from pathlib import Path
import pandas as pd
import hub.helpers.constants as cte


class Results:
  def __init__(self, city, path):
    self._city = city
    self._path = path

  def print(self):
    print_results = None
    file = 'city name: ' + self._city.name + '\n'
    for building in self._city.buildings:
      heating_results = building.heating[cte.MONTH].rename(columns={'INSEL': f'{building.name} heating Wh'})
      cooling_results = building.cooling[cte.MONTH].rename(columns={'INSEL': f'{building.name} cooling Wh'})
      if print_results is None:
        print_results = heating_results
      else:
        print_results = pd.concat([print_results, heating_results], axis='columns')
      print_results = pd.concat([print_results, cooling_results,
                                 building.lighting_electrical_demand,
                                 building.appliances_electrical_demand,
                                 building.domestic_hot_water_heat_demand], axis='columns')
      file += '\n'
      file += 'name: ' + building.name + '\n'
      file += 'year of construction: ' + str(building.year_of_construction) + '\n'
      file += 'function: ' + building.function + '\n'
      file += 'floor area: ' + str(building.floor_area) + '\n'
      file += 'storeys: ' + str(int(building.eave_height / building.average_storey_height)) + '\n'
      file += 'heated_volume: ' + str(0.85 * building.volume) + '\n'
      file += 'volume: ' + str(building.volume) + '\n'

    full_path_results = Path(self._path / 'demand.csv').resolve()
    print_results.to_csv(full_path_results)
    full_path_metadata = Path(self._path / 'metadata.csv').resolve()
    with open(full_path_metadata, 'w') as metadata_file:
      metadata_file.write(file)