Examples

Examples#

This section provides practical examples of using the DQ Validator module.

Note

Complete working examples are available in the examples/ directory of the repository.

Basic Validation#

See examples/basic_usage.py for array-based record validation.

CEL Expression Validation#

  • examples/cel_usage.py - Column-level CEL expressions with batch validation

  • examples/table_cel_usage.py - Table-level CEL expressions for cross-column validation

  • examples/cel_pandas_dataframe_usage.py - CEL expressions with Pandas DataFrames

DataFrame Validation#

  • examples/pandas_dataframe_usage.py - Pandas DataFrame validation

  • examples/spark_dataframe_usage.py - PySpark DataFrame validation

REST API Integration#

  • examples/auth_provider_usage.py - Authentication examples

  • examples/assets_usage.py - Working with data assets

  • examples/issues_usage.py - Managing data quality issues

  • examples/dimensions_usage.py - Working with DQ dimensions

  • examples/checks_usage.py - Managing DQ checks

Result Consolidation#

See examples/consolidation_usage.py for aggregating validation results.

Complete Workflow#

See examples/dq_workflow_usage.py for an end-to-end data quality workflow.

For detailed API documentation, see the API Reference.