import csv
from influxdb import InfluxDBClient

USER='root'
PASSWORD='root'
DBNAME='sensordata'
HOST='localhost'
PORT=8086

client = InfluxDBClient(HOST,PORT,USER,PASSWORD,DBNAME)
query="select * from home where time > '2017-11-15 14:55:00' AND time <= '2017-11-15 14:55:05' tz('Asia/Kolkata')"
result = client.query(query,epoch='ns')
exported_data = list(result.get_points())
with open("output.csv", "a", newline='') as fp:
    writer = csv.writer(fp, dialect='excel')
    for line in exported_data:
        print(line)
        writer.writerow(line)

{'time': 1510737900336919297, 'value1': 18.84, 'value10': 19.83, 'value2': 18.56, 'value3': 12.61, 'value4': 17.57, 'value5': 16.6, 'value6': 16.81, 'value7': 12.84, 'value8': 11.54, 'value9': 14.26}
{'time': 1510737901370333995, 'value1': 11.32, 'value10': 12.98, 'value2': 12.34, 'value3': 12.22, 'value4': 11.08, 'value5': 12.07, 'value6': 17.62, 'value7': 14.68, 'value8': 16.87, 'value9': 11.4}
{'time': 1510737902403461281, 'value1': 12.37, 'value10': 16.18, 'value2': 18.83, 'value3': 14.59, 'value4': 11.79, 'value5': 18.52, 'value6': 11.25, 'value7': 17.28, 'value8': 10.54, 'value9': 19.1}
{'time': 1510737903436997966, 'value1': 13, 'value10': 12.04, 'value2': 10.02, 'value3': 14.28, 'value4': 14.51, 'value5': 17.3, 'value6': 16.14, 'value7': 15.04, 'value8': 13.16, 'value9': 10.47}
{'time': 1510737904470366806, 'value1': 16.2, 'value10': 10.83, 'value2': 12.64, 'value3': 13.51, 'value4': 13.74, 'value5': 11.52, 'value6': 13.42, 'value7': 13.14, 'value8': 16.6, 'value9': 11.24}

time,value1,value10,value2,value3,value4,value5,value6,value7,value8,value9
time,value1,value10,value2,value3,value4,value5,value6,value7,value8,value9
time,value1,value10,value2,value3,value4,value5,value6,value7,value8,value9
time,value1,value10,value2,value3,value4,value5,value6,value7,value8,value9
time,value1,value10,value2,value3,value4,value5,value6,value7,value8,value9

time_heading, value1_heading, value2_heading ....
time_value, value1_value, value2_value ....
time_value, value1_value, value2_value ....
time_value, value1_value, value2_value ....
.
.
.