Model/etl/customers/vander_elliot/single_property_pilot.py
2024-05-02 18:33:25 +01:00

56 lines
1.3 KiB
Python

import pandas as pd
from utils.s3 import read_excel_from_s3
from utils.s3 import save_csv_to_s3
PORTFOLIO_ID = 77
USER_ID = 8
patches = [
{
"address": "79 Perryn Road",
"postcode": "W3 7LT",
"roof-description": "Pitched, no insulation (assumed)"
}
]
def app():
asset_list = [
{
'uprn': 12103117,
"address": "79 Perryn Road",
"postcode": "W3 7LT",
},
]
asset_list = pd.DataFrame(asset_list)
# Store the asset list in s3
filename = f"{USER_ID}/{PORTFOLIO_ID}/pilot.csv"
save_csv_to_s3(
dataframe=asset_list,
bucket_name="retrofit-plan-inputs-dev",
file_name=filename
)
# Store patches in s3
patches_filename = f"{USER_ID}/{PORTFOLIO_ID}/patches.json"
save_csv_to_s3(
dataframe=pd.DataFrame(patches),
bucket_name="retrofit-plan-inputs-dev",
file_name=patches_filename
)
body = {
"portfolio_id": str(PORTFOLIO_ID),
"housing_type": "Private",
"goal": "Increase EPC",
"goal_value": "B",
"trigger_file_path": filename,
"already_installed_file_path": "",
"patches_file_path": patches_filename,
"non_invasive_recommendations_file_path": "",
"budget": None,
}
print(body)