import housecanary, pandas, csv, json, time
from requests import get

client = housecanary.ApiClient("ZQEEDT3ZE89QU7CUFON1", "UjYOXpu7ciS6sqvqZ1Rvrom6YFiPc96k")
user = 'jack@patchhomes.com'
password = 'kj6qje1qaz'
addresses = pandas.read_csv('TestJaime.csv')

with open('new.csv','w') as csvfile:
 titles = ['zipcode','returns_12mo_f','returns_24mo_f', 'returns_36mo_f', 'cagr_12mo_f', 'cagr_24mo_f','cagr_36mo_f','risk_12mo_loss','max_12mo_loss', 'market_action_median', 'months_of_inventory_median', 'days_on_market_median']
 csvfile.write(','.join([str(i) for i in titles])+'\n')
 for address in addresses.iterrows():
  try:
   zipcode = address[1].zipcode
   housevals = [zipcode]
   housekeys = [zipcode]
   hpivals = [zipcode]
   hpikeys = [zipcode]
   zipcode = str(int(zipcode))
   if len(zipcode) == 4: zipcode = '0' + zipcode
   # print('details data ---------------')
   result = client.zip.details(zipcode)
   # print(json.loads(result.text)[0])
   for val in json.loads(result.text)[0]['zip/details']['result']['single_family'].keys(): housekeys.append(val)
   for val in json.loads(result.text)[0]['zip/details']['result']['single_family'].values(): housevals.append(val)
   # housevals.append('')
   result3 = client.zip.hpi_forecast(zipcode)
   for val in json.loads(result3.text)[0]['zip/hpi_forecast']['result'].keys(): hpikeys.append(val)
   # for val in json.loads(result3.text)[0]['zip/hpi_forecast']['result'].values(): hpivals.append(val)
   print('details data ---------------')
   # print(result.text)
   print('zip/details --->')
   print(json.loads(result.text)[0]['zip/details']['result'])
   print('zip/hpi_forecast --->')
   print(json.loads(result3.text)[0]['zip/hpi_forecast']['result'])
   # print(json.loads(result.text)[0]['zip/details']['result']['single_family']['market_action_median'])
   print('details data end ---------------')
   # for val in json.loads(result.text)[0]['zip/details']['result']['single_family'].values(): hpivals.append(val)
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['returns_12mo_f'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['returns_24mo_f'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['returns_36mo_f'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['cagr_12mo_f'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['cagr_24mo_f'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['cagr_36mo_f'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['risk_12mo_loss'])
   hpivals.append(json.loads(result3.text)[0]['zip/hpi_forecast']['result']['max_12mo_loss'])
   hpivals.append(json.loads(result.text)[0]['zip/details']['result']['single_family']['market_action_median'])
   hpivals.append(json.loads(result.text)[0]['zip/details']['result']['single_family']['months_of_inventory_median'])
   hpivals.append(json.loads(result.text)[0]['zip/details']['result']['single_family']['days_on_market_median'])

   csvfile.write(','.join([str(i) for i in hpivals])+'\n')
   time.sleep(1)
  except:
   print('error')
   csvfile.write(zipcode+'\n')
   time.sleep(1)