FrameTablesBasedOnFallbackReason.py

import sempy.fabric as fabric
import numpy as np
import pandas as pd

def frame_necessary_tables(datasetName):
    
    x = fabric.evaluate_dax(
            datasetName,
            """
            SELECT [TableName] AS [Table Name],[FallbackReason] AS [FallbackReasonID]
            FROM $SYSTEM.TMSCHEMA_DELTA_TABLE_METADATA_STORAGES
            """)
    x

    value_mapping = {
        0: 'No reason for fallback',
        1: 'This table is not framed',
        2: 'This object is a view in the lakehouse',
        3: 'The table does not exist in the lakehouse',
        4: 'Transient error',
        5: 'Using OLS will result in fallback to DQ',
        6: 'Using RLS will result in fallback to DQ'
    }

    # Add new column based on value_mapping
    x['Fallback Reason Detail'] = np.vectorize(value_mapping.get)(x['FallbackReasonID'])

    display(x)
    df = x[x['FallbackReasonID'].isin([1, 4])]

    if df.empty:
            print("No tables in your dataset need framing.")
    else:
        table_names = df['Table Name'].unique()
        my_objects = [{"table": table_name} for table_name in table_names]
        tables_string = ', '.join(table_names)

        # Refresh (frame) necessary tables
        requestID = fabric.refresh_dataset(dataset = datasetName, refresh_type = "full", objects = my_objects)

        while True:
            requestDetails = fabric.get_refresh_execution_details(datasetName,requestID)
            status = requestDetails.status

            # Check if the refresh has completed
            if status == 'Completed':
                break

            time.sleep(3)

        print(f"The following tables have been framed: {tables_string}.")

frame_necessary_tables('') #Enter dataset name