semantic-link-labs 0.7.0

Improvements in 0.7.0

• New functions
  • sempy_labs
    • run_model_bpa_bulk Scan semantic models across workspaces in one go and saves the results to a delta table in your Fabric lakehouse (#78).
    • create_model_bpa_semantic_model Dynamically generates a semantic model to be used in analyzing the model Best Practice Analyzer results.
    • list_reports_using_semantic_model Lists all the reports which feed from a given semantic model - across any workspace.
    • get_notebook_definition Retrieves the Fabric notebook definition.
    • import_notebook_from_web Load any Jupyter Notebook (.ipynb) from the web (i.e. GitHub) into a Fabric workspace.
    • is_default_semantic_semantic_model Easily check if a semantic model is a default semantic model.
    • resolve_dataset_from_report Identifies the semantic model which feeds the report.
    • resolve_item_type Identifies the item type (i.e. Lakehouse, SemanticModel).
    • get_capacity_id
    • get_capacity_name
    • resolve_workspace_capacity
    • resolve_capacity_name
  • sempy_labs.report
    • create_model_bpa_report Dynamically generates a report to be used in analyzing the model Best Practice Analyzer report.
    • get_report_definition Retrieves the Power BI report definition files.
    • update_report_from_reportjson Updates a Power BI report based on a report.json file.
  • sempy_labs.directlake
    • generate_direct_lake_semantic_model Dynamically generates a Direct Lake semantic model based on a user-specified list of lakehouse tables (#55).
    • get_direct_lake_source Obtains the lakehouse and SQL endpoint or Warehouse for any Direct Lake semantic model - even across different workspaces.
• Updated functions
  • sempy_labs
    • run_model_bpa Now has the 'language' parameter for auto-translating the Rule Name, Category and Description into any language. For example: language='it-IT' will translate the rules into Italian.
    • run_model_bpa, run_model_bpa_bulk, vertipaq_analyzer The following properties are now also saved when exporting this data to a delta table: Capacity Name, Capacity Id, Workspace Id, Configured By.
    • clear_cache Updated to check whether the semantic model is the default semantic model and if so yield a useful error as XMLA operations are not allowed against default semantic models.
    • translate_semantic_model Now returns a pandas dataframe showing all translations in the semantic model.
    • save_as_delta_table The 'merge_schema' parameter has been added. Setting this to True enables spark to merge the schema between the dataframe and delta table.
    • refresh_semantic_model added the 'max_parallelism' parameter (#66).
  • sempy_labs.tom
    • Added support for setting Format String Expressions within the add_measure, add_calculation_item, update_measure, update_calculation_item functions.
    • Added the 'object_names' parameter in the add_field_parameter function (#60).
  • sempy_labs.report
    • report_rebind_all Specifying the 'report_workspace' parameter as None will find all reports in all workspaces which use the semantic model and rebind them to the new semantic model.
  • sempy_labs.migration
    • Updated migration functions to support handling special characters in table/column names. Special characters are preserved in the table/column names within the semantic model but are removed in the PQT/lakehouse layer as they are not supported.
    • Updated create_pqt_file function to handle Dataflows Gen2's limitation of 50 tables per Dataflow Gen2. If the .pqt file would have more than 50 tables, multiple .pqt files are created and saved.

Bug fixes in 0.7.0

• Fixed an issue with regard to the default lakehouse and its workspace in the run_model_bpa and veritpaq_analyzer functions (#42, #55).
• Raise an error when the get_lakehouse_tables function is used improperly (#51).
• Fixed a bug in create_field_parameter (#68).
• Fixed long running operation issue and fortified similar functions to optimize long running operation performance (#81).
• Fixed issue (#86) to support pagination for GET API calls in all relevant functions.
• Fixed remove_object function (#83).

Notebooks in 0.7.0

• Added the Best Practice Analyzer Report notebook to provide guidance on how to run the model BPA in bulk and dynamically set up its corresponding model and report for multi-capacity/workspace/model analysis.
• Added new notebook which provides examples for refreshing and cancelling refreshes of semantic models: Semantic Model Refresh

Misc updates in 0.7.0

• Semantic Link 0.7.7 is installed by default.