import pandas as pd
from utils.s3 import save_csv_to_s3

asset_list = [
    {
        "address": "4, King Henrys Drive",
        "postcode": "CR0 0PA"
    },
]
portfolio_id = 110
user_id = 8

asset_list = pd.DataFrame(asset_list)

filename = f"{user_id}/{portfolio_id}/asset_list.csv"
save_csv_to_s3(
    dataframe=asset_list,
    bucket_name="retrofit-plan-inputs-dev",
    file_name=filename
)

body1 = {
    "portfolio_id": str(portfolio_id),
    "housing_type": "Private",
    "goal": "Increasing EPC",
    "goal_value": "A",
    "trigger_file_path": filename,
    "already_installed_file_path": "",
    "patches_file_path": "",
    "non_invasive_recommendations_file_path": "",
    "inclusions": [
        "cavity_wall_insulation", "loft_insulation", "air_source_heat_pump", "solar_pv"
    ],
    "budget": None,
    "scenario_name": "Whole House",
    "multi_plan": False,
}
print(body1)
