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
    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://uat2.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'])

def getMongoDB(**context):
    token = context.get("ti").xcom_pull(key="token")
    response = requests.get(
    url=f"{dRoW_api_end_url}/api/module/nd201907/document-data?from=1665845580212&documentId=5fc46708b52b8f7ffa7b5ff6",
    headers={
    "x-access-token": f"Bearer {token}",
    "ICWPxAccessKey": "nd@201907ICWP_[1AG:4UdI){n=b~"
    }
    )
    #print('got_data')
    RISC_Data = json.loads(response.text)
    Mapping= {
    "A01 Date" : "a01_date", 
    "A02 Section-Area" : "a02_section_area",
    "A03 Location" : "a03_location",
    }

    #print('start transform')
    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"

    # #cursor Type
    # cusrsorType            = pymysql.cursors.DictCursor



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

    # df = context.get("ti").xcom_pull(key="InsertData")
    # print(df)
    # conn_string = 'postgres://user:password@host/data1'
    
    db = create_engine(conn_string)
    conn = db.connect()
    #print('db connected')
    with conn as conn:
        df = pd.DataFrame()
        for x in RISC_Data:
            df_nested_list = json_normalize(x['data'])
            #print('process 1')
            df2 = df_nested_list.reindex(columns=Mapping.keys())
            df2.rename(columns=Mapping, inplace=True)
            df2.columns = df2.columns.str.replace(' ', '_').str.replace('.', '_').str.replace('(', '_').str.replace(')', '').str.replace('%', 'percent').str.replace('/', '_').str.replace('__', '_')
            df = df.append(df2)
        cnt = df.groupby('a01_date').size().rename('Count')
        df = df.drop_duplicates(subset='a01_date').merge(cnt, left_on='a01_date', right_index=True)
        df['a01_date']=df['a01_date'].apply(pd.to_datetime)
        df.to_sql('nd201907_site_diary_activities_general_count', con=conn, if_exists='replace', index= False)
    # sql1 = '''select * from ND201907_RISC_Data;'''
    # cursor.execute(sql1)
    # for i in cursor.fetchall():
    #     print(1,i)
    
    # conn.commit()
    # conn.close()
    #print("success")

    # context["ti"].xcom_push(key="dataResponse", value=response.text)

# def reformData(**context):
    # dataResponse = context.get("ti").xcom_pull(key="dataResponse")
    # RISC_Data = json.loads(dataResponse)
    # Mapping= {"A10 - Request Submission Date Time" : "a10_request_submission_date_time", 
    # 'C02 - Survey Checked on Date Time' : 'c02_inspect_on_date_time',
    # # 'C02 - Survey Checked on Date Time' : 'Inspection/Survey Inspection date',
    # "E01 - Received on behalf of Contractor on Date Time" : "e01_received_on_behalf_of_contractor_on_date_time",
    # 'A01a - Request No. Revision': "a01a_request_no_revision",
    # "A01 - Request No.": "a01_request_no",
    # "C12 Time Pass to Senior or Contractor" : 'c12_time_pass_to_senior_or_contractor',
    # "D01 - Countersigned on Date Time" : 'd01_countersigned_on_date_time',
    # 'C03 - Approval given?' : "c03_approval_given",
    # "A01b - Work Category" : "a01b_work_category"
    # # 'C12 Time Pass to Senior or Contractor' : 'Sign time by manager'
    # }
    # # df = pd.DataFrame.from_dict([RISC_Data['data'],RISC_Data['data']])
    # # print(df)
    # df_nested_list = json_normalize(
    # RISC_Data['data']
    # )
    # print (df_nested_list)
    # df2 = df_nested_list.reindex(columns=Mapping.keys())
    # df2["request_no"] = df2["A01 - Request No."].astype(str) + df2["A01a - Request No. Revision"]
    # print (df2)
    # df2.rename(columns=Mapping, inplace=True)
    # # df2.to_sql('table_temp', engine, if_exists='replace')
    # context["ti"].xcom_push(key="InsertData", value=df2)
    # insert_data_sql_query = """

    # """
    # return "Done"

# def insertData(**context):

    # Create a connection object

    # Host of the MySQL database server (or ip)


# id SERIAL
# create_table_sql_query = """ 
#     CREATE TABLE IF NOT EXISTS nd201907_cleansing (
#     f2_checked_by_supd_on_date TIMESTAMP,
#     a01a_inspection_date TIMESTAMP,
#     d4_submission_date TIMESTAMP,
#     a2_daily_or_weekly VARCHAR (100),
#     report_name VARCHAR (100),
#     report_complete_or_incomplete VARCHAR (100),
#     nc_report BOOLEAN,
#     complete_time_in_days NUMERIC(10,2)
#     );
#     """

# create_table_sql_query = """ 
#     CREATE TABLE IF NOT EXISTS nd201907_risc (id INT NOT NULL, 
    # a10_request_submission_date_time TIMESTAMP, 
    # b01_request_received_date_time TIMESTAMP,
    # c02_inspect_or_survey_on_date_time TIMESTAMP,
    # a05_proposed_inspection_or_survey_date_time TIMESTAMP,
    # e01_received_on_behalf_of_contractor_on_date_time TIMESTAMP,
    # a01a_request_no_revision VARCHAR (50),
    # a01_request_no VARCHAR (50),
    # c12_time_pass_to_senior_or_contractor TIMESTAMP,
    # d01_countersigned_on_date_time TIMESTAMP,
    # c03_approval_given VARCHAR (50),
    # request_no VARCHAR (50),
    # a01b_work_category VARCHAR (50),
    # nc_report BOOLEAN,
    # urgent_report BOOLEAN,
    # elapsed_time NUMERIC(10,2),
    # overdue_report BOOLEAN,
    # delayed_approval_report BOOLEAN,
    # fail_in_first_inspection BOOLEAN,
    # complete_incomplete_outstanding_report VARCHAR(50)
#     );
#     """

# */2 * * * * Execute every two minute 
with DAG(
        dag_id="nd201907_site_diary_activity_general_count",
        schedule_interval="0 4,10,16,22 * * *",
        default_args={
            "owner": "airflow",
            "retries": 1,
            "retry_delay": timedelta(minutes=5),
            "start_date": datetime(2023, 1, 17)
        },
        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
# create_table >> 
getDrowToken >> getMongoDB
    
            # if df2['F2. 監理代表 Checked by SupD on Date'].isnull().bool():
            #     df2['report_complete_or_incomplete'] = 'incomplete'
            # else:
            #     df2['report_complete_or_incomplete'] = 'complete'
            # if not df2['F2. 監理代表 Checked by SupD on Date'].isnull().bool() and not df2['D4 Submission Date'].isnull().bool() and (df2["F2. 監理代表 Checked by SupD on Date"].astype('datetime64[ns]') < df2["D4 Submission Date"].astype('datetime64[ns]')).bool():
            #     df2['nc_report'] = True
            # else:
            #     df2['nc_report'] = False
            # if (not df2['F2. 監理代表 Checked by SupD on Date'].isnull().bool() and not df2['A1a 巡查日期 Inspection Date'].isnull().bool()):
            #     df2['complete_time_in_days'] = (((df2['F2. 監理代表 Checked by SupD on Date'].astype('datetime64[ns]') - 
            #     df2['A1a 巡查日期 Inspection Date'].astype('datetime64[ns]'))/ np.timedelta64(1, 'h'))/24).round(2)
            #     if df2['complete_time_in_days'].isnull().bool() or df2['complete_time_in_days'].lt(0).bool():
            #         df2['complete_time_in_days'] = 0
            # else:
            #     df2['complete_time_in_days'] = 0
            # if(not df2["C02 - Survey Checked on Date Time"].isnull().bool() and not df2["A10 - Request Submission Date Time"].isnull().bool() and ((df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]') < df2["A10 - Request Submission Date Time"].astype('datetime64[ns]')).bool())):
            #     print((df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]') < df2["A10 - Request Submission Date Time"].astype('datetime64[ns]')))
            # else:
            #     print((df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]') < df2["A10 - Request Submission Date Time"].astype('datetime64[ns]')))

            # if (not df2["C02 - Survey Checked on Date Time"].isnull().bool() and (not df2["A10 - Request Submission Date Time"].isnull().bool()) and (df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]') < df2["A10 - Request Submission Date Time"].astype('datetime64[ns]')).bool()):
            #     df2['nc_report'] = True
            # else:
            #     df2['nc_report'] = False

            # if (not df2["C02 - Survey Checked on Date Time"].isnull().bool() and not df2["A10 - Request Submission Date Time"].isnull().bool() and (((df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]') - df2["A10 - Request Submission Date Time"].astype('datetime64[ns]'))) < pd.Timedelta(24, unit='h')).bool()):
            #     df2['urgent_report'] = True
            # else:
            #     df2['urgent_report'] = False

            # if (not df2['E01 - Received on behalf of Contractor on Date Time'].isnull().bool() and not df2['A10 - Request Submission Date Time'].isnull().bool()):
            #     df2['elapsed_time'] = (((df2['E01 - Received on behalf of Contractor on Date Time'].astype('datetime64[ns]') - 
            #     df2['A10 - Request Submission Date Time'].astype('datetime64[ns]'))/ np.timedelta64(1, 'h'))/24).round(2)
            #     if df2['elapsed_time'].isnull().bool() or df2['elapsed_time'].lt(0).bool():
            #         df2['elapsed_time'] = 0
            # else:
            #     df2['elapsed_time'] = 0
            
            # if (not df2["C02 - Survey Checked on Date Time"].isnull().bool() and not df2["D01 - Countersigned on Date Time"].isnull().bool() and (((df2["D01 - Countersigned on Date Time"].astype('datetime64[ns]') - df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]')))>= pd.Timedelta(24, unit='h')).bool()):
            #     df2['overdue_report'] = True
            # else:
            #     df2['overdue_report'] = False
            
            # if (not df2["C02 - Survey Checked on Date Time"].isnull().bool() and not df2["C12 Time Pass to Senior or Contractor"].isnull().bool() and (((df2["C12 Time Pass to Senior or Contractor"].astype('datetime64[ns]') - df2["C02 - Survey Checked on Date Time"].astype('datetime64[ns]')))>= pd.Timedelta(24, unit='h')).bool()):
            #     df2['delayed_approval_report'] = True
            # else:
            #     df2['delayed_approval_report'] = False

            # if ((df2['A01a - Request No. Revision']=="-A").bool()):
            #     df2['fail_in_first_inspection'] = True
            # else:
            #     df2['fail_in_first_inspection'] = False
            
            # if (not df2["C12 Time Pass to Senior or Contractor"].isnull().bool() and not df2["C02 - Survey Checked on Date Time"].isnull().bool() and not df2["E01 - Received on behalf of Contractor on Date Time"].isnull().bool()):
            #     df2['complete_incomplete_outstanding_report'] = 'complete'
            # elif ((df2["C12 Time Pass to Senior or Contractor"].isnull().bool() or df2["E01 - Received on behalf of Contractor on Date Time"].isnull().bool()) and not df2["C02 - Survey Checked on Date Time"].isnull().bool()):
            #     df2['complete_incomplete_outstanding_report'] = 'in-complete'
            # elif ((not df2["C12 Time Pass to Senior or Contractor"].isnull().bool() or df2["E01 - Received on behalf of Contractor on Date Time"].isnull().bool()) and df2["C02 - Survey Checked on Date Time"].isnull().bool()):
            #     df2['complete_incomplete_outstanding_report'] = 'outstanding'
            # else:
            #     df2['complete_incomplete_outstanding_report'] = 'outstanding'