import PySAM.Pvwattsv8 as pv
import glob
import PySAM.ResourceTools as tools
import csv
import itertools

kW_filename = open('Parcel_Locations.csv', 'r')
file = csv.DictReader(kW_filename)
Kw_list = []
for col in file:
    Kw_list.append(col['kW_per_acre'])
print('Kw per acre:', Kw_list)

weather_folder = "[...]/SAM Downloaded Weather Files"
weather_files = glob.glob(weather_folder + "/*.csv")

# load data from file into dictionaries
for f in weather_files:
    print(f)
    weather_data = tools.SAM_CSV_to_solar_data(f)

    steps_per_year = len(weather_data['year'])
    print(steps_per_year)

    for kW in Kw_list:
        pvSingleOwner_model = pv.default("PVWattsSingleOwner")
        pvSingleOwner_model.value("system_capacity", float(kW))
        pvSingleOwner_model.SolarResource.solar_resource_data = weather_data
        pvSingleOwner_model.execute(0)

        ac_annual = pvSingleOwner_model.Outputs.ac_annual
        print(ac_annual)
        ac_monthly = pvSingleOwner_model.Outputs.ac_monthly
        print(ac_monthly)
        annual_energy = pvSingleOwner_model.Outputs.annual_energy
        print(annual_energy)
        lat = pvSingleOwner_model.Outputs.lat
        print(lat)
        long = pvSingleOwner_model.Outputs.lon
        print(long)