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changed function name

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Jun-te Kim 2026-05-12 10:54:45 +00:00
parent bec5c4f3c3
commit 35fea20fc7
2 changed files with 9 additions and 10 deletions
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6
backend/address2UPRN/main.py
View file

@ -18,7 +18,7 @@ from backend.utils.addressMatch import (
AddressMatch, AddressMatch,
get_uprn_candidates, get_uprn_candidates,
) )
from backend.address2UPRN.scoring import df_has_single_uprn from backend.address2UPRN.scoring import all_uprns_match
from datatypes.epc.domain.historic_epc_matching import ( from datatypes.epc.domain.historic_epc_matching import (
match_addresses_for_postcode, match_addresses_for_postcode,
) )
@ -98,7 +98,7 @@ def get_uprn_with_epc_df(
top_rank_df = scored_df[scored_df["lexirank"] == 1] top_rank_df = scored_df[scored_df["lexirank"] == 1]
# If rank-1 rows do not agree on a single UPRN → ambiguous # If rank-1 rows do not agree on a single UPRN → ambiguous
if not df_has_single_uprn(top_rank_df, uprn=top_rank_df.iloc[0]["uprn"]): if not all_uprns_match(top_rank_df, target_uprn=top_rank_df.iloc[0]["uprn"]):
return None return None
address = top_rank_df["address"].values[0] address = top_rank_df["address"].values[0]
@ -207,7 +207,7 @@ def resolve_uprns_for_postcode_group(
top_rank_df = scored_df[scored_df["lexirank"] == 1] top_rank_df = scored_df[scored_df["lexirank"] == 1]
if not df_has_single_uprn(top_rank_df, top_rank_df.iloc[0]["uprn"]): if not all_uprns_match(top_rank_df, top_rank_df.iloc[0]["uprn"]):
results.append( results.append(
{ {
"found_uprn": None, "found_uprn": None,

13
backend/address2UPRN/scoring.py
View file

@ -3,12 +3,11 @@ import pandas as pd
from backend.utils.addressMatch import AddressMatch from backend.utils.addressMatch import AddressMatch
def df_has_single_uprn(df: pd.DataFrame, uprn: str, column: str = "uprn") -> bool: def all_uprns_match(
""" df: pd.DataFrame,
Returns True if all non-null UPRNs in df match the given uprn. target_uprn: str,
Returns False otherwise. column: str = "uprn",
""" ) -> bool:
if column not in df.columns: if column not in df.columns:
return False return False
@ -17,7 +16,7 @@ def df_has_single_uprn(df: pd.DataFrame, uprn: str, column: str = "uprn") -> boo
if len(uprns) == 0: if len(uprns) == 0:
return False return False
return len(uprns) == 1 and uprns[0] == str(uprn) return len(uprns) == 1 and uprns[0] == str(target_uprn)
def get_uprn_candidates( def get_uprn_candidates(