pybigquery

import os from sqlalchemy import create_engine, text # Ensure GOOGLE_APPLICATION_CREDENTIALS points to your service account key file # or use `gcloud auth application-default login` for Application Default Credentials. # Replace 'your-gcp-project-id' and 'your_dataset' with actual values or set env vars. project_id = os.environ.get('BIGQUERY_PROJECT_ID', 'your-gcp-project-id') dataset_id = os.environ.get('BIGQUERY_DATASET_ID', 'your_dataset') if project_id == 'your-gcp-project-id': print("WARNING: Set BIGQUERY_PROJECT_ID env var or replace 'your-gcp-project-id'.") if dataset_id == 'your_dataset': print("WARNING: Set BIGQUERY_DATASET_ID env var or replace 'your_dataset'.") try: # Connect using the 'bigquery' dialect provided by pybigquery # Note: For production, ensure credentials are set securely. engine = create_engine(f"bigquery://{project_id}/{dataset_id}") with engine.connect() as connection: # Example query (replace with your specific table/data) # Note: 'text()' is required for string-based SQL statements in SQLAlchemy 1.4+/2.0. result = connection.execute(text("SELECT 1 as num, 'hello' as str")) for row in result: print(f"Retrieved row: num={row.num}, str='{row.str}'") print("Successfully connected to BigQuery using PyBigQuery (obsolete).") except Exception as e: print(f"An error occurred: {e}") print("Troubleshooting hint: Check BigQuery project/dataset IDs, credentials, and Python version.") print("RECOMMENDATION: Migrate to 'google-cloud-bigquery-sqlalchemy' for active support.")