GPT

Pipeline Observability (great Expectations)

import greatexpectations as gx context = gx.getcontext() def validatesilverorders(df) - dict: batch = context.sources.pandasdefault.readdataframe(df) result = batch.validate( expectationsuitename="silverorders.criti

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import great_expectations as gx

context = gx.get_context()

def validate_silver_orders(df) -> dict:
 batch = context.sources.pandas_default.read_dataframe(df)
 result = batch.validate(
 expectation_suite_name="silver_orders.critical",
 run_id={"run_name": "silver_orders_daily", "run_time": datetime.now()}
 )
 stats = {
 "success": result["success"],
 "evaluated": result["statistics"]["evaluated_expectations"],
 "passed": result["statistics"]["successful_expectations"],
 "failed": result["statistics"]["unsuccessful_expectations"],
 }
 if not result["success"]:
 raise DataQualityException(f"Silver orders failed validation: {stats['failed']} checks failed")
 return stats

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