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.

semantic-link-labs 0.6.0

Improvements in 0.6.0

• New functions:
  • sempy_labs
    • deploy_semantic_model
    • delete_custom_pool
    • list_capacities Semantic Link has this function as well but here in Semantic Link Labs the output dataframe contains an additional column showing the admin accounts for the capacity.
  • sempy_labs.directlake
    • add_table_to_direct_lake_semantic_model
  • sempy_labs.tom
    • is_calculated_table
    • update_measure
    • update_column
    • update_role
    • update_calculation_item
• Updated functions
  • The run_model_bpa and model_bpa_rules functions have been updated to use TOM directly (instead of dataframes as done previously). Using your own rules or modifying the existing rules is simpler now as the rules rely on basic TOM plus the functions contained within the Semantic Link Labs library. Simply follow the example of the model_bpa_rules code and use the returned dataframe as the 'rules' parameter for the run_model_bpa function.
  • The get_semantic_model_bim has been updated to contain a new parameter 'lakehouse_workspace' which should be used in case you want to save the .bim file to the lakehouse attached to your notebook and that lakehouse resides in a different workspace from the semantic model. This function has also been updated to leverage the 'lro_wait' parameter in Semantic Link for easily resolving long running operations (#26).

Bug fixes in 0.6.0

• Fixed bug in assign_workspace_to_capacity.
• Fixed bug in get_measure_dependencies.
• Various other bug fixes and code improvements.

Renamed functions in 0.6.0

• Renamed the 'hybrid_tables' function to all_hybrid_tables to align with other 'all_'* functions.
• Renamed the 'date_tables' function to all_date_tables to align with other 'all_'* functions.

Notebooks

• Tabular Object Model
  • Added examples for renaming objects (tables, columns)

semantic-link-labs 0.5.0

Improvements

• New functions:
  • sempy_labs
    • list_workspace_role_assignments
    • list_workspace_users
    • assign_workspace_to_dataflow_storage
    • update_workspace_user
    • delete_user_from_workspace
    • add_user_to_workspace
    • get_spark_settings
    • update_spark_settings
    • assign_workspace_to_capacity
    • unassign_workspace_from_capacity
    • create_custom_pool
    • update_custom_pool
    • list_custom_pools
  • sempy_labs.tom
    • update_m_partition
    • set_sort_by_column
    • remove_sort_by_column
• Updated functions
  • sempy_labs.report
    • report_rebind The report parameter can now be either a str or a List[str].
    • report_rebind_all The report_workspace parameter can now be either a str or a List[str].

Bug fixes

• Fixed boolean type bug in the logic of several functions including get_measure_dependencies.
• Fixed bug in the all_calculated_tables function.

semantic-link-labs 0.4.2

The initial release of semantic-link-labs is now available!

• Everything in the fabric_cat_tools library has been moved to the semantic-link-labs library. Please use this library going forward as the fabric_cat_tools library is being decommissioned in favor of this library.
• Semantic-link-labs is now available on PyPI for easy installation.
• Documentation for all functions is available here.

New functions

• The following new functions have been made available for managing Query Scale Out operations.
  • qso_sync
  • qso_sync_status
  • disable_qso
  • set_qso
  • list_qso_settings
  • set_semantic_model_storage_format
  • set_workspace_default_storage_format

Updated functions

• refresh_semantic_model now contains the 'apply_refresh_policy' parameter.