def getPaymentStatistics(**context):
    token = context.get("ti").xcom_pull(key="token")

    main_records = get_workflow_records(token, WORKFLOW_ID)
    print(f"Total records fetched from main workflow: {len(main_records) if main_records else 0}")

    if not main_records:
        print("No records found in main workflow.")
        return

    final_stats_records = get_workflow_records(token, FINAL_STATS_WORKFLOW_ID)
    print(f"Total records fetched from final stats workflow: {len(final_stats_records) if final_stats_records else 0}")

    final_stats_lookup = build_final_stats_lookup(final_stats_records)
    print(f"Final stats lookup rows prepared: {len(final_stats_lookup)}")

    output_rows = []
    matched_final_stats_count = 0
    unmatched_ip_nos = []

    for record in main_records:
        row = extract_output_row(record)
        ip_no = normalize_ip_no(row.get("ip_no"))

        final_stats = final_stats_lookup.get(ip_no)
        if final_stats:
            row["final_total_of_the_price_with_pain"] = final_stats.get("final_total_of_the_price_with_pain")
            row["final_total_of_the_price"] = final_stats.get("final_total_of_the_price")
            matched_final_stats_count += 1
        else:
            unmatched_ip_nos.append(ip_no)

        output_rows.append(row)

    print("\n===== SAMPLE OUTPUT ROW (PAYMENT STATISTICS) =====")
    print(json.dumps(output_rows[:1], indent=2, default=str))

    print(f"Matched final stats rows: {matched_final_stats_count}")
    print(f"Unmatched IP nos count: {len(unmatched_ip_nos)}")
    if unmatched_ip_nos:
        print("Sample unmatched IP nos:", unmatched_ip_nos[:10])

    df = pd.DataFrame(output_rows)

    engine = get_postgres_connection()

    df.to_sql(
        TARGET_TABLE,
        engine,
        if_exists="replace",
        index=False
    )

    print(f"Inserted {len(df)} rows into {TARGET_TABLE}")