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375 | try:
import json
from datetime import datetime, timedelta
import numpy as np
import pandas as pd
import requests
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from pandas.io.json import json_normalize
from sqlalchemy import create_engine
except Exception as e:
print("Error {} ".format(e))
dRoW_api_end_url = "https://drow.cloud"
Mapping= {
"Date of Inspection" : "a01a_inspection_date",
"A Part SO/EO Sign Date:": "a_part_so_eo_sign_date",
"B Part RSS Sign Date:": "b_part_rss_sign_date",
}
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 getFirstAction(**context):
token = context.get("ti").xcom_pull(key="token")
response = requests.get(
url=f"{dRoW_api_end_url}/api/module/document-export/airflow/workflow/6541f7d28674275009aba801?export_type=0",
headers={
"x-access-token": f"Bearer {token}",
"ICWPxAccessKey": "nd@201907ICWP_[1AG:4UdI){n=b~"
}
)
RISC_Data = json.loads(response.text)
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
port = "5432"
# Character set
charSet = "utf8mb4"
conn_string = ('postgres://' +
dbUserName + ':' +
dbUserPassword +
'@' + host + ':' + port +
'/' + database)
db = create_engine(conn_string)
conn = db.connect()
with conn as conn:
df = pd.DataFrame()
for x in RISC_Data:
df_nested_list = json_normalize(x['data'])
df2 = df_nested_list.reindex(columns=Mapping.keys())
df2.rename(columns=Mapping, inplace=True)
df2['a2_daily_or_weekly'] = "daily"
df2['a01a_inspection_date'] = df2['a01a_inspection_date'].astype('datetime64[ns]') - pd.Timedelta(8, unit='h')
if len(x['ApproveLogSummary']) > 0:
request_data = [data for data in x['ApproveLogSummary'] if data.get('statusName')=="B : RSS check"]
if len(request_data) > 0 and 'from' in request_data[-1]:
df2['f2_checked_by_supd_on_date'] = request_data[-1]['from']
else:
df2['f2_checked_by_supd_on_date'] = None
if len(request_data) > 0 and 'to' in request_data[-1]:
df2['d4_submission_date'] = request_data[-1]['to']
else:
df2['d4_submission_date'] = None
else:
df2['f2_checked_by_supd_on_date'] = None
df2['d4_submission_date'] = None
df2["report_name"] = df2["a01a_inspection_date"].astype(str).str[:10]
if len([data for data in x['ApproveLogSummary'] if data.get('statusName')=="Z : END"])>0:
df2['report_complete_or_incomplete'] = 'complete'
else:
df2['report_complete_or_incomplete'] = 'incomplete'
if 'data' in x and isinstance(x['data'], dict):
for key in x['data']:
if 'Checklist' in key:
total_report = 0
total_x = 0
for item in x['data'][key]:
for item_key in item:
if item[item_key] == 'N/A' or item[item_key] == 'Yes':
total_report += 1
if item[item_key] == 'No' or item[item_key] == '✗':
total_x += 1
total_report += 1
df2['nc_report_item'] = total_x
df2['total_report_item'] = total_report
if (not df2['f2_checked_by_supd_on_date'].isnull().bool() and not df2['a01a_inspection_date'].isnull().bool()):
df2['complete_time_in_days'] = (((df2['f2_checked_by_supd_on_date'].astype('datetime64[ns]') -
df2['a01a_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
df = df.append(df2)
df['a01a_inspection_date']=df['a01a_inspection_date'].apply(pd.to_datetime)
df['d4_submission_date']=df['d4_submission_date'].apply(pd.to_datetime)
df['f2_checked_by_supd_on_date']=df['f2_checked_by_supd_on_date'].apply(pd.to_datetime)
df['a_part_so_eo_sign_date']=df['a_part_so_eo_sign_date'].apply(pd.to_datetime)
df['b_part_rss_sign_date']=df['b_part_rss_sign_date'].apply(pd.to_datetime)
df.to_sql('cleansing_dc202312', con=conn, if_exists='replace', index= False)
def getSecondAction(**context):
token = context.get("ti").xcom_pull(key="token")
response = requests.get(
url=f"{dRoW_api_end_url}/api/module/document-export/airflow/workflow/657680fb912eb1311127a9ef?export_type=0",
headers={
"x-access-token": f"Bearer {token}",
"ICWPxAccessKey": "nd@201907ICWP_[1AG:4UdI){n=b~"
}
)
RISC_Data = json.loads(response.text)
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
port = "5432"
# Character set
charSet = "utf8mb4"
conn_string = ('postgres://' +
dbUserName + ':' +
dbUserPassword +
'@' + host + ':' + port +
'/' + database)
db = create_engine(conn_string)
conn = db.connect()
with conn as conn:
df = pd.DataFrame()
for x in RISC_Data:
df_nested_list = json_normalize(x['data'])
df2 = df_nested_list.reindex(columns=Mapping.keys())
df2.rename(columns=Mapping, inplace=True)
df2['a2_daily_or_weekly'] = "weekly"
df2['a01a_inspection_date'] = df2['a01a_inspection_date'].astype('datetime64[ns]') - pd.Timedelta(8, unit='h')
if len(x['ApproveLogSummary']) > 0:
request_data = [data for data in x['ApproveLogSummary'] if data.get('statusName')=="B : RSS check"]
if len(request_data) > 0 and 'from' in request_data[-1]:
df2['f2_checked_by_supd_on_date'] = request_data[-1]['from']
else:
df2['f2_checked_by_supd_on_date'] = None
if len(request_data) > 0 and 'to' in request_data[-1]:
df2['d4_submission_date'] = request_data[-1]['to']
else:
df2['d4_submission_date'] = None
else:
df2['f2_checked_by_supd_on_date'] = None
df2['d4_submission_date'] = None
df2["report_name"] = df2["a01a_inspection_date"].astype(str).str[:10]
if len([data for data in x['ApproveLogSummary'] if data.get('statusName')=="Z : END"])>0:
df2['report_complete_or_incomplete'] = 'complete'
else:
df2['report_complete_or_incomplete'] = 'incomplete'
if 'data' in x and isinstance(x['data'], dict):
for key in x['data']:
if 'Checklist' in key:
total_report = 0
total_x = 0
for item in x['data'][key]:
for item_key in item:
if item[item_key] == 'N/A' or item[item_key] == 'Yes':
total_report += 1
if item[item_key] == 'No' or item[item_key] == '✗':
total_x += 1
total_report += 1
df2['nc_report_item'] = total_x
df2['total_report_item'] = total_report
if (not df2['f2_checked_by_supd_on_date'].isnull().bool() and not df2['a01a_inspection_date'].isnull().bool()):
df2['complete_time_in_days'] = (((df2['f2_checked_by_supd_on_date'].astype('datetime64[ns]') -
df2['a01a_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
df = df.append(df2)
df['a01a_inspection_date']=df['a01a_inspection_date'].apply(pd.to_datetime)
df['d4_submission_date']=df['d4_submission_date'].apply(pd.to_datetime)
df['f2_checked_by_supd_on_date']=df['f2_checked_by_supd_on_date'].apply(pd.to_datetime)
df['a_part_so_eo_sign_date']=df['a_part_so_eo_sign_date'].apply(pd.to_datetime)
df['b_part_rss_sign_date']=df['b_part_rss_sign_date'].apply(pd.to_datetime)
df.to_sql('cleansing_dc202312', con=conn, if_exists='append', index= False)
def getThirdAction(**context):
token = context.get("ti").xcom_pull(key="token")
response = requests.get(
url=f"{dRoW_api_end_url}/api/module/document-export/airflow/workflow/65d2be65d30fff37ac849ddf?export_type=0",
headers={
"x-access-token": f"Bearer {token}",
"ICWPxAccessKey": "nd@201907ICWP_[1AG:4UdI){n=b~"
}
)
RISC_Data = json.loads(response.text)
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
port = "5432"
# Character set
charSet = "utf8mb4"
conn_string = ('postgres://' +
dbUserName + ':' +
dbUserPassword +
'@' + host + ':' + port +
'/' + database)
db = create_engine(conn_string)
conn = db.connect()
with conn as conn:
df = pd.DataFrame()
for x in RISC_Data:
df_nested_list = json_normalize(x['data'])
df2 = df_nested_list.reindex(columns=Mapping.keys())
df2.rename(columns=Mapping, inplace=True)
df2['a2_daily_or_weekly'] = "monthly"
if len(x['ApproveLogSummary']) > 0:
request_data = [data for data in x['ApproveLogSummary'] if data.get('statusName')=="B : RSS check"]
if len(request_data) > 0 and 'from' in request_data[-1]:
df2['f2_checked_by_supd_on_date'] = request_data[-1]['from']
else:
df2['f2_checked_by_supd_on_date'] = None
if len(request_data) > 0 and 'to' in request_data[-1]:
df2['d4_submission_date'] = request_data[-1]['to']
else:
df2['d4_submission_date'] = None
else:
df2['f2_checked_by_supd_on_date'] = None
df2['d4_submission_date'] = None
df2["report_name"] = df2["a01a_inspection_date"].astype(str).str[:10]
if len([data for data in x['ApproveLogSummary'] if data.get('statusName')=="Z : END"])>0:
df2['report_complete_or_incomplete'] = 'complete'
else:
df2['report_complete_or_incomplete'] = 'incomplete'
if 'data' in x and isinstance(x['data'], dict):
for key in x['data']:
if 'Checklist' in key:
total_report = 0
total_x = 0
for item in x['data'][key]:
for item_key in item:
if item[item_key] == 'N/A' or item[item_key] == 'Yes':
total_report += 1
if item[item_key] == 'No' or item[item_key] == '✗':
total_x += 1
total_report += 1
df2['nc_report_item'] = total_x
df2['total_report_item'] = total_report
if (not df2['f2_checked_by_supd_on_date'].isnull().bool() and not df2['a01a_inspection_date'].isnull().bool()):
df2['complete_time_in_days'] = (((df2['f2_checked_by_supd_on_date'].astype('datetime64[ns]') -
df2['a01a_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
df = df.append(df2)
df['a01a_inspection_date']=df['a01a_inspection_date'].apply(pd.to_datetime)
df['d4_submission_date']=df['d4_submission_date'].apply(pd.to_datetime)
df['f2_checked_by_supd_on_date']=df['f2_checked_by_supd_on_date'].apply(pd.to_datetime)
df['a_part_so_eo_sign_date']=df['a_part_so_eo_sign_date'].apply(pd.to_datetime)
df['b_part_rss_sign_date']=df['b_part_rss_sign_date'].apply(pd.to_datetime)
df.to_sql('cleansing_dc202312', con=conn, if_exists='append', index= False)
create_table_sql_query = """
CREATE TABLE IF NOT EXISTS cleansing_dc202312 (
f2_checked_by_supd_on_date TIMESTAMP,
a01a_inspection_date TIMESTAMP,
d4_submission_date TIMESTAMP,
report_name VARCHAR (100),
report_complete_or_incomplete VARCHAR (100),
nc_report BOOLEAN,
complete_time_in_days NUMERIC(10,2)
a_part_so_eo_sign_date TIMESTAMP,
b_part_rss_sign_date TIMESTAMP,
a2_daily_or_weekly VARCHAR (100),
);
"""
# */2 * * * * Execute every two minute
with DAG(
dag_id="dc202312_cleaning",
schedule_interval="0 15 * * *",
default_args={
"owner": "airflow",
"retries": 1,
"retry_delay": timedelta(minutes=5),
"start_date": datetime(2023, 1, 17)
},
catchup=False) as f:
getFirstAction = PythonOperator(
task_id="getFirstAction",
python_callable=getFirstAction,
op_kwargs={"name": "Dylan"},
provide_context=True,
)
getSecondAction = PythonOperator(
task_id="getSecondAction",
python_callable=getSecondAction,
op_kwargs={"name": "Dylan"},
provide_context=True,
)
getThirdAction = PythonOperator(
task_id="getThirdAction",
python_callable=getThirdAction,
op_kwargs={"name": "Dylan"},
provide_context=True,
)
getDrowToken = PythonOperator(
task_id="getDrowToken",
python_callable=getDrowToken,
provide_context=True,
)
# create_table = PostgresOperator(
# sql = create_table_sql_query,
# task_id = "create_table_task",
# postgres_conn_id = "postgres_rds",
# )
getDrowToken >> getFirstAction >> getSecondAction >> getThirdAction
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