more flake fixes (#14)

Co-authored-by: Markus Cozowicz <[email protected]>

pyproject.toml

@@ -37,4 +37,7 @@ Repository = "https://github.com/microsoft/semantic-link-labs.git"
 
 [[tool.mypy.overrides]]
 module = "sempy.*,Microsoft.*,System.*,anytree.*,powerbiclient.*,synapse.ml.services.*"
-ignore_missing_imports = true
+ignore_missing_imports = true
+
+[tool.flake8]
+max-line-length = 200

src/sempy_labs/__init__.py

@@ -52,9 +52,9 @@
     resolve_dataset_name,
     resolve_report_id,
     resolve_report_name,
-    # language_validate
+    #  language_validate
 )
-#from sempy_labs._model_auto_build import model_auto_build
+#  from sempy_labs._model_auto_build import model_auto_build
 from sempy_labs._model_bpa import model_bpa_rules, run_model_bpa
 from sempy_labs._model_dependencies import (
     measure_dependency_tree,

src/sempy_labs/_ai.py

@@ -8,6 +8,7 @@
 from IPython.display import display
 import sempy_labs._icons as icons
 
+
 def optimize_semantic_model(dataset: str, workspace: Optional[str] = None):
 
     from ._model_bpa import run_model_bpa
@@ -92,7 +93,7 @@ def generate_measure_descriptions(
     df = dfM_filt[["Table Name", "Measure Name", "Measure Expression"]]
 
     df["prompt"] = (
-        f"The following is DAX code used by Microsoft Power BI. Please explain this code in simple terms:"
+        "The following is DAX code used by Microsoft Power BI. Please explain this code in simple terms:"
         + df["Measure Expression"]
     )
 
@@ -152,11 +153,11 @@ def generate_aggs(
     #'OrderDateKey': 'GroupBy'
     # }
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
-    if lakehouse_workspace == None:
+    if lakehouse_workspace is None:
         lakehouse_workspace = workspace
         lakehouse_workspace_id = workspace_id
     else:

src/sempy_labs/_clear_cache.py

@@ -20,7 +20,7 @@ def clear_cache(dataset: str, workspace: Optional[str] = None):
         or if no lakehouse attached, resolves to the workspace of the notebook.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 

src/sempy_labs/_dax.py

@@ -27,7 +27,6 @@ def evaluate_dax_impersonation(
         The DAX query.
     user_name : str
         The user name (i.e. [email protected]).
-        Defaults to None which resolves to no user impersonation.
     workspace : str, default=None
         The Fabric workspace name.
         Defaults to None which resolves to the workspace of the attached lakehouse
@@ -49,13 +48,10 @@ def evaluate_dax_impersonation(
 
     dataset_id = resolve_dataset_id(dataset=dataset, workspace=workspace)
 
-    if user_name is None:
-        request_body = {"queries": [{"query": dax_query}]}
-    else:
-        request_body = {
-            "queries": [{"query": dax_query}],
-            "impersonatedUserName": user_name,
-        }
+    request_body = {
+        "queries": [{"query": dax_query}],
+        "impersonatedUserName": user_name
+    }
 
     client = fabric.PowerBIRestClient()
     response = client.post(

src/sempy_labs/_generate_semantic_model.py

@@ -31,7 +31,7 @@ def create_blank_semantic_model(
         or if no lakehouse attached, resolves to the workspace of the notebook.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -178,11 +178,11 @@ def deploy_semantic_model(
 
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
-    if new_dataset_workspace == None:
+    if new_dataset_workspace is None:
         new_dataset_workspace = workspace
 
     if new_dataset is None:
@@ -257,7 +257,7 @@ def get_semantic_model_bim(
 
     if save_to_file_name is not None:
         lakeAttach = lakehouse_attached()
-        if lakeAttach == False:
+        if lakeAttach is False:
             print(
                 f"In order to save the model.bim file, a lakehouse must be attached to the notebook. Please attach a lakehouse to this notebook."
             )

src/sempy_labs/_helper_functions.py

@@ -101,7 +101,7 @@ def resolve_report_id(report: str, workspace: Optional[str] = None):
         The ID of the Power BI report.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -129,7 +129,7 @@ def resolve_report_name(report_id: UUID, workspace: Optional[str] = None):
         The name of the Power BI report.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -159,7 +159,7 @@ def resolve_dataset_id(dataset: str, workspace: Optional[str] = None):
         The ID of the semantic model.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -189,7 +189,7 @@ def resolve_dataset_name(dataset_id: UUID, workspace: Optional[str] = None):
         The name of the semantic model.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -220,7 +220,7 @@ def resolve_lakehouse_name(lakehouse_id: Optional[UUID] = None, workspace: Optio
         The name of the Fabric lakehouse.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -253,7 +253,7 @@ def resolve_lakehouse_id(lakehouse: str, workspace: Optional[str] = None):
         The ID of the Fabric lakehouse.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -283,18 +283,17 @@ def get_direct_lake_sql_endpoint(dataset: str, workspace: Optional[str] = None)
         The ID of SQL Endpoint.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
     dfP = fabric.list_partitions(dataset=dataset, workspace=workspace)
     dfP_filt = dfP[dfP["Mode"] == "DirectLake"]
 
     if len(dfP_filt) == 0:
-        print(
+        raise ValueError(
             f"The '{dataset}' semantic model in the '{workspace}' workspace is not in Direct Lake mode."
         )
-        return
 
     dfE = fabric.list_expressions(dataset=dataset, workspace=workspace)
     dfE_filt = dfE[dfE["Name"] == "DatabaseQuery"]
@@ -502,10 +501,10 @@ def resolve_workspace_name_and_id(workspace: Optional[str] = None) -> Tuple[str,
         The name and ID of the Fabric workspace.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
     else:
         workspace_id = fabric.resolve_workspace_id(workspace)
 
-    return workspace, workspace_id
+    return str(workspace), str(workspace_id)

src/sempy_labs/_list_functions.py

@@ -29,7 +29,7 @@ def get_object_level_security(dataset: str, workspace: Optional[str] = None):
         A pandas dataframe showing the object level security for the semantic model.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -88,7 +88,7 @@ def list_tables(dataset: str, workspace: Optional[str] = None):
         A pandas dataframe showing the semantic model's tables and their properties.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -154,7 +154,7 @@ def list_annotations(dataset: str, workspace: Optional[str] = None):
         A pandas dataframe showing the semantic model's annotations and their properties.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -384,7 +384,7 @@ def list_columns(
         get_direct_lake_lakehouse,
     )
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -1032,10 +1032,10 @@ def create_warehouse(
 
     (workspace, workspace_id) = resolve_workspace_name_and_id(workspace)
 
-    if description == None:
-        request_body = {"displayName": warehouse}
-    else:
-        request_body = {"displayName": warehouse, "description": description}
+    request_body = {"displayName": warehouse}
+
+    if description:
+        request_body["description"] = description
 
     client = fabric.FabricRestClient()
     response = client.post(
@@ -1123,18 +1123,17 @@ def update_item(
 
     itemId = dfI_filt["Id"].iloc[0]
 
-    if description == None:
-        request_body = {"displayName": new_name}
-    else:
-        request_body = {"displayName": new_name, "description": description}
+    request_body = {"displayName": new_name}
+    if description:
+        request_body["description"] = description
 
     client = fabric.FabricRestClient()
     response = client.patch(
         f"/v1/workspaces/{workspace_id}/{itemType}/{itemId}", json=request_body
     )
 
     if response.status_code == 200:
-        if description == None:
+        if description is None:
             print(
                 f"The '{current_name}' {item_type} within the '{workspace}' workspace has been updated to be named '{new_name}'"
             )
@@ -1171,7 +1170,7 @@ def list_relationships(
         A pandas dataframe showing the object level security for the semantic model.
     """
 
-    if workspace == None:
+    if workspace is None:
         workspace_id = fabric.get_workspace_id()
         workspace = fabric.resolve_workspace_name(workspace_id)
 
@@ -1560,7 +1559,7 @@ def list_shortcuts(
 
     (workspace, workspace_id) = resolve_workspace_name_and_id(workspace)
 
-    if lakehouse == None:
+    if lakehouse is None:
         lakehouse_id = fabric.get_lakehouse_id()
         lakehouse = resolve_lakehouse_name(lakehouse_id, workspace)
     else: