now reads all sources entries before invoking the transformer. Upstream nodes referenced via {nodes.X} SQL placeholders are pre-loaded here rather than inside DataFrameExpr
• Dtype class now supports time_unit and time_zone properties.
• Databricks Terraform provider updated to 1.117.0

Fixed

• Table creation when cdc_merge_options with SCD_TYPE 2 is used
• TableDataSink supports "ORC" and "AVRO" formats

Breaking changes

• Renamed Databricks Pipelines orchestrator to Lakehouse Declarative Pipeline
• Refactored Lakehouse Declarative Pipeline script to use latest API (apply_changes -> create_auto_cdc_flow)
• CLI --dbks-job / --dbks-pipeline flags replaced by --databricks-job / --databricks-pipeline
• PipelineNode.source field removed - use PipelineNode.sources (dict) instead. YAML using source: is automatically migrated; Python code accessing .source directly must be updated.
• Renamed data sink databricks_quality_monitor to databricks_data_profiling_config
• Removed pipeline databricks_quality_monitors_enabled flag (now auto-detected)
• Pipeline Lakeflow Job orchestrator data profiling configuration task is no longer active by default. Needs to set data_profiling_config_task to True
• QualityMonitor resource renamed to DataQualityMonitor to be aligned with Databricks latest naming convention
• Lakeflow Job data profiling task key renamed from post-execute to data-profiling-configs

Full Changelog