def getMongoDB(**context):
    token = context.get("ti").xcom_pull(key="token")
    response = requests.get(
        url=f"{dRoW_api_end_url}/api/module/document-export/airflow/workflow/66ff882a373b4986e8a2f09b?export_type=0",
        headers={
        "x-access-token": f"Bearer {token}",
        }
    )
    Data = json.loads(response.text)

    # Mapping= {
    #         "Original Doc No.": "Original_Doc_No",
    #         "NEC Doc Type": "NEC_Doc_Type",
    #         "NEC Event No.": "NEC_Event_No",
    #         "Doc Ver.": "Doc_Ver",
    #         "Doc Date": "Doc_Date",
    #         "Subject": "Subject",
    #         "From": "From",
    #         "To": "To",
    #         "CE Amount": "CE_PMI_Amount",
    #         "CE Increase / Decrease": "CE_Increase_Decrease",
    #         "Quotation Status": "Quotation_Status",
    #         "NEC Clause": "NEC_Clause",
    #         "Receive Date": "Receive_Date"
    # }
    host                  = 'drowdatewarehouse.crlwwhgepgi7.ap-east-1.rds.amazonaws.com'  
    # User name of the database server
    dbUserName            = 'dRowAdmin'  
    # Password for the database user
    dbUserPassword        = 'drowsuper'  
    # Name of the database 
    database              = 'drowDateWareHouse'
    # Character set
    charSet               = "utf8mb4"  
    port                  = "5432"

    #create_engine('mysql+mysqldb://root:password@localhost:3306/mydbname', echo = False)
    conn_string = ('postgres://' +
                           dbUserName + ':' + 
                           dbUserPassword +
                           '@' + host + ':' + port +
                           '/' + database)
    db = create_engine(conn_string)
    conn = db.connect()

    df = pd.DataFrame()
    with conn as conn:
        for x in Data:
            try:
                if len(x['data'].keys()) == 0:
                    continue
                df_nested_list = json_normalize(x['data'])
                df = df.append(df_nested_list)
            except Exception as e:
                print(f"Error processing data: {e}")  # Add logging
            continue

        df.columns = df.columns.str.replace(' ', '_').str.replace('.', '').str.replace('(', '_').str.replace(')', '').str.replace('%', 'percent').str.replace('/', '_')
        df.drop(['Payment_Summary', "Contractor's_Application", "PM's_Assessment"], axis=1, inplace=True)
        df.to_sql('cv202211_payment_excel', con=conn, if_exists='replace', index= False)