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changed function name
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parent
bec5c4f3c3
commit
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2 changed files with 9 additions and 10 deletions
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@ -18,7 +18,7 @@ from backend.utils.addressMatch import (
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AddressMatch,
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get_uprn_candidates,
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)
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from backend.address2UPRN.scoring import df_has_single_uprn
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from backend.address2UPRN.scoring import all_uprns_match
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from datatypes.epc.domain.historic_epc_matching import (
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match_addresses_for_postcode,
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)
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@ -98,7 +98,7 @@ def get_uprn_with_epc_df(
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top_rank_df = scored_df[scored_df["lexirank"] == 1]
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# If rank-1 rows do not agree on a single UPRN → ambiguous
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if not df_has_single_uprn(top_rank_df, uprn=top_rank_df.iloc[0]["uprn"]):
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if not all_uprns_match(top_rank_df, target_uprn=top_rank_df.iloc[0]["uprn"]):
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return None
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address = top_rank_df["address"].values[0]
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@ -207,7 +207,7 @@ def resolve_uprns_for_postcode_group(
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top_rank_df = scored_df[scored_df["lexirank"] == 1]
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if not df_has_single_uprn(top_rank_df, top_rank_df.iloc[0]["uprn"]):
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if not all_uprns_match(top_rank_df, top_rank_df.iloc[0]["uprn"]):
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results.append(
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{
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"found_uprn": None,
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@ -3,12 +3,11 @@ import pandas as pd
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from backend.utils.addressMatch import AddressMatch
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def df_has_single_uprn(df: pd.DataFrame, uprn: str, column: str = "uprn") -> bool:
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"""
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Returns True if all non-null UPRNs in df match the given uprn.
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Returns False otherwise.
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"""
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def all_uprns_match(
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df: pd.DataFrame,
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target_uprn: str,
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column: str = "uprn",
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) -> bool:
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if column not in df.columns:
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return False
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@ -17,7 +16,7 @@ def df_has_single_uprn(df: pd.DataFrame, uprn: str, column: str = "uprn") -> boo
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if len(uprns) == 0:
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return False
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return len(uprns) == 1 and uprns[0] == str(uprn)
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return len(uprns) == 1 and uprns[0] == str(target_uprn)
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def get_uprn_candidates(
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