/tmp/batch.py:39: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  df = pd.read_sql("SELECT customer_id, age, income, debt_ratio FROM demo_customers", conn)
[step5] resolved credit_risk@Production -> v1 run=7dc5896e2fb744608004bdab8ad505e7
[step5] artifact_uri=s3://mlflow-artifacts/1/7dc5896e2fb744608004bdab8ad505e7/artifacts/model
[step5] model loaded: LogisticRegression
[step5] silver rows=10000
[step5] predictions: default=0 (rate=0.000)
[step5] chunk 1/10 inserted (1000 rows)
[step5] chunk 2/10 inserted (1000 rows)
[step5] chunk 3/10 inserted (1000 rows)
[step5] chunk 4/10 inserted (1000 rows)
[step5] chunk 5/10 inserted (1000 rows)
[step5] chunk 6/10 inserted (1000 rows)
[step5] chunk 7/10 inserted (1000 rows)
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[step5] chunk 9/10 inserted (1000 rows)
[step5] chunk 10/10 inserted (1000 rows)
[step5] Gold verified: rows=10000, defaults=0, avg_score=0.1526
{
  "model_version": "1",
  "run_id": "7dc5896e2fb744608004bdab8ad505e7",
  "rows_written": 10000,
  "predicted_defaults": 0,
  "avg_score": 0.1526
}