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Khalim Conn-Kowlessar 2024-04-10 17:20:49 +01:00
parent 5ac5cd7737
commit 4e41993455
2 changed files with 2 additions and 17 deletions
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13
etl/customers/immo/pilot/asset_list.py
View file

@ -1,18 +1,7 @@
import os
import pandas as pd import pandas as pd
from tqdm import tqdm
from dotenv import load_dotenv
from utils.s3 import read_excel_from_s3 from utils.s3 import read_excel_from_s3
from backend.SearchEpc import SearchEpc
from epc_api.client import EpcClient
from utils.s3 import save_csv_to_s3 from utils.s3 import save_csv_to_s3
# Read in the .env file in backend
load_dotenv(dotenv_path="backend/.env")
EPC_AUTH_TOKEN = os.getenv("EPC_AUTH_TOKEN")
USER_ID = 8 USER_ID = 8
PORTFOLIO_ID = 70 PORTFOLIO_ID = 70
@ -28,6 +17,7 @@ council_tax_bands = [
{'address': '6 Beech Road', 'postcode': 'DY1 4BP', 'band': 'A'}, {'address': '6 Beech Road', 'postcode': 'DY1 4BP', 'band': 'A'},
{'address': '5 Oaklands', 'postcode': 'B62 0JA', 'band': 'A'}, {'address': '5 Oaklands', 'postcode': 'B62 0JA', 'band': 'A'},
] ]
council_tax_bands = pd.DataFrame(council_tax_bands)
def app(): def app():
@ -41,7 +31,6 @@ def app():
raw_asset_list["address"] = raw_asset_list["Full Address"].str.split(",").str[0] raw_asset_list["address"] = raw_asset_list["Full Address"].str.split(",").str[0]
raw_asset_list["postcode"] = raw_asset_list["Full Address"].str.split(",").str[-1].str.strip() raw_asset_list["postcode"] = raw_asset_list["Full Address"].str.split(",").str[-1].str.strip()
council_tax_bands = pd.DataFrame(council_tax_bands)
asset_list = raw_asset_list.merge(council_tax_bands, how="left", on=["address", "postcode"]) asset_list = raw_asset_list.merge(council_tax_bands, how="left", on=["address", "postcode"])
# Store the data in s3 # Store the data in s3

6
recommendations/optimiser/optimiser_functions.py
View file

@ -20,10 +20,6 @@ def prepare_input_measures(property_recommendations, goal, housing_type):
if not goal_key: if not goal_key:
raise NotImplementedError("Not implemented this gain type - investigate me") raise NotImplementedError("Not implemented this gain type - investigate me")
# We don't include suspended and solid floor insulation as possible measures in private housing, because
# of the need to decant the tenant
ignored_measures = ["suspended_floor_insulation", "solid_floor_insulation"] if housing_type == "Private" else []
input_measures = [] input_measures = []
for recs in property_recommendations: for recs in property_recommendations:
input_measures.append( input_measures.append(
@ -34,7 +30,7 @@ def prepare_input_measures(property_recommendations, goal, housing_type):
"gain": rec[goal_key], "gain": rec[goal_key],
"type": rec["type"] "type": rec["type"]
} }
for rec in recs if rec["type"] not in ignored_measures for rec in recs
] ]
) )