Model/etl/customers/goldman/asset_list.py
2024-04-26 14:06:48 +01:00

63 lines
1.5 KiB
Python

import pandas as pd
from utils.s3 import read_excel_from_s3
from utils.s3 import save_csv_to_s3
PORTFOLIO_ID = 75
USER_ID = 8
def app():
asset_list = [
{
"address": "19 Emily Gardens",
"postcode": "B16 0ED",
},
{
"address": "Flat 6 41 Bradford Street",
"postcode": "B5 6HX",
},
{
"address": "197 FIELD LANE",
"postcode": "B32 4HL",
},
{
"address": "FLAT 4 108 SUMMER ROAD",
"postcode": "B23 6DY",
},
{
"address": "1, St. Benedicts Road",
"postcode": "B10 9DP",
},
{
"address": "29 COOKSEY LANE",
"postcode": "B44 9QL",
},
{
"address": "40 TRITTIFORD ROAD",
"postcode": "B13 0HG",
}
]
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
)
# EPC C portoflio
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": "",
"non_invasive_recommendations_file_path": "",
"budget": None,
}
print(body)