added functions for kqldashboard apis

src/sempy_labs/__init__.py

@@ -1,3 +1,9 @@
+from sempy_labs._kql_dashboards import (
+    list_kql_dashboards,
+    create_kql_dashboard,
+    delete_kql_dashboard,
+    create_workspace_monitoring_dashboard,
+)
 from sempy_labs._graphQL import (
     list_graphql_apis,
     create_graphql_api,
@@ -511,4 +517,8 @@
     "delta_analyzer",
     # "dax_perf_test",
     # "dax_perf_test_bulk",
+    "list_kql_dashboards",
+    "create_kql_dashboard",
+    "delete_kql_dashboard",
+    "create_workspace_monitoring_dashboard",
 ]

src/sempy_labs/_kql_dashboards.py

@@ -0,0 +1,195 @@
+import sempy.fabric as fabric
+import pandas as pd
+import sempy_labs._icons as icons
+from typing import Optional
+from sempy_labs._helper_functions import (
+    resolve_workspace_name_and_id,
+    _base_api,
+    _create_dataframe,
+    _conv_b64,
+    generate_guid,
+)
+from uuid import UUID
+import requests
+import json
+
+
+def list_kql_dashboards(workspace: Optional[str | UUID] = None) -> pd.DataFrame:
+    """
+    Shows the KQL dashboards within a workspace.
+
+    This is a wrapper function for the following API: `Items - List KQL Dashboards <https://learn.microsoft.com/rest/api/fabric/kqldatabase/items/list-kql-dashboards>`_.
+
+    Parameters
+    ----------
+    workspace : str | uuid.UUID, default=None
+        The Fabric workspace name or ID.
+        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
+    -------
+    pandas.DataFrame
+        A pandas dataframe showing the KQL dashboards within a workspace.
+    """
+
+    columns = {
+        "KQL Dashboard Name": "string",
+        "KQL Dashboard Id": "string",
+        "Description": "string",
+    }
+    df = _create_dataframe(columns=columns)
+
+    (workspace_name, workspace_id) = resolve_workspace_name_and_id(workspace)
+
+    responses = _base_api(
+        request=f"v1/workspaces/{workspace_id}/kqlDashboards", uses_pagination=True
+    )
+
+    for r in responses:
+        for v in r.get("value", []):
+            new_data = {
+                "KQL Dashboard Name": v.get("displayName"),
+                "KQL Dashboard Id": v.get("id"),
+                "Description": v.get("description"),
+            }
+            df = pd.concat([df, pd.DataFrame(new_data, index=[0])], ignore_index=True)
+
+    return df
+
+
+def create_kql_dashboard(
+    name: str,
+    content: Optional[str] = None,
+    description: Optional[str] = None,
+    workspace: Optional[str | UUID] = None,
+):
+    """
+    Creates a KQL dashboard.
+
+    This is a wrapper function for the following API: `Items - Create KQL Dashboard <https://learn.microsoft.com/rest/api/fabric/kqldatabase/items/create-kql-dashboard>`_.
+
+    Parameters
+    ----------
+    name: str
+        Name of the KQL dashboard.
+    content: Optional[dict], default=None
+        The RealTimeDashboard.json content.
+    description : str, default=None
+        A description of the environment.
+    workspace : str | uuid.UUID, default=None
+        The Fabric workspace name or ID.
+        Defaults to None which resolves to the workspace of the attached lakehouse
+        or if no lakehouse attached, resolves to the workspace of the notebook.
+    """
+
+    (workspace_name, workspace_id) = resolve_workspace_name_and_id(workspace)
+
+    payload = {"displayName": name}
+
+    if description:
+        payload["description"] = description
+
+    if content:
+        payload["definition"] = {
+            "format": None,
+            "parts": [
+                {
+                    "path": "RealTimeDashboard.json",
+                    "payload": _conv_b64(content),
+                    "payloadType": "InlineBase64",
+                },
+            ],
+        }
+
+    _base_api(
+        request=f"v1/workspaces/{workspace_id}/kqlDashboards",
+        method="post",
+        payload=payload,
+        status_codes=201,
+    )
+
+    print(
+        f"{icons.green_dot} The '{name}' KQL dashboard has been created within the '{workspace_name}' workspace."
+    )
+
+
+def create_workspace_monitoring_dashboard(
+    name: str = "Fabric Workspace Monitoring Dashboard",
+    workspace: Optional[str | UUID] = None,
+):
+    """
+    Creates a workspace monitoring dashboard based on `this <https://github.com/microsoft/fabric-toolbox/tree/main/monitoring/workspace-monitoring-dashboards>`_ template.
+
+    This function requires the workspace to have workspace monitoring enabled.
+
+    Parameters
+    ----------
+    name : str, default="Fabric Workspace Monitoring Dashboard"
+        The name of the workspace monitoring dashboard.
+    workspace : str | uuid.UUID, default=None
+        The Fabric workspace name or ID.
+        Defaults to None which resolves to the workspace of the attached lakehouse
+        or if no lakehouse attached, resolves to the workspace of the notebook.
+    """
+    from sempy_labs._kql_databases import list_kql_databases
+
+    (workspace_name, workspace_id) = resolve_workspace_name_and_id(workspace)
+    db_name = "Monitoring KQL database"
+
+    url = "https://raw.githubusercontent.com/microsoft/fabric-toolbox/refs/heads/main/monitoring/workspace-monitoring-dashboards/Fabric%20Workspace%20Monitoring%20Dashboard.json"
+    response = requests.get(url)
+    content = json.loads(response.content)
+
+    # Resolve the cluster URI and database ID
+    dfK = list_kql_databases(workspace=workspace)
+    dfK_filt = dfK[dfK["KQL Database Name"] == db_name]
+    if dfK_filt.empty:
+        raise ValueError(
+            f"{icons.red_dot} Workspace monitoring is not set up for the '{workspace_name}' workspace."
+        )
+    cluster_uri = dfK_filt["Query Service URI"].iloc[0]
+    database_id = dfK_filt["KQL Database Id"].iloc[0]
+
+    content["dataSources"] = [
+        {
+            "kind": "kusto-trident",
+            "scopeId": "kusto-trident",
+            "clusterUri": cluster_uri,
+            "database": database_id,
+            "name": db_name,
+            "id": generate_guid(),
+            "workspace": workspace_id,
+        }
+    ]
+
+    create_kql_dashboard(name=name, content=content, workspace=workspace)
+
+
+def delete_kql_dashboard(
+    kql_dashboard: str | UUID, workspace: Optional[str | UUID] = None
+):
+    """
+    Deletes a KQL database.
+
+    This is a wrapper function for the following API: `Items - Delete KQL Dashboard <https://learn.microsoft.com/rest/api/fabric/kqldatabase/items/delete-kql-dashboard>`_.
+
+    Parameters
+    ----------
+    kql_dashboard: str | uuid.UUID
+        Name or ID of the KQL dashboard.
+    workspace : str | uuid.UUID, default=None
+        The Fabric workspace name or ID.
+        Defaults to None which resolves to the workspace of the attached lakehouse
+        or if no lakehouse attached, resolves to the workspace of the notebook.
+    """
+
+    (workspace_name, workspace_id) = resolve_workspace_name_and_id(workspace)
+    item_id = fabric.resolve_item_id(
+        item_name=kql_dashboard, type="KQLDashboard", workspace=workspace_id
+    )
+
+    fabric.delete_item(item_id=item_id, workspace=workspace)
+    print(
+        f"{icons.green_dot} The '{kql_dashboard}' KQL database within the '{workspace_name}' workspace has been deleted."
+    )