Files
AddressBookExport/main.py
2021-02-19 13:43:47 -05:00

122 lines
4.1 KiB
Python

from sqlalchemy import create_engine, Column, Integer, String, BOOLEAN
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
import xlwt
UserAddressID = []
ActiveUser = []
LineCount = 1
engine = create_engine('mssql+pymssql://IDV2Ridge:cWZSGWXS9muyYkHN*@10.10.10.50/IDV2Ridge', echo=False)
engine.connect()
Base = declarative_base()
class UserAddress(Base):
__tablename__ = 'UserAddress'
UserId = Column(Integer, primary_key=True)
AddressId = Column(Integer, primary_key=True)
class Address(Base):
__tablename__ = 'Address'
Id = Column(Integer, primary_key=True)
ContactName = Column(String)
CompanyName = Column(String)
Line1 = Column(String)
Line2 = Column(String)
City = Column(String)
StateId = Column(Integer)
PostalCode = Column(String)
CountryId = Column(Integer)
PhoneNumber = Column(String)
EmailAddress = Column(String)
class User(Base):
__tablename__ = 'User'
ID = Column(Integer, primary_key=True)
FirstName = Column(String)
LastName = Column(String)
IsDeleted = Column(BOOLEAN)
class State(Base):
__tablename__ = 'State'
Id = Column(Integer, primary_key=True)
StateName = Column(String)
class Country(Base):
__tablename__ = 'Country'
Id = Column(Integer, primary_key=True)
CountryName = Column(String)
Session = sessionmaker(bind=engine)
session = Session()
# Get list of active users
for user in session.query(User).filter(User.ID == 14):
ActiveUser.append([user.ID, user.FirstName, user.LastName])
# loop through each user in the ActiveUser array. Combine Users First/Last name for the filename and
# the first letter/last name combo for username
for each in ActiveUser:
#
FileName = each[1] + ' ' + each[2]
UserName = each[1][0]+each[2]
# Setup XLS workbook and sheet
wb = xlwt.Workbook()
ws = wb.add_sheet('Addresses')
# Write header row
ws.write(0, 0, 'ACTION')
ws.write(0, 1, 'BU_ID')
ws.write(0, 2, 'LOGIN_ID')
ws.write(0, 3, 'PA_NAME')
ws.write(0, 4, 'PA_NAME2')
ws.write(0, 5, 'LINE1')
ws.write(0, 6, 'LINE2')
ws.write(0, 7, 'LINE3')
ws.write(0, 8, 'CITY')
ws.write(0, 9, 'STATE')
ws.write(0, 10, 'ZIP')
ws.write(0, 11, 'COUNTRY')
ws.write(0, 12, 'PHONE_NR')
ws.write(0, 13, 'SHIP_TO_ATTN_TX')
ws.write(0, 14, 'PROFILE_TYPE')
# For each username we're filtering the UserAddress table by their userID and adding it to the UserAddressID array.
# The UserAddressID array is then looped through and for each AddressID we pull the Address information,
# State Information, and Country Information and combine it into one result
for ua in session.query(UserAddress).filter(UserAddress.UserId == each[0]):
UserAddressID.append(ua.AddressId)
for aid in UserAddressID:
for cn in session.query(Address, State, Country).join(State, Address.StateId == State.Id).join(Country, Address.CountryId == Country.Id).filter(Address.Id == aid):
# Combine all the required fields into one variable for simplicity
AddresssBookLine = UserName, cn[0].CompanyName, cn[0].Line1, cn[0].Line2, cn[0].City, cn[1].StateName, cn[0].PostalCode, cn[2].CountryName, cn[0].PhoneNumber,cn[0].ContactName
# Loop through each row and populate the variable columns with the corresponding AddressBookLine element
ws.write(LineCount, 2, AddresssBookLine[0])
ws.write(LineCount, 3, AddresssBookLine[1])
ws.write(LineCount, 5, AddresssBookLine[2])
ws.write(LineCount, 6, AddresssBookLine[3])
ws.write(LineCount, 8, AddresssBookLine[4])
ws.write(LineCount, 9, AddresssBookLine[5])
ws.write(LineCount, 10, AddresssBookLine[6])
ws.write(LineCount, 11, AddresssBookLine[7])
ws.write(LineCount, 12, AddresssBookLine[8])
ws.write(LineCount, 13, AddresssBookLine[9])
LineCount = LineCount + 1
print(LineCount)
UserAddressID = []
LineCount = 1
wb.save(FileName+'.xls')