from webdav3.client import Client
from datetime import datetime
import pandas as pd
import dateutil
from dateutil import parser
from dateutil.parser import *
from sqlalchemy import create_engine
import os
#record db create date
db_create_date=datetime.strptime(datetime.strftime(pd.to_datetime(datetime.utcnow()), '%Y-%m-%d %H:%M:%S'),'%Y-%m-%d %H:%M:%S')
superstates_list = ['PRO_SUPERSTATE','PRO_SUPERSTATE_NEW']
for file in os.listdir(r'D:/Aspect_Files/Temp/'):
if file.split('.')[0] in superstates_list:
df=pd.read_csv(r'D:/Aspect_Files/Temp/'+file).fillna(0)
del df['PRI_INDEX']
del df['EMP_SK']
del df['EMP_LAST_NAME']
del df['EMP_FIRST_NAME']
del df['EMP_SORT_NAME']
del df['EMP_SHORT_NAME']
del df['EMP_SENIORITY']
del df['EMP_EFF_HIRE_DATE']
del df['START']
del df['STOP']
del df['WRK_SEG']
del df['GEN_SEG']
del df['EMP_CLASS_1']
del df['EMP_CLASS_1_DESCR']
del df['EMP_CLASS_2']
del df['EMP_CLASS_2_DESCR']
del df['EMP_CLASS_3']
del df['EMP_CLASS_3_DESCR']
del df['EMP_CLASS_4']
del df['EMP_CLASS_4_DESCR']
# Credentials to database connection
print(df)
df['NOM_DATE'] = [datetime.strptime(x,'%m/%d/%Y') for x in df['NOM_DATE']]
hostname='localhost'
dbname='aspect'
uname=''
pwd=""
# Create SQLAlchemy engine to connect to MySQL Database
db = create_engine("mysql+pymysql://{user}:{pw}@{host}/{db}"
.format(host=hostname, db=dbname, user=uname, pw=pwd))
#connect with database
conn = db.connect()
# Convert dataframe to sql table
df.to_sql('superstate_staging', db, if_exists='append', index=False)
# close connection
conn.close()
# dispose engine
db.dispose()
exit()