import pandas as pd from utils.s3 import save_csv_to_s3 EPC_C_PORTFOLIO_ID = 78 EPC_B_PORTFOLIO_ID = 79 USER_ID = 8 def app(): """ This code sets up the asset list for the 9 property portfolio for the pilot :return: """ asset_list = [ { "address": "79 Clare Road", "postcode": "L20 9LZ", "uprn": 41018850, # 3 bedroom property }, { "address": "Flat 1, 29 Bedford Road", "postcode": "L4 5PS", "uprn": 38237316 # Single dewlling converted into two flats }, { "address": "Flat 2, 29 Bedford Road", "postcode": "L4 5PS", "uprn": 38237317 # Single dewlling converted into two flats }, # 7 Flats above a domestic unit { "address": "Flat 1, 2 Linacre Lane", "postcode": "L20 5AH", "uprn": 41052320 }, { "address": "Flat 2, 2 Linacre Lane", "postcode": "L20 5AH", "uprn": 41052321, }, { "address": "Flat 3, 2 Linacre Lane", "postcode": "L20 5AH", "uprn": 41052322, }, { "address": "Flat 4, 2 Linacre Lane", "postcode": "L20 5AH", "uprn": 41222759, }, { "address": "Flat 1, 4 Linacre Lane", "postcode": "L20 5AH", "uprn": 41222760, }, { "address": "Flat 2, 4 Linacre Lane", "postcode": "L20 5AH", "uprn": 41222761, }, { "address": "Flat 3, 4 Linacre Lane", "postcode": "L20 5AH", "uprn": 41212534, }, ] asset_list = pd.DataFrame(asset_list) # Store the asset list in s3 filename = f"{USER_ID}/{EPC_C_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(EPC_C_PORTFOLIO_ID), "housing_type": "Private", "goal": "Increase EPC", "goal_value": "C", "trigger_file_path": filename, "already_installed_file_path": "", "patches_file_path": "", "non_invasive_recommendations_file_path": "", "budget": None, } print(body) # EPC B portoflio body = { "portfolio_id": str(EPC_B_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)