Create multiple/single csv file for each sql records

[mg24]

Hi Team,

below code I am using to extract big sql table 60gb.
how to extract sql table to csv using sqlalchemy with headers.

import pyodbc
import csv

connection = pyodbc.connect('DRIVER={ODBC Driver 17 for SQL Server};SERVER=DESKTOP-GQK64O6;DATABASE=Customer;Trusted_Connection=yes;')
cursor = connection.cursor()


qry = "select * from employee"

cursor.execute(qry) 
#data = cursor.fetchall()


With open("E:\\backup\\output.csv","w","newline="") as outfile
	writer = csv.writer(outfile,quoting = csv.QUOTE_NONNUMERIC)
	writer.writerows(col[0] for col in cursor.description)
	While True:
		rows = cursor.fetchmany(10000)
		if len(rows) ==0:
			print("no records found")
			break
		else:
	          x = x+len(rows)
               print(x)
               for row in rows:
                  writer.writerows(row)


conn.close()
print("success")
print('time taken' . time.time()-initial,"Seconds")

Below is my attempted code, how to fetch extract SQL Table data with header using pycharm.
without memory full issue.

from sqlalchemy import create_engine
import pandas as pd

DRIVER= "ODBC Driver 17 for SQL Server"
server="DESKTOP-GQK64O6"
DATABASE="Customer"

str_conn = f'mssql://{server}/{DATABASE}?Driver={DRIVER}'
connection = create_engine(str_conn).connect()

mylist = []

#Read in Chunk
for chunk in pd.read_sql_table('employee',connection,chunksize=1000):
	mylist.append(chunk)
df = pd.concat(mylist)
ndf = pd.DataFrame(df)

ndf.to_parquet("C:\\C_Programming\\output.csv")

Thanks
mg