> ## Documentation Index > Fetch the complete documentation index at: https://docs.open-metadata.org/llms.txt > Use this file to discover all available pages before exploring further. # Getting Started with Data Quality as Code > Install the OpenMetadata Python SDK and configure authentication # Getting Started with Data Quality as Code This guide will help you install the OpenMetadata Python SDK and configure authentication to start running data quality tests programmatically. ## Prerequisites Before you begin, ensure you have: * Python 3.10 or higher installed * pip package manager * Access to an OpenMetadata instance (version 1.11.0 or later) * A JWT token for authentication (see [Authentication](#authentication) below) ## Installation Install the `openmetadata-ingestion` package with the necessary extras for your use case: ### Basic Installation ```bash theme={null} pip install "openmetadata-ingestion>=1.12.0.0" ``` ### Installation with Database Connectors Install additional dependencies based on the databases you'll be testing: ```bash theme={null} # For PostgreSQL pip install "openmetadata-ingestion[postgres]>=1.12.0.0" # For MySQL pip install "openmetadata-ingestion[mysql]>=1.12.0.0" # For BigQuery pip install "openmetadata-ingestion[bigquery]>=1.12.0.0" # For multiple databases pip install "openmetadata-ingestion[postgres,mysql,bigquery]>=1.12.0.0" ``` ### Installation with DataFrame Support If you plan to use DataFrame validation features: ```bash theme={null} pip install "openmetadata-ingestion[pandas]>=1.12.0.0" ``` ### Installation with Multiple Features Combine multiple extras as needed: ```bash theme={null} # For DataFrame validation with Postgres support pip install "openmetadata-ingestion[pandas,postgres]>=1.12.0.0" # For comprehensive ETL support pip install "openmetadata-ingestion[pandas,postgres,pyarrow]>=1.12.0.0" ``` ## Authentication Data Quality as Code requires authentication with your OpenMetadata instance. The SDK supports JWT token authentication. ### Getting a JWT Token You can obtain a JWT token in two ways: #### Option 1: Using an Existing Bot Token OpenMetadata provides pre-configured bots like the `ingestion-bot`: 1. Log in to your OpenMetadata instance 2. Navigate to **Settings > Bots** 3. Find the **ingestion-bot** (or create a new bot) 4. Copy the JWT token Obtain Bot JWT Token #### Option 2: Creating a Custom Bot For production use, create a dedicated bot with specific permissions: 1. Go to **Settings > Bots** 2. Click **Add Bot** 3. Provide a name and description 4. Assign appropriate roles (typically `DefaultBotPolicy` and `Ingestion Bot Policy`) 5. Copy the generated JWT token ### Configuring the SDK Once you have a JWT token, configure the SDK in your Python code: ```python theme={null} from metadata.sdk import configure configure( host="http://localhost:8585/api", # Your OpenMetadata API URL jwt_token="your-jwt-token-here" ) ``` #### Using Environment Variables For better security, let `configure` pick them up from environment variables: ```python theme={null} from metadata.sdk import configure configure() ``` Set the environment variable before running your script: ```bash theme={null} export OPENMETADATA_HOST="http://localhost:8585/api" export OPENMETADATA_JWT_TOKEN="your-jwt-token-here" python your_script.py ``` #### Configuration Parameters The `configure()` function accepts the following parameters: | Parameter | Type | Required | Description | Environment Variable | | ----------- | ----- | -------- | -------------------------------------------------------- | ------------------------ | | `host` | `str` | No | OpenMetadata API URL (e.g., `http://localhost:8585/api`) | `OPENMETADATA_HOST` | | `jwt_token` | `str` | No | JWT authentication token | `OPENMETADATA_JWT_TOKEN` | ## Verify Installation Create a simple test to verify your setup: ```python theme={null} from metadata.sdk import configure from metadata.sdk.data_quality import TestRunner # Configure SDK configure( host="http://localhost:8585/api", jwt_token="your-jwt-token-here" ) # Test connection by creating a runner try: runner = TestRunner.for_table("your_service.database.schema.table") print("✓ SDK configured successfully!") except Exception as e: print(f"✗ Configuration failed: {e}") ``` Replace `"your_service.database.schema.table"` with the fully qualified name of an actual table in your OpenMetadata instance. ## Your First Data Quality Test Now that you're set up, let's run your first data quality test: ```python theme={null} from metadata.sdk import configure from metadata.sdk.data_quality import TestRunner, TableRowCountToBeBetween # Configure SDK configure( host="http://localhost:8585/api", jwt_token="your-jwt-token-here" ) # Create a test runner for a specific table runner = TestRunner.for_table("MySQL.ecommerce.public.customers") # Add a test to verify row count is within expected range runner.add_test( TableRowCountToBeBetween(min_count=1000, max_count=100000) ) # Run the tests results = runner.run() # Print results for result in results: test_case = result.testCase test_result = result.testCaseResult print(f"Test: {test_case.name.root}") print(f"Status: {test_result.testCaseStatus}") print(f"Result: {test_result.result}") ``` ## Common Installation Issues ### Connection Timeout If you experience connection timeouts, verify: 1. OpenMetadata instance is running and accessible 2. API URL is correct (should end with `/api`) 3. Network connectivity between your script and OpenMetadata 4. Firewall rules allow the connection ### Import Errors If you encounter import errors: ```python theme={null} ModuleNotFoundError: No module named 'metadata' ``` Verify the package is installed correctly: ```bash theme={null} pip list | grep openmetadata ``` If not listed, reinstall: ```bash theme={null} pip install --upgrade "openmetadata-ingestion>=1.12.0.0" ``` ## Next Steps Now that you have the SDK installed and configured: * Learn how to [run table-level tests](/v1.12.x/how-to-guides/data-quality-observability/quality/data-quality-as-code/test-runner) using the TestRunner API * Explore [DataFrame validation](/v1.12.x/how-to-guides/data-quality-observability/quality/data-quality-as-code/dataframe-validation) for ETL pipelines * Review the [complete test definitions reference](/v1.12.x/how-to-guides/data-quality-observability/quality/data-quality-as-code/test-definitions) ## Additional Resources * [OpenMetadata Python SDK Documentation](https://docs.open-metadata.org/latest/sdk/python) * [Data Quality Overview](/v1.12.x/how-to-guides/data-quality-observability/quality) * [Authentication & Authorization](https://docs.open-metadata.org/latest/deployment/security) * [Examples and Tutorials](https://github.com/open-metadata/OpenMetadata/tree/main/examples/python-sdk/data-quality/README.md)