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%pip install semantic-link-labs
import sempy_labs as labs import sempy_labs.report as rep
labs.run_model_bpa_bulk(workspace='Workspace 1')
labs.run_model_bpa_bulk(workspace=['Workspace 1', 'Workspace 2'])
labs.run_model_bpa_bulk(workspace=None)
labs.create_model_bpa_semantic_model()
rep.create_model_bpa_report()
Going forward, you just need to run the 'run_model_bpa_bulk' function which will append BPA results to the 'modelbparesults' delta table in your lakehouse. Since the 'BPAModel' semantic model is in Direct Lake mode, the data will appear in the semantic model and report automatically without any need for processing the semantic model.
https%3A%2F%2Fgithub.com%2Fmicrosoft%2Fsemantic-link-labs%2Fblob%2Fmain%2Fnotebooks%2FBest%2520Practice%2520Analyzer%2520Report.ipynb
Thanks for sharing the code. This is super helpful. I get the error below when running the
ArrowInvalid: ('Casting from timestamp[us] to timestamp[ms] would lose data: 1747114480485629', 'Conversion failed for column Timestamp with type datetime64[us]')