You can utilise Semantic Link Labs to repoint to new lakehouse.
import sempy.fabric as fabric
from sempy_labs.directlake._get_shared_expression import get_shared_expression
from sempy_labs._helper_functions import (
resolve_lakehouse_name,
)
from sempy_labs.tom import connect_semantic_model
from typing import Optional
import sempy_labs._icons as icons
def update_direct_lake_model_lakehouse_connection(
dataset: str,
workspace: Optional[str] = None,
lakehouse: Optional[str] = None,
lakehouse_workspace: Optional[str] = None,
😞
"""
Remaps a Direct Lake semantic model's SQL Endpoint connection to a new lakehouse.
Parameters
----------
dataset : str
Name of the semantic model.
workspace : str, default=None
The Fabric workspace name in which the semantic model exists.
Defaults to None which resolves to the workspace of the attached lakehouse
or if no lakehouse attached, resolves to the workspace of the notebook.
lakehouse : str, default=None
The Fabric lakehouse used by the Direct Lake semantic model.
Defaults to None which resolves to the lakehouse attached to the notebook.
lakehouse_workspace : str, default=None
The Fabric workspace used by the lakehouse.
Defaults to None which resolves to the workspace of the attached lakehouse
or if no lakehouse attached, resolves to the workspace of the notebook.
Returns
-------
"""
workspace = fabric.resolve_workspace_name(workspace)
if lakehouse_workspace is None:
lakehouse_workspace = workspace
if lakehouse is None:
lakehouse_id = fabric.get_lakehouse_id()
lakehouse = resolve_lakehouse_name(lakehouse_id, lakehouse_workspace)
# Check if lakehouse is valid
dfI = fabric.list_items(workspace=lakehouse_workspace, type="Lakehouse")
dfI_filt = dfI[(dfI["Display Name"] == lakehouse)]
if len(dfI_filt) == 0:
raise ValueError(
f"{icons.red_dot} The '{lakehouse}' lakehouse does not exist within the '{lakehouse_workspace}' workspace. "
f"Therefore it cannot be used to support the '{dataset}' semantic model within the '{workspace}' workspace."
)
dfP = fabric.list_partitions(dataset=dataset, workspace=workspace)
dfP_filt = dfP[dfP["Mode"] == "DirectLake"]
if len(dfP_filt) == 0:
raise ValueError(
f"{icons.red_dot} The '{dataset}' semantic model is not in Direct Lake. This function is only applicable to Direct Lake semantic models."
)
else:
with connect_semantic_model(
dataset=dataset, readonly=False, workspace=workspace
) as tom:
shEx = get_shared_expression(lakehouse, lakehouse_workspace)
try:
tom.model.Expressions["DatabaseQuery"].Expression = shEx
print(
f"{icons.green_dot} The expression in the '{dataset}' semantic model has been updated to point to the '{lakehouse}' lakehouse in the '{lakehouse_workspace}' workspace."
)
except Exception as e:
raise ValueError(
f"{icons.red_dot} The expression in the '{dataset}' semantic model was not updated."
) from e
Try the above code. Simalarly you can repoint the reports
Regards,
Srisakthi
If this helps, please mark is Accept As Solution
