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Add notebook for migrating semantic models and reports between workspaces using Semantic Links #901

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392 changes: 392 additions & 0 deletions notebooks/Migrate Semantic Model&Report.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# **Migrating Semantic Models and Reports between Workspaces**\n",
"\n",
"This notebook uses the native `semantic-link-labs` functions to:\n",
"- Migrate semantic models between workspaces\n",
"- Clone reports between workspaces\n",
"\n",
"**Documentation:**\n",
"- [deploy_semantic_model](https://semantic-link-labs.readthedocs.io/en/stable/sempy_labs.html#sempy_labs.deploy_semantic_model)\n",
"- [clone_report](https://semantic-link-labs.readthedocs.io/en/stable/sempy_labs.report.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Install Semantic Link Labs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%pip install semantic-link-labs --upgrade"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Import libraries"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sempy_labs as labs\n",
"from sempy_labs.report import clone_report\n",
"import sempy.fabric as fabric"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Workspace and Resource Configuration\n",
"\n",
"Define the IDs/names of your source and target workspaces:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Source workspace\n",
"SOURCE_WORKSPACE = \"XXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\" # Can be name or ID\n",
"\n",
"# Target workspace\n",
"TARGET_WORKSPACE = \"XXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\" # Can be name or ID\n",
"\n",
"# Semantic Model (Dataset)\n",
"SOURCE_DATASET_NAME = \"Gold_Semantic\" # Name of the source dataset\n",
"TARGET_DATASET_NAME = \"Gold_Semantic_Migrated\" # Name of the dataset in target\n",
"\n",
"# Report (optional)\n",
"SOURCE_REPORT_NAME = \"Report\" # Name of the report to clone\n",
"TARGET_REPORT_NAME = \"Reporte_Cloned\" # Name of the cloned report"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Migrate Semantic Model\n",
"\n",
"Use `deploy_semantic_model` to copy a semantic model from one workspace to another.\n",
"\n",
"**Main parameters:**\n",
"- `source_dataset`: Name of the source semantic model\n",
"- `source_workspace`: Source workspace (name or ID)\n",
"- `target_dataset`: Name of the new semantic model in target\n",
"- `target_workspace`: Target workspace (name or ID)\n",
"- `refresh_target_dataset`: If True, refreshes the dataset after creating it (default: True)\n",
"- `overwrite`: If True, overwrites the dataset if it already exists (default: False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Option 1: Migrate semantic model WITHOUT overwriting if it already exists\n",
"try:\n",
" labs.deploy_semantic_model(\n",
" source_dataset=SOURCE_DATASET_NAME,\n",
" source_workspace=SOURCE_WORKSPACE,\n",
" target_dataset=TARGET_DATASET_NAME,\n",
" target_workspace=TARGET_WORKSPACE,\n",
" refresh_target_dataset=True, # Refresh after creating\n",
" overwrite=False # Don't overwrite if already exists\n",
" )\n",
" print(f\"✅ Semantic model '{TARGET_DATASET_NAME}' migrated successfully\")\n",
"except Exception as e:\n",
" print(f\"❌ Error migrating semantic model: {str(e)}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Option 2: Migrate semantic model OVERWRITING if it already exists\n",
"try:\n",
" labs.deploy_semantic_model(\n",
" source_dataset=SOURCE_DATASET_NAME,\n",
" source_workspace=SOURCE_WORKSPACE,\n",
" target_dataset=TARGET_DATASET_NAME,\n",
" target_workspace=TARGET_WORKSPACE,\n",
" refresh_target_dataset=True,\n",
" overwrite=True # OVERWRITE if already exists\n",
" )\n",
" print(f\"✅ Semantic model '{TARGET_DATASET_NAME}' migrated/updated successfully\")\n",
"except Exception as e:\n",
" print(f\"❌ Error migrating semantic model: {str(e)}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. Verify Migrated Semantic Model\n",
"\n",
"List the datasets in the target workspace to confirm the migration:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# List datasets in the target workspace\n",
"datasets = fabric.list_datasets(workspace=TARGET_WORKSPACE)\n",
"print(f\"\\nDatasets in target workspace:\")\n",
"print(datasets[['Dataset Name', 'Dataset ID', 'Created Timestamp']])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6. Clone Report (Optional)\n",
"\n",
"Use `clone_report` to clone a report from one workspace to another.\n",
"\n",
"**Main parameters:**\n",
"- `report`: Name of the source report\n",
"- `cloned_report`: Name of the cloned report\n",
"- `workspace`: Workspace where the original report is located\n",
"- `target_workspace`: Target workspace for the cloned report\n",
"- `target_dataset`: Name of the semantic model that the cloned report will use\n",
"- `target_dataset_workspace`: Workspace where the target semantic model is located"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Clone report to the target workspace connecting it to the migrated semantic model\n",
"try:\n",
" clone_report(\n",
" report=SOURCE_REPORT_NAME,\n",
" cloned_report=TARGET_REPORT_NAME,\n",
" workspace=SOURCE_WORKSPACE, # Workspace where the original report is located\n",
" target_workspace=TARGET_WORKSPACE, # Target workspace for the report\n",
" target_dataset=TARGET_DATASET_NAME, # Connect to the migrated semantic model\n",
" target_dataset_workspace=TARGET_WORKSPACE # Workspace of the semantic model\n",
" )\n",
" print(f\"✅ Report '{TARGET_REPORT_NAME}' cloned successfully\")\n",
"except Exception as e:\n",
" print(f\"❌ Error cloning report: {str(e)}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7. Verify Cloned Report"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# List reports in the target workspace\n",
"reports = fabric.list_reports(workspace=TARGET_WORKSPACE)\n",
"print(f\"\\nReports in target workspace:\")\n",
"print(reports[['Name', 'Id']])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 8. Helper Function for Complete Migration\n",
"\n",
"A function that combines semantic model migration and report cloning:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def migrate_complete_solution(\n",
" source_workspace: str,\n",
" target_workspace: str,\n",
" source_dataset: str,\n",
" target_dataset: str,\n",
" source_report: str = None,\n",
" target_report: str = None,\n",
" overwrite_dataset: bool = False,\n",
" refresh_dataset: bool = True\n",
"):\n",
" \"\"\"\n",
" Migrates a semantic model and optionally a report from one workspace to another.\n",
" \n",
" Args:\n",
" source_workspace: Source workspace (name or ID)\n",
" target_workspace: Target workspace (name or ID)\n",
" source_dataset: Name of the source semantic model\n",
" target_dataset: Name of the target semantic model\n",
" source_report: Name of the report to clone (optional)\n",
" target_report: Name of the cloned report (optional)\n",
" overwrite_dataset: If True, overwrites the dataset if it exists\n",
" refresh_dataset: If True, refreshes the dataset after creating it\n",
" \n",
" Returns:\n",
" dict: Operation result\n",
" \"\"\"\n",
" results = {\n",
" 'dataset_migrated': False,\n",
" 'report_cloned': False,\n",
" 'errors': []\n",
" }\n",
" \n",
" # 1. Migrate semantic model\n",
" print(f\"🔄 Migrating semantic model '{source_dataset}'...\")\n",
" try:\n",
" labs.deploy_semantic_model(\n",
" source_dataset=source_dataset,\n",
" source_workspace=source_workspace,\n",
" target_dataset=target_dataset,\n",
" target_workspace=target_workspace,\n",
" refresh_target_dataset=refresh_dataset,\n",
" overwrite=overwrite_dataset\n",
" )\n",
" results['dataset_migrated'] = True\n",
" print(f\"✅ Semantic model migrated: '{target_dataset}'\")\n",
" except Exception as e:\n",
" error_msg = f\"Error migrating semantic model: {str(e)}\"\n",
" results['errors'].append(error_msg)\n",
" print(f\"❌ {error_msg}\")\n",
" return results\n",
" \n",
" # 2. Clone report (if specified)\n",
" if source_report and target_report:\n",
" print(f\"\\n🔄 Cloning report '{source_report}'...\")\n",
" try:\n",
" clone_report(\n",
" report=source_report,\n",
" cloned_report=target_report,\n",
" workspace=source_workspace,\n",
" target_workspace=target_workspace,\n",
" target_dataset=target_dataset,\n",
" target_dataset_workspace=target_workspace\n",
" )\n",
" results['report_cloned'] = True\n",
" print(f\"✅ Report cloned: '{target_report}'\")\n",
" except Exception as e:\n",
" error_msg = f\"Error cloning report: {str(e)}\"\n",
" results['errors'].append(error_msg)\n",
" print(f\"❌ {error_msg}\")\n",
" \n",
" return results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 9. Use the Helper Function"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example: Execute the helper function to migrate both semantic model AND report\n",
"# This will run the complete migration process\n",
"result = migrate_complete_solution(\n",
" source_workspace=SOURCE_WORKSPACE,\n",
" target_workspace=TARGET_WORKSPACE,\n",
" source_dataset=SOURCE_DATASET_NAME,\n",
" target_dataset=TARGET_DATASET_NAME,\n",
" source_report=SOURCE_REPORT_NAME,\n",
" target_report=TARGET_REPORT_NAME,\n",
" overwrite_dataset=False,\n",
" refresh_dataset=True\n",
")\n",
"\n",
"# Display the migration summary\n",
"print(\"\\n\" + \"=\"*50)\n",
"print(\"MIGRATION SUMMARY\")\n",
"print(\"=\"*50)\n",
"print(f\"Dataset migrated: {result['dataset_migrated']}\")\n",
"print(f\"Report cloned: {result['report_cloned']}\")\n",
"if result['errors']:\n",
" print(f\"\\nErrors found:\")\n",
" for error in result['errors']:\n",
" print(f\" - {error}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 10. List Reports Using a Semantic Model\n",
"\n",
"Useful to identify which reports depend on a semantic model:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# List reports that use the source semantic model\n",
"reports_using_dataset = labs.list_reports_using_semantic_model(\n",
" dataset=SOURCE_DATASET_NAME,\n",
" workspace=SOURCE_WORKSPACE\n",
")\n",
"\n",
"print(f\"Reports that use the semantic model '{SOURCE_DATASET_NAME}':\")\n",
"print(reports_using_dataset)"
]
}
],
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"display_name": "Python 3",
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"name": "ipython",
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},
"file_extension": ".py",
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"name": "python",
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"pygments_lexer": "ipython3",
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"nbformat": 4,
"nbformat_minor": 4
}