Quick Tip : Using NotebookUtils To Get Fabric Lakehouse Properties

Notebookutils in Fabric now has getWithProperties() method to get the properties of a lakehouse. Earlier the get() method only returned abfs path and not the SQL endpoint.

By default it returns the JSON:

//sample output 

{'id': '<>',
 'type': 'Lakehouse',
 'displayName': '<name>',
 'description': '',
 'workspaceId': '<>',
 'properties': {'oneLakeTablesPath': 'https://onelake.dfs.fabric.microsoft.com/<>/<>/Tables',
  'oneLakeFilesPath': 'https://onelake.dfs.fabric.microsoft.com/<>/<>/Files',
  'sqlEndpointProperties': {'connectionString': '<>.datawarehouse.fabric.microsoft.com', 'id': '<>', 'provisioningStatus': 'Success'},
  'abfsPath': 'abfss://<>@onelake.dfs.fabric.microsoft.com/<>'}}

Below script normalizes the JSON to a pandas df:

import pandas as pd
import sempy.fabric as fabric

def lakehouse_properties(lakehouse_name, workspace=None):
    """
    Sandeep Pawar | fabric.guru
    Returns properties of a lakehouse as a pandas df.
    Default workspace is used if workspace is None.

    """
    workspace = fabric.resolve_workspace_id(workspace) or fabric.get_workspace_id()

    # Get the Lakehouse data
    data = notebookutils.lakehouse.getWithProperties(name=lakehouse_name, workspaceId=workspace)

    flattened_data = {
        'lakehouse_id': data['id'],
        'type': data['type'],
        'lakehouse_name': data['displayName'],
        'description': data['description'],
        'workspaceId': data['workspaceId'],
        'oneLakeTablesPath': data['properties']['oneLakeTablesPath'],
        'oneLakeFilesPath': data['properties']['oneLakeFilesPath'],
        'abfsPath': data['properties']['abfsPath'],
        'sqlep_connectionString': data['properties']['sqlEndpointProperties']['connectionString'],
        'sqlep_id': data['properties']['sqlEndpointProperties']['id'],
        'sqlep_provisioningStatus': data['properties']['sqlEndpointProperties']['provisioningStatus']
    }

    df = pd.DataFrame([flattened_data])

    # Column order
    column_order = [
        'lakehouse_id', 'type', 'lakehouse_name', 'description', 'workspaceId',
        'oneLakeTablesPath', 'oneLakeFilesPath',
        'sqlep_connectionString',
        'sqlep_id',
        'sqlep_provisioningStatus',
        'abfsPath'
    ]
    df = df[column_order]

    return df

lakehouse_properties("<lakehouse_name>")

To get properties of all lakehouses in a workspace:

df = pd.concat([lakehouse_properties(lh) for lh in fabric.list_items(type="Lakehouse")['Display Name']])