Request and store the "Maximum Temperature" for 5 cities over 30 day period.

temperature.py

import requests
import sqlite3 as lite
import datetime

api_key = 'API_KEY'

url = 'https://api.forecast.io/forecast/' + api_key

cities = { "Wamego": '39.201941,-96.304998',
            "Grinnell": '39.127230,-100.629031',
            "Eldorado": '37.817240,-96.862252',
            "Salina": '38.840280,-97.611424',
            "Denver": '39.739236,-104.990251'
        }

end_date = datetime.datetime.now()

con = lite.connect('weather.db')
cur = con.cursor()

cities.keys()
with con:
	cur.execute('CREATE TABLE daily_temp ( day_of_reading INT, Wamego REAL, Grinnell REAL, Eldorado REAL, Salina REAL, Denver REAL);')


query_date = end_date - datetime.timedelta(days=30)

with con:
	while query_date < end_date:
		cur.execute("INSERT INTO daily_temp(day_of_reading) VALUES (?)", (int(query_date.strftime('%s')),))
		query_date += datetime.timedelta(days=1)


for k,v in cities.iteritems():
	query_date = end_date - datetime.timedelta(days=30)
	while query_date < end_date:
		r = requests.get(url + '/' + v + ',' + query_date.strftime('%Y-%m-%dT12:00:00'))

		with con:
			# insert temperatureMax into db
			cur.execute('UPDATE daily_temp SET ' + k + ' = ' + str(r.json()['daily']['data'][0]['temperatureMax']) + ' WHERE day_of_reading = ' + query_date.strftime('%s'))


		query_date += datetime.timedelta(days=1)

con.close()