%pip install semantic-link-labs

import sempy_labs as labs
from sempy_labs import migration, directlake
import sempy_labs.report as rep

dataset_name = '' #Enter the import/DQ semantic model name
workspace_name = None #Enter the workspace of the import/DQ semantic model. It set to none it will use the current workspace.
new_dataset_name = '' #Enter the new Direct Lake semantic model name
new_dataset_workspace_name = None #Enter the workspace where the Direct Lake model will be created. If set to None it will use the current workspace.
lakehouse_name = None #Enter the lakehouse to be used for the Direct Lake model. If set to None it will use the lakehouse attached to the notebook.
lakehouse_workspace_name = None #Enter the lakehouse workspace. If set to None it will use the new_dataset_workspace_name.

migration.create_pqt_file(dataset = dataset_name, workspace = workspace_name)

import time
labs.create_blank_semantic_model(dataset = new_dataset_name, workspace = new_dataset_workspace_name, overwrite=False)

migration.migrate_calc_tables_to_lakehouse(
    dataset=dataset_name,
    new_dataset=new_dataset_name,
    workspace=workspace_name,
    new_dataset_workspace=new_dataset_workspace_name,
    lakehouse=lakehouse_name,
    lakehouse_workspace=lakehouse_workspace_name
)
migration.migrate_tables_columns_to_semantic_model(
    dataset=dataset_name,
    new_dataset=new_dataset_name,
    workspace=workspace_name,
    new_dataset_workspace=new_dataset_workspace_name,
    lakehouse=lakehouse_name,
    lakehouse_workspace=lakehouse_workspace_name
)
migration.migrate_calc_tables_to_semantic_model(
    dataset=dataset_name,
    new_dataset=new_dataset_name,
    workspace=workspace_name,
    new_dataset_workspace=new_dataset_workspace_name,
    lakehouse=lakehouse_name,
    lakehouse_workspace=lakehouse_workspace_name
)
migration.migrate_model_objects_to_semantic_model(
    dataset=dataset_name,
    new_dataset=new_dataset_name,
    workspace=workspace_name,
    new_dataset_workspace=new_dataset_workspace_name
)
migration.migrate_field_parameters(
    dataset=dataset_name,
    new_dataset=new_dataset_name,
    workspace=workspace_name,
    new_dataset_workspace=new_dataset_workspace_name
)
time.sleep(2)
labs.refresh_semantic_model(dataset=new_dataset_name, workspace=new_dataset_workspace_name)
migration.refresh_calc_tables(dataset=new_dataset_name, workspace=new_dataset_workspace_name)
labs.refresh_semantic_model(dataset=new_dataset_name, workspace=new_dataset_workspace_name)

migration.migration_validation(
    dataset=dataset_name,
    new_dataset=new_dataset_name, 
    workspace=workspace_name, 
    new_dataset_workspace=new_dataset_workspace_name
)

rep.report_rebind_all(
    dataset=dataset_name,
    dataset_workspace=workspace_name,
    new_dataset=new_dataset_name,
    new_dataset_workpace=new_dataset_workspace_name,
    report_workspace=None
)

report_name = '' # Enter report name which you want to rebind to the new Direct Lake model

rep.report_rebind(
    report=report_name,
    dataset=new_dataset_name,
    report_workspace=workspace_name,
    dataset_workspace=new_dataset_workspace_name)

dfT, dfC, dfR = directlake.show_unsupported_direct_lake_objects(dataset = dataset_name, workspace = workspace_name)

print('Calculated Tables are not supported...')
display(dfT)
print("Learn more about Direct Lake limitations here: https://learn.microsoft.com/power-bi/enterprise/directlake-overview#known-issues-and-limitations")
print('Calculated columns are not supported. Columns of binary data type are not supported.')
display(dfC)
print('Columns used for relationship must be of the same data type.')
display(dfR)

directlake.direct_lake_schema_compare(dataset=new_dataset_name, workspace=new_dataset_workspace_name)

directlake.list_direct_lake_model_calc_tables(dataset=new_dataset_name, workspace=new_dataset_workspace_name)