# try:

#     from datetime import timedelta
#     from airflow import DAG
    
#     from airflow.operators.python_operator import PythonOperator
#     from airflow.operators.http_operator import SimpleHttpOperator
#     from datetime import datetime, timezone
#     from pandas.io.json import json_normalize
#     from airflow.operators.postgres_operator import PostgresOperator

#     import pandas as pd
#     import json
#     import requests
#     import numpy as np
    

#     import psycopg2
#     from sqlalchemy import create_engine
#     #print("All Dag moudules are sucessfully imported")

# except Exception as e:
#     print("Error {} ".format(e))

# dRoW_api_end_url = "https://drow.cloud"

# def getDrowToken(**context):

#     response = requests.post(
#     url=f"{dRoW_api_end_url}/api/auth/authenticate",
#     data={
#     "username": "icwp2@drow.cloud",
#     "password": "dGVzdDAxQHRlc3QuY29t"
#     }
#     ).json()
#     context["ti"].xcom_push(key="token", value=response['token'])
#     # return 'DLLM{}'.format(response)


# 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/61e95dc8a6d0ad434015b52d?export_type=0",
#     # https://drow.cloud/asset/longtask-file/?filePath=longtask/9ePrntTN5v/61e27b64b3e8d9753110ee97-exportdata&fileName=9ePrntTN5v&contentType=application/json",
#     headers={
#     "x-access-token": f"Bearer {token}",
#     }
#     )
#     #print('got_data')
    
#     # Host of the RDS
#     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"

#     conn_string = ('postgres://' +
#                            dbUserName + ':' + 
#                            dbUserPassword +
#                            '@' + host + ':' + port +
#                            '/' + database)

#     resData = json.loads(response.text)
#     db = create_engine(conn_string)
#     conn = db.connect()
#     #print('db connected')
#     df = pd.DataFrame()
#     with conn as conn:
#         for x in resData:
#             df_nested_list = json_normalize(x['data'])
#             #print('process 1')
#             # df2 = df_nested_list.reindex(columns=Mapping.keys())
#             df2 = df_nested_list
#             # dataToExtract.append(objectToPush)
#             if x['data']['Date of Early Warning'] == None:
#                 Date_of_Early_Warning = datetime.now(timezone.utc)
#             else: 
#                 Date_of_Early_Warning = datetime.strptime(x['data']['Date of Early Warning'], '%Y-%m-%dT%H:%M:%S.%f%z')
#             if x['data']['Date of Close of EW'] == None:
#                 Date_of_Close_of_EW = datetime.now(timezone.utc)
#             else: 
#                 Date_of_Close_of_EW = datetime.strptime(x['data']['Date of Close of EW'], '%Y-%m-%dT%H:%M:%S.%f%z')
#             #print((Date_of_Close_of_EW - Date_of_Early_Warning))
#             if (Date_of_Close_of_EW - Date_of_Early_Warning) > np.timedelta64(24, 'h'):
#                 df2['Elapsed_Time'] = ((Date_of_Close_of_EW - Date_of_Early_Warning))
#             else:
#                 df2['Elapsed_Time'] = np.timedelta64(0, 'D')
#             if (df2['Elapsed_Time'] >= np.timedelta64(365, 'D')).bool():
#                 df2['Elapsed_Time_more_then_1_year'] = True
#             else:
#                 df2['Elapsed_Time_more_then_1_year'] = False
#             df2['Elapsed_Time'] = df2['Elapsed_Time'] / 1000 / 1000 / 86400000
#             df = df.append(df2)

#         df['Date of Close of EW']=df['Date of Close of EW'].apply(pd.to_datetime)
#         df['Date of Close of EW'] = df['Date of Close of EW'] - pd.Timedelta(hours=8)
#         df['Date of Early Warning']=df['Date of Early Warning'].apply(pd.to_datetime)
#         df['Date of Early Warning'] = df['Date of Early Warning'] - pd.Timedelta(hours=8)
#         df['Action Party  (CEDD / AECOM / DCK JV)']=np.array(df['Action Party  (CEDD / AECOM / DCK JV)'].tolist())
#         df.columns = df.columns.str.replace(' ', '_').str.replace('.', '_').str.replace('(', '_').str.replace(')', '').str.replace('/', '_').str.replace('%', 'percent')
#         # df['Action_Party___CEDD_/_AECOM_/_DCK_JV']=np.array(df['Action_Party___CEDD_/_AECOM_/_DCK_JV'].tolist())
#         df.to_sql('nec_risk_register', con=conn, if_exists='replace', index= False)

# with DAG(
#         dag_id="nec_risk_register",
#         schedule_interval="0 0,4,8,11,16 * * *",
#         default_args={
#             "owner": "airflow",
#             "retries": 1,
#             "retry_delay": timedelta(minutes=5),
#             "start_date": datetime(2022, 10, 24)
#         },
#         catchup=False) as f:
    
#     getMongoDB = PythonOperator(
#         task_id="getMongoDB",
#         python_callable=getMongoDB,
#         op_kwargs={"name": "Dylan"},
#         provide_context=True,
#     )

#     # reformData = PythonOperator(
#     #     task_id="reformData",
#     #     python_callable=reformData,
#     #     provide_context=True,
#     #     # op_kwargs={"name": "Dylan"}
#     # )

#     getDrowToken = PythonOperator(
#         task_id="getDrowToken",
#         python_callable=getDrowToken,
#         provide_context=True,
#         # op_kwargs={"name": "Dylan"}
#     )

#     # insertData = PythonOperator(
#     #     task_id="insetDateToPG",
#     #     python_callable=insertData,
#     #     provide_context=True,
#     #     # op_kwargs={"name": "Dylan"}
#     # )

#     # create_table = PostgresOperator(
#     #     sql = create_table_sql_query,
#     #     task_id = "create_table_task",
#     #     postgres_conn_id = "postgres_rds",
#     # )

#     # insert_data = PostgresOperator(
#     #     sql = insert_data_sql_query,
#     #     task_id = "insertData_sql_query_task",
#     #     postgres_conn_id = "postgres_rds",
#     # )



# # getDrowToken >> getMongoDB >> reformData >> create_table
# # create_table >> getDrowToken >> getMongoDB >> reformData >> insertData
# # getDrowToken >> getMongoDB >> reformData >> insertData\
# getDrowToken >> getMongoDB