mirror of
https://github.com/Hestia-Homes/Model.git
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Take a Postcode value object at the historic EPC repository boundary 🟩
The port accepts a normalised Postcode and rejects malformed/empty ones via Postcode.is_valid() (PostcodeNotFound) — dropping the per-lookup postcodes.io HTTP call and the cross-module use of the private _sanitise_postcode. Mapper helper promoted to public. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Jun-te Kim
parent
23dfb3f899
commit
0536f70162
7 changed files with 69 additions and 135 deletions
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@ -4,7 +4,6 @@ from typing import Optional
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import pandas as pd
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from backend.address2UPRN.scoring import rank_address_similarity
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from backend.utils.addressMatch import AddressMatch
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from datatypes.epc.domain.historic_epc import HistoricEpc
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from utils.pandas_utils import pandas_cell_to_str
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@ -13,7 +12,7 @@ DEFAULT_S3_ROOT = "s3://retrofit-data-dev/historical_epc"
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_EXTRA_COLS = {"lexiscore", "lexirank"}
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def _map_historic_epc_pandas_row_to_domain(row: pd.Series) -> HistoricEpc:
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def map_historic_epc_pandas_row_to_domain(row: pd.Series) -> HistoricEpc:
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kwargs = {
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col.lower(): pandas_cell_to_str(val)
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for col, val in row.items()
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@ -92,15 +91,6 @@ def rank_historic_epc(
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]
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def _sanitise_postcode(postcode: str) -> str:
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cleaned = (postcode or "").upper().replace(" ", "")
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if not cleaned:
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raise ValueError("postcode must contain non-whitespace characters")
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if not AddressMatch.is_valid_postcode(cleaned):
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raise ValueError(f"postcode {cleaned!r} is not a valid UK postcode")
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return cleaned
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def match_addresses_for_postcode(
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user_address: str,
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postcode: str,
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@ -6,11 +6,9 @@ import pandas as pd
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import pytest
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from botocore.exceptions import ClientError
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from datatypes.epc.domain import historic_epc_matching as matcher_mod
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from datatypes.epc.domain.historic_epc_matching import (
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HistoricEpcMatches,
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ScoredHistoricEpc,
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_sanitise_postcode,
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match_addresses_for_postcode,
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)
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from repositories.historic_epc import historic_epc_s3_repository as repo_mod
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@ -126,14 +124,6 @@ def _build_df(rows: list[dict]) -> pd.DataFrame:
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return pd.DataFrame(rows, columns=_FULL_COLUMN_FIELDS)
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@pytest.fixture
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def patch_postcode_valid():
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with patch.object(
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matcher_mod.AddressMatch, "is_valid_postcode", return_value=True
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) as m:
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yield m
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@pytest.fixture
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def patch_read():
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# match_addresses_for_postcode now reads via the historic-EPC repository, so
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@ -142,38 +132,12 @@ def patch_read():
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yield m
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# ---------- _sanitise_postcode ----------
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class TestSanitisePostcode:
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def test_uppercases_and_strips_spaces(self, patch_postcode_valid):
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assert _sanitise_postcode("ab33 8al") == "AB338AL"
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def test_empty_raises(self, patch_postcode_valid):
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with pytest.raises(ValueError, match="non-whitespace"):
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_sanitise_postcode("")
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def test_whitespace_only_raises(self, patch_postcode_valid):
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with pytest.raises(ValueError, match="non-whitespace"):
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_sanitise_postcode(" ")
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def test_invalid_postcode_raises(self):
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with patch.object(
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matcher_mod.AddressMatch, "is_valid_postcode", return_value=False
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):
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with pytest.raises(ValueError, match="not a valid UK postcode"):
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_sanitise_postcode("NONSENSE")
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# ---------- match_addresses_for_postcode ----------
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class TestMatchAddressesForPostcode:
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def test_preserves_row_count_including_zero_score_rows(
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self, patch_read, patch_postcode_valid
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):
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def test_preserves_row_count_including_zero_score_rows(self, patch_read):
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# Disjoint number sets => hard zero. Still kept in matches.
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patch_read.return_value = _build_df(
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[
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@ -185,9 +149,7 @@ class TestMatchAddressesForPostcode:
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assert isinstance(result, HistoricEpcMatches)
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assert len(result.matches) == 2
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def test_top_has_lexirank_one_and_lexiscore_monotone(
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self, patch_read, patch_postcode_valid
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):
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def test_top_has_lexirank_one_and_lexiscore_monotone(self, patch_read):
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patch_read.return_value = _build_df(
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[
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_row("48 GORDON ROAD", "200"), # near miss
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@ -195,20 +157,20 @@ class TestMatchAddressesForPostcode:
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]
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)
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result = match_addresses_for_postcode("47 Gordon Road", "AB33 8AL")
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assert result.top().lexirank == 1
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top = result.top()
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assert top is not None
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assert top.lexirank == 1
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scores = [m.lexiscore for m in result.matches]
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assert scores == sorted(scores, reverse=True)
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def test_s3_key_built_from_default_root(self, patch_read, patch_postcode_valid):
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def test_s3_key_built_from_default_root(self, patch_read):
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patch_read.return_value = _build_df([_row("47 GORDON ROAD", "100")])
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match_addresses_for_postcode("47 Gordon Road", "AB33 8AL")
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patch_read.assert_called_once_with(
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"retrofit-data-dev", "historical_epc/AB338AL/data.csv.gz"
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)
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def test_s3_key_respects_custom_root_with_trailing_slash(
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self, patch_read, patch_postcode_valid
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):
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def test_s3_key_respects_custom_root_with_trailing_slash(self, patch_read):
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patch_read.return_value = _build_df([_row("47 GORDON ROAD", "100")])
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match_addresses_for_postcode(
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"47 Gordon Road",
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@ -219,9 +181,7 @@ class TestMatchAddressesForPostcode:
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"my-bucket", "some/prefix/AB338AL/data.csv.gz"
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)
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def test_missing_postcode_object_yields_empty_matches(
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self, patch_read, patch_postcode_valid
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):
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def test_missing_postcode_object_yields_empty_matches(self, patch_read):
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# A valid postcode with no stored shard is a normal miss, not an error:
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# empty matches, not FileNotFoundError.
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patch_read.side_effect = ClientError(
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@ -231,14 +191,14 @@ class TestMatchAddressesForPostcode:
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assert result.matches == []
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assert result.unambiguous_uprn() is None
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def test_other_client_error_propagates(self, patch_read, patch_postcode_valid):
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def test_other_client_error_propagates(self, patch_read):
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patch_read.side_effect = ClientError(
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{"Error": {"Code": "AccessDenied", "Message": "nope"}}, "GetObject"
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)
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with pytest.raises(ClientError):
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match_addresses_for_postcode("47 Gordon Road", "AB33 8AL")
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def test_empty_user_address_raises(self, patch_postcode_valid):
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def test_empty_user_address_raises(self):
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with pytest.raises(ValueError, match="user_address"):
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match_addresses_for_postcode("", "AB33 8AL")
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@ -248,7 +208,7 @@ class TestMatchAddressesForPostcode:
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class TestUnambiguousUprn:
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def test_exact_match_returns_uprn(self, patch_read, patch_postcode_valid):
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def test_exact_match_returns_uprn(self, patch_read):
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patch_read.return_value = _build_df(
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[
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_row("47 GORDON ROAD", "100"),
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@ -258,7 +218,7 @@ class TestUnambiguousUprn:
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result = match_addresses_for_postcode("47 Gordon Road", "AB33 8AL")
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assert result.unambiguous_uprn() == "100"
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def test_ambiguous_tie_returns_none(self, patch_read, patch_postcode_valid):
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def test_ambiguous_tie_returns_none(self, patch_read):
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# Two duplicate addresses with different UPRNs share rank-1.
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patch_read.return_value = _build_df(
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[
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@ -269,9 +229,7 @@ class TestUnambiguousUprn:
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result = match_addresses_for_postcode("47 Gordon Road", "AB33 8AL")
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assert result.unambiguous_uprn() is None
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def test_all_zero_score_returns_none_even_when_uprn_unique(
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self, patch_read, patch_postcode_valid
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):
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def test_all_zero_score_returns_none_even_when_uprn_unique(self, patch_read):
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# User address has building number 47; no row has 47 -> all hard-zero.
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patch_read.return_value = _build_df(
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[
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@ -283,9 +241,7 @@ class TestUnambiguousUprn:
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assert all(m.lexiscore == 0.0 for m in result.matches)
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assert result.unambiguous_uprn() is None
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def test_nan_uprn_becomes_empty_string_not_nan(
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self, patch_read, patch_postcode_valid
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):
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def test_nan_uprn_becomes_empty_string_not_nan(self, patch_read):
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# Use a real NaN in the UPRN cell.
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patch_read.return_value = _build_df(
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[
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@ -310,7 +266,7 @@ class TestUnambiguousUprn:
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class TestTopHelpers:
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def test_top_n_returns_first_k(self, patch_read, patch_postcode_valid):
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def test_top_n_returns_first_k(self, patch_read):
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patch_read.return_value = _build_df(
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[
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_row("47 GORDON ROAD", "100"),
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@ -3,15 +3,15 @@ from __future__ import annotations
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from abc import ABC, abstractmethod
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from datatypes.epc.domain.historic_epc import HistoricEpc
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from domain.postcode import Postcode
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class PostcodeNotFound(Exception):
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"""The postcode is empty or not a valid UK postcode, so it cannot key a
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historic-EPC lookup.
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"""The postcode is empty, so it cannot key a historic-EPC lookup.
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Distinct from a *valid* postcode that simply has no stored data — that case
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returns an empty list, because a miss is the normal, expected outcome of a
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best-effort historic lookup.
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Distinct from a non-empty postcode that simply has no stored data — that
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case returns an empty list, because a miss is the normal, expected outcome
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of a best-effort historic lookup.
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"""
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@ -20,9 +20,11 @@ class HistoricEpcRepository(ABC):
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sharded by postcode in S3 (``historical_epc/{POSTCODE}/data.csv.gz``).
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A Repo, not a Fetcher (ADR-0011): it reads stored data with no live EPC API
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call. A valid postcode with no stored object returns ``[]``; an unusable
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postcode raises :class:`PostcodeNotFound`.
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call. Takes a normalised :class:`Postcode` value object (so the boundary is
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strictly typed and never re-sanitises a raw string). A non-empty postcode
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with no stored object returns ``[]``; an empty one raises
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:class:`PostcodeNotFound`.
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"""
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@abstractmethod
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def get_for_postcode(self, postcode: str) -> list[HistoricEpc]: ...
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def get_for_postcode(self, postcode: Postcode) -> list[HistoricEpc]: ...
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@ -6,10 +6,8 @@ from datatypes.epc.domain.historic_epc_matching import (
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HistoricEpcMatches,
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rank_historic_epc,
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)
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from repositories.historic_epc.historic_epc_repository import (
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HistoricEpcRepository,
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PostcodeNotFound,
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)
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from domain.postcode import Postcode
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from repositories.historic_epc.historic_epc_repository import HistoricEpcRepository
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class HistoricEpcResolver:
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@ -25,11 +23,12 @@ class HistoricEpcResolver:
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"""All of the postcode's historic EPCs scored against ``user_address``."""
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if not user_address:
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raise ValueError("user_address must be non-empty")
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records = self._repo.get_for_postcode(postcode)
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pc = Postcode(postcode)
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records = self._repo.get_for_postcode(pc)
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matches = rank_historic_epc(records, user_address)
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return HistoricEpcMatches(
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user_address=user_address,
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postcode=postcode.upper().replace(" ", ""),
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postcode=str(pc),
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matches=matches,
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)
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@ -6,10 +6,10 @@ from typing import Optional
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import pandas as pd
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from botocore.exceptions import ClientError
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from domain.postcode import Postcode
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from datatypes.epc.domain.historic_epc import HistoricEpc
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from datatypes.epc.domain.historic_epc_matching import (
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_map_historic_epc_pandas_row_to_domain,
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_sanitise_postcode,
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map_historic_epc_pandas_row_to_domain,
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)
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from repositories.historic_epc.historic_epc_repository import (
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HistoricEpcRepository,
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@ -38,17 +38,15 @@ class HistoricEpcS3Repository(HistoricEpcRepository):
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self._read_csv_gz: CsvGzReader = read_csv_gz or read_csv_gz_from_s3
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self._s3_root = s3_root
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def get_for_postcode(self, postcode: str) -> list[HistoricEpc]:
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try:
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pc = _sanitise_postcode(postcode)
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except ValueError as e:
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raise PostcodeNotFound(str(e)) from e
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def get_for_postcode(self, postcode: Postcode) -> list[HistoricEpc]:
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if not postcode.is_valid():
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raise PostcodeNotFound(f"{postcode.value!r} is not a valid UK postcode")
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bucket, root_prefix = parse_s3_uri(self._s3_root)
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key = f"{root_prefix.rstrip('/')}/{pc}/data.csv.gz"
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key = f"{root_prefix.rstrip('/')}/{postcode}/data.csv.gz"
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try:
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df = self._read_csv_gz(bucket, key)
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except ClientError as e:
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if e.response.get("Error", {}).get("Code") in ("NoSuchKey", "404"):
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return []
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raise
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return [_map_historic_epc_pandas_row_to_domain(row) for _, row in df.iterrows()]
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return [map_historic_epc_pandas_row_to_domain(row) for _, row in df.iterrows()]
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@ -11,6 +11,7 @@ import dataclasses
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from datatypes.epc.domain.historic_epc import HistoricEpc
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from datatypes.epc.domain.historic_epc_matching import HistoricEpcMatches
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from domain.postcode import Postcode
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from repositories.historic_epc.historic_epc_repository import HistoricEpcRepository
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from repositories.historic_epc.historic_epc_resolver import HistoricEpcResolver
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@ -26,9 +27,8 @@ class _FakeRepo(HistoricEpcRepository):
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def __init__(self, by_postcode: dict[str, list[HistoricEpc]]) -> None:
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self._by_postcode = by_postcode
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def get_for_postcode(self, postcode: str) -> list[HistoricEpc]:
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key = postcode.upper().replace(" ", "")
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return self._by_postcode.get(key, [])
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def get_for_postcode(self, postcode: Postcode) -> list[HistoricEpc]:
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return self._by_postcode.get(str(postcode), [])
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def test_match_composes_repo_and_matcher_into_scored_matches():
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@ -50,7 +50,9 @@ def test_match_composes_repo_and_matcher_into_scored_matches():
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assert isinstance(result, HistoricEpcMatches)
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assert result.postcode == "AB338AL"
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assert len(result.matches) == 2
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assert result.top().record.address == "47 GORDON ROAD"
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top = result.top()
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assert top is not None
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assert top.record.address == "47 GORDON ROAD"
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def test_resolve_uprn_returns_unambiguous_match():
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@ -1,23 +1,22 @@
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"""HistoricEpcS3Repository reads per-postcode shards of the old-EPC backup.
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A reference-data lookup, not a Fetcher (ADR-0011): no live EPC API call. The
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adapter reads ``historical_epc/{POSTCODE}/data.csv.gz`` via an injected reader,
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so the tests exercise mapping + key construction + absence against a fake reader
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with no network.
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adapter takes a normalised ``Postcode`` and reads
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``historical_epc/{POSTCODE}/data.csv.gz`` via an injected reader, so the tests
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exercise mapping + key construction + absence against a fake reader with no
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network.
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"""
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from __future__ import annotations
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import dataclasses
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from contextlib import contextmanager
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from unittest.mock import patch
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import pandas as pd
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import pytest
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from botocore.exceptions import ClientError
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from backend.utils.addressMatch import AddressMatch
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from datatypes.epc.domain.historic_epc import HistoricEpc
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from domain.postcode import Postcode
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from repositories.historic_epc.historic_epc_repository import PostcodeNotFound
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from repositories.historic_epc.historic_epc_s3_repository import (
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HistoricEpcS3Repository,
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@ -28,31 +27,24 @@ from repositories.historic_epc.historic_epc_s3_repository import (
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_COLS = [f.name.upper() for f in dataclasses.fields(HistoricEpc)]
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def _row(address: str, uprn: object) -> dict:
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row = {col: "" for col in _COLS}
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def _row(address: str, uprn: object) -> dict[str, object]:
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row: dict[str, object] = {col: "" for col in _COLS}
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row["ADDRESS"] = address
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row["UPRN"] = uprn
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return row
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def _df(rows: list[dict]) -> pd.DataFrame:
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def _df(rows: list[dict[str, object]]) -> pd.DataFrame:
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return pd.DataFrame(rows, columns=_COLS)
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|
||||
@contextmanager
|
||||
def _valid_postcode():
|
||||
with patch.object(AddressMatch, "is_valid_postcode", return_value=True):
|
||||
yield
|
||||
|
||||
|
||||
def test_get_for_postcode_maps_reader_rows_to_historic_epc_records():
|
||||
# Arrange
|
||||
df = _df([_row("47 GORDON ROAD", "100")])
|
||||
repo = HistoricEpcS3Repository(read_csv_gz=lambda bucket, key: df)
|
||||
|
||||
# Act
|
||||
with _valid_postcode():
|
||||
records = repo.get_for_postcode("AB33 8AL")
|
||||
records = repo.get_for_postcode(Postcode("AB33 8AL"))
|
||||
|
||||
# Assert
|
||||
assert len(records) == 1
|
||||
|
|
@ -61,8 +53,8 @@ def test_get_for_postcode_maps_reader_rows_to_historic_epc_records():
|
|||
assert records[0].uprn == "100"
|
||||
|
||||
|
||||
def test_valid_postcode_with_no_stored_object_returns_empty_list():
|
||||
# Arrange — a valid postcode whose shard does not exist in S3.
|
||||
def test_non_empty_postcode_with_no_stored_object_returns_empty_list():
|
||||
# Arrange — a postcode whose shard does not exist in S3.
|
||||
def missing(bucket: str, key: str) -> pd.DataFrame:
|
||||
raise ClientError(
|
||||
{"Error": {"Code": "NoSuchKey", "Message": "missing"}}, "GetObject"
|
||||
|
|
@ -71,14 +63,13 @@ def test_valid_postcode_with_no_stored_object_returns_empty_list():
|
|||
repo = HistoricEpcS3Repository(read_csv_gz=missing)
|
||||
|
||||
# Act
|
||||
with _valid_postcode():
|
||||
records = repo.get_for_postcode("AB33 8AL")
|
||||
records = repo.get_for_postcode(Postcode("AB33 8AL"))
|
||||
|
||||
# Assert — a miss is the normal, expected outcome, not an exception.
|
||||
assert records == []
|
||||
|
||||
|
||||
def test_builds_s3_key_from_sanitised_postcode_and_default_root():
|
||||
def test_builds_s3_key_from_postcode_and_default_root():
|
||||
# Arrange
|
||||
calls: list[tuple[str, str]] = []
|
||||
|
||||
|
|
@ -88,9 +79,8 @@ def test_builds_s3_key_from_sanitised_postcode_and_default_root():
|
|||
|
||||
repo = HistoricEpcS3Repository(read_csv_gz=capture)
|
||||
|
||||
# Act
|
||||
with _valid_postcode():
|
||||
repo.get_for_postcode("ab33 8al")
|
||||
# Act — the Postcode value object has already normalised the casing/spacing.
|
||||
repo.get_for_postcode(Postcode("ab33 8al"))
|
||||
|
||||
# Assert
|
||||
assert calls == [("retrofit-data-dev", "historical_epc/AB338AL/data.csv.gz")]
|
||||
|
|
@ -106,28 +96,26 @@ def test_non_missing_read_error_propagates():
|
|||
repo = HistoricEpcS3Repository(read_csv_gz=denied)
|
||||
|
||||
# Act / Assert
|
||||
with _valid_postcode():
|
||||
with pytest.raises(ClientError):
|
||||
repo.get_for_postcode("AB33 8AL")
|
||||
with pytest.raises(ClientError):
|
||||
repo.get_for_postcode(Postcode("AB33 8AL"))
|
||||
|
||||
|
||||
def test_empty_postcode_raises_postcode_not_found():
|
||||
# Arrange
|
||||
# Arrange — Postcode normalises whitespace away, leaving an empty key.
|
||||
repo = HistoricEpcS3Repository(read_csv_gz=lambda bucket, key: _df([]))
|
||||
|
||||
# Act / Assert — an unusable key, distinct from a valid-but-absent postcode.
|
||||
# Act / Assert — an unusable key, distinct from a non-empty absent postcode.
|
||||
with pytest.raises(PostcodeNotFound):
|
||||
repo.get_for_postcode(" ")
|
||||
repo.get_for_postcode(Postcode(" "))
|
||||
|
||||
|
||||
def test_invalid_postcode_raises_postcode_not_found():
|
||||
# Arrange
|
||||
def test_malformed_postcode_raises_postcode_not_found():
|
||||
# Arrange — a non-empty but malformed postcode can't key a real shard.
|
||||
repo = HistoricEpcS3Repository(read_csv_gz=lambda bucket, key: _df([]))
|
||||
|
||||
# Act / Assert
|
||||
with patch.object(AddressMatch, "is_valid_postcode", return_value=False):
|
||||
with pytest.raises(PostcodeNotFound):
|
||||
repo.get_for_postcode("NONSENSE")
|
||||
with pytest.raises(PostcodeNotFound):
|
||||
repo.get_for_postcode(Postcode("NONSENSE"))
|
||||
|
||||
|
||||
def test_uprn_trailing_dot_zero_is_stripped():
|
||||
|
|
@ -137,8 +125,7 @@ def test_uprn_trailing_dot_zero_is_stripped():
|
|||
repo = HistoricEpcS3Repository(read_csv_gz=lambda bucket, key: df)
|
||||
|
||||
# Act
|
||||
with _valid_postcode():
|
||||
records = repo.get_for_postcode("AB33 8AL")
|
||||
records = repo.get_for_postcode(Postcode("AB33 8AL"))
|
||||
|
||||
# Assert
|
||||
assert records[0].uprn == "151020766"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue