from hub.imports.geometry_factory import GeometryFactory
from hub.helpers.dictionaries import Dictionaries
from hub.imports.results.archetype_based_demand import DemandEnricher
import urllib.parse

input_file = "data/cmm_points_function_vintage_surface.csv"
output_file = "output_buildings.csv"

# Database credentials
db_username = 'postgres'
db_password = ''
db_host = 'localhost'
db_port = '5432'
db_name = 'energydemanddb'

# URL-encode username and password
db_username_encoded = urllib.parse.quote_plus(db_username)
db_password_encoded = urllib.parse.quote_plus(db_password)

# Construct the database connection URL
database_url = f'postgresql://{db_username_encoded}:{db_password_encoded}@{db_host}:{db_port}/{db_name}'

# Initialize city object from GeometryFactory
city = GeometryFactory(
    file_type="csv",
    path=input_file,
    centroid_x_field="centroid_x",
    centroid_y_field="centroid_y",
    year_of_construction_field="anne_cnstr",
    function_field="code_util",
    function_to_hub=Dictionaries().montreal_function_to_hub_function,
    total_floor_area_field="supfi_etag"
).city

# Create an instance of DemandEnricher using the database URL
demand_enricher = DemandEnricher(database_url)
demand_enricher.enrich_city(city)
# Close the database connection when done
demand_enricher.close_connection()

print("done")