PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such as Apache Spark, Apache Beam, and more.
When contribution_bounds_already_enforced = True then PipelineDP does no contribution bounding. As a privacy id is not needed. The current validation requires privacy_id_extractor to be None, but there is no problem if privacy id extractor is set up. But it's pretty confusing for users why privacy_id_extractor has to be None. Let's drop this validation for simplicity
When
contribution_bounds_already_enforced = Truethen PipelineDP does no contribution bounding. As a privacy id is not needed. The current validation requiresprivacy_id_extractorto be None, but there is no problem if privacy id extractor is set up. But it's pretty confusing for users whyprivacy_id_extractorhas to beNone. Let's drop this validation for simplicity