refactor: rename similar → nearby, so the code says what the section does
The section ranks on distance and is headed "Other schools nearby", but every identifier still called it "similar" — the exact drift that leaves a later reader trusting a name over the behaviour. Mechanical: files, the module, the payload key, the type, the components, the prop. No behaviour change; the suites are unchanged in count and still green. Free to do now because #150 has not merged, so the payload key rename needs no lockstep deploy. Uses of "similar" that are ordinary English — progress measures compared to similar pupils, and unrelated comments — are untouched. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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@@ -15,10 +15,10 @@ card and never reorders the row.
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import numpy as np
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import pandas as pd
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from backend.similar_schools import (
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from backend.nearby_schools import (
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is_secondary_phase,
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radius_miles,
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select_similar,
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select_nearby,
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)
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BASE_LAT, BASE_LON = 51.5000, -0.1000
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@@ -66,7 +66,7 @@ def test_returns_nearest_first():
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_row(100003, "Near", latitude=_at(0.4)),
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_row(100004, "Far", latitude=_at(1.8)),
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)
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result = select_similar(frame, 100001)
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result = select_nearby(frame, 100001)
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assert [s["urn"] for s in result] == [100003, 100002, 100004]
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assert result[0]["distance_miles"] == 0.4
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@@ -81,7 +81,7 @@ def test_a_faith_match_never_outranks_a_closer_school():
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_row(100004, "Sacred Heart RC", religious_denomination="Roman Catholic", latitude=_at(1.2)),
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_row(100005, "St Peter's RC", religious_denomination="Roman Catholic", latitude=_at(1.6)),
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)
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result = select_similar(frame, 100001)
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result = select_nearby(frame, 100001)
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assert result[0]["urn"] == 100002, "the nearest school leads, whatever its intake"
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assert [s["distance_miles"] for s in result] == sorted(s["distance_miles"] for s in result)
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@@ -98,7 +98,7 @@ def test_the_nearest_eligible_school_is_always_shown():
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for n in range(6)
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],
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)
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assert select_similar(frame, 100001)[0]["urn"] == 100002
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assert select_nearby(frame, 100001)[0]["urn"] == 100002
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def test_caps_at_six_taking_the_nearest():
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@@ -106,7 +106,7 @@ def test_caps_at_six_taking_the_nearest():
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_row(100001, "Subject"),
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*[_row(100010 + n, f"Peer {n}", latitude=_at(0.1 * (n + 1))) for n in range(7)],
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)
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result = select_similar(frame, 100001)
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result = select_nearby(frame, 100001)
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assert len(result) == 6
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assert 100016 not in {s["urn"] for s in result}, "the seventh-nearest is the one dropped"
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@@ -116,7 +116,7 @@ def test_fewer_than_two_matches_returns_empty():
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_row(100001, "Subject"),
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_row(100002, "Only neighbour", latitude=_at(0.5)),
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)
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assert select_similar(frame, 100001) == []
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assert select_nearby(frame, 100001) == []
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def test_excludes_the_subject_school():
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@@ -125,7 +125,7 @@ def test_excludes_the_subject_school():
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_row(100002, "A", latitude=_at(0.5)),
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_row(100003, "B", latitude=_at(0.6)),
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)
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assert 100001 not in {s["urn"] for s in select_similar(frame, 100001)}
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assert 100001 not in {s["urn"] for s in select_nearby(frame, 100001)}
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def test_a_school_is_never_listed_twice():
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@@ -134,7 +134,7 @@ def test_a_school_is_never_listed_twice():
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_row(100002, "A", latitude=_at(0.5)),
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_row(100003, "B", latitude=_at(0.6)),
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)
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result = select_similar(frame, 100001)
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result = select_nearby(frame, 100001)
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assert len(result) == len({s["urn"] for s in result})
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@@ -151,7 +151,7 @@ def test_primary_does_not_reach_past_two_miles():
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)
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# One inside the cap is below the minimum, so nothing renders at all —
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# a primary with nothing within two miles has no nearby schools.
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assert select_similar(frame, 100001) == []
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assert select_nearby(frame, 100001) == []
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def test_secondary_reaches_further_than_primary():
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@@ -160,7 +160,7 @@ def test_secondary_reaches_further_than_primary():
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_row(100002, "A", phase="Secondary", latitude=_at(3.0)),
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_row(100003, "B", phase="Secondary", latitude=_at(5.5)),
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)
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assert {s["urn"] for s in select_similar(frame, 100001)} == {100002, 100003}
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assert {s["urn"] for s in select_nearby(frame, 100001)} == {100002, 100003}
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def test_the_cap_follows_the_phase():
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@@ -183,8 +183,8 @@ def test_selective_never_meets_non_selective():
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_row(100002, "Comp A", phase="Secondary", admissions_policy="Non-selective", latitude=_at(0.5)),
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_row(100003, "Comp B", phase="Secondary", admissions_policy="Non-selective", latitude=_at(0.6)),
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)
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assert select_similar(frame, 100001) == []
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assert 100001 not in {s["urn"] for s in select_similar(frame, 100002)}
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assert select_nearby(frame, 100001) == []
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assert 100001 not in {s["urn"] for s in select_nearby(frame, 100002)}
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def test_special_schools_match_only_each_other():
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@@ -193,8 +193,8 @@ def test_special_schools_match_only_each_other():
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_row(100002, "Mainstream A", latitude=_at(0.5)),
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_row(100003, "Mainstream B", latitude=_at(0.6)),
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)
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assert select_similar(frame, 100001) == []
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assert select_similar(frame, 100002) == []
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assert select_nearby(frame, 100001) == []
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assert select_nearby(frame, 100002) == []
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def test_boys_never_meets_girls():
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@@ -204,7 +204,7 @@ def test_boys_never_meets_girls():
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_row(100003, "Mixed School", gender="Mixed", latitude=_at(0.6)),
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_row(100004, "Another Mixed", gender="Mixed", latitude=_at(0.7)),
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)
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urns = {s["urn"] for s in select_similar(frame, 100001)}
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urns = {s["urn"] for s in select_nearby(frame, 100001)}
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assert 100002 not in urns
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assert urns == {100003, 100004}
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@@ -217,7 +217,7 @@ def test_closed_schools_and_missing_coordinates_are_dropped():
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_row(100004, "Good A", latitude=_at(0.6)),
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_row(100005, "Good B", latitude=_at(0.7)),
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)
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assert {s["urn"] for s in select_similar(frame, 100001)} == {100004, 100005}
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assert {s["urn"] for s in select_nearby(frame, 100001)} == {100004, 100005}
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def test_all_through_is_offered_on_both_phase_sides():
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@@ -226,14 +226,14 @@ def test_all_through_is_offered_on_both_phase_sides():
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_row(100002, "All through", phase="All-through", latitude=_at(0.5)),
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_row(100003, "Primary peer", phase="Primary", latitude=_at(0.6)),
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)
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assert 100002 in {s["urn"] for s in select_similar(frame, 100001)}
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assert 100002 in {s["urn"] for s in select_nearby(frame, 100001)}
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secondary = _frame(
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_row(100010, "Secondary subject", phase="Secondary"),
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_row(100002, "All through", phase="All-through", latitude=_at(0.5)),
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_row(100011, "Secondary peer", phase="Secondary", latitude=_at(0.6)),
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)
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assert 100002 in {s["urn"] for s in select_similar(secondary, 100010)}
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assert 100002 in {s["urn"] for s in select_nearby(secondary, 100010)}
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def test_sixteen_plus_is_matched_against_secondary_not_primary():
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@@ -248,7 +248,7 @@ def test_sixteen_plus_is_matched_against_secondary_not_primary():
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_row(100003, "Nearby College", phase="16 plus", latitude=_at(0.6)),
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_row(100004, "Nearby Primary", phase="Primary", latitude=_at(0.1)),
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)
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result = select_similar(frame, 100001)
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result = select_nearby(frame, 100001)
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urns = {s["urn"] for s in result}
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assert 100004 not in urns, "a primary school is not a peer for a sixth form"
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assert urns == {100002, 100003}
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@@ -278,7 +278,7 @@ def test_shared_lists_only_what_is_actually_shared():
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_row(100003, "Faith differs", phase="Secondary", gender="Mixed",
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religious_denomination="Church of England", admissions_policy="Non-selective", latitude=_at(0.6)),
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)
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by_urn = {s["urn"]: s for s in select_similar(frame, 100001)}
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by_urn = {s["urn"]: s for s in select_nearby(frame, 100001)}
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assert by_urn[100002]["shared"] == ["Mixed", "Non-selective", "No religious character"]
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assert by_urn[100003]["shared"] == ["Mixed", "Non-selective"]
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@@ -289,7 +289,7 @@ def test_a_shared_faith_is_named():
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_row(100002, "Also RC", religious_denomination="Roman Catholic", latitude=_at(0.4)),
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_row(100003, "Secular", religious_denomination="None", latitude=_at(0.5)),
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)
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by_urn = {s["urn"]: s for s in select_similar(frame, 100001)}
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by_urn = {s["urn"]: s for s in select_nearby(frame, 100001)}
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assert "Roman Catholic" in by_urn[100002]["shared"]
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assert by_urn[100003]["shared"] == ["Mixed"]
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@@ -300,7 +300,7 @@ def test_shared_is_empty_when_nothing_is_shared():
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_row(100002, "A", gender="Mixed", religious_denomination="None", latitude=_at(0.4)),
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_row(100003, "B", gender="Mixed", religious_denomination="Church of England", latitude=_at(0.5)),
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)
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assert all(s["shared"] == [] for s in select_similar(frame, 100001))
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assert all(s["shared"] == [] for s in select_nearby(frame, 100001))
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def test_no_tier_is_reported_because_there_are_no_tiers():
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@@ -309,7 +309,7 @@ def test_no_tier_is_reported_because_there_are_no_tiers():
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_row(100002, "A", latitude=_at(0.4)),
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_row(100003, "B", latitude=_at(0.5)),
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)
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assert all("tier" not in s for s in select_similar(frame, 100001))
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assert all("tier" not in s for s in select_nearby(frame, 100001))
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def test_metric_follows_the_phase_side_not_the_neighbour():
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@@ -318,7 +318,7 @@ def test_metric_follows_the_phase_side_not_the_neighbour():
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_row(100002, "A", phase="Secondary", attainment_8_score=52.8, latitude=_at(0.5)),
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_row(100003, "B", phase="Secondary", attainment_8_score=np.nan, latitude=_at(0.6)),
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)
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by_urn = {s["urn"]: s for s in select_similar(frame, 100001)}
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by_urn = {s["urn"]: s for s in select_nearby(frame, 100001)}
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assert by_urn[100002]["metric_key"] == "attainment_8_score"
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assert by_urn[100002]["metric_value"] == 52.8
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assert by_urn[100002]["metric_year"] == 202425
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@@ -331,7 +331,7 @@ def test_values_are_json_safe_native_types():
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_row(100002, "A", latitude=_at(0.5)),
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_row(100003, "B", latitude=_at(0.6)),
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)
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for school in select_similar(frame, 100001):
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for school in select_nearby(frame, 100001):
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assert isinstance(school["urn"], int)
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assert isinstance(school["distance_miles"], float)
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assert not isinstance(school["metric_value"], np.generic)
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@@ -366,7 +366,7 @@ def client(monkeypatch):
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def test_detail_payload_carries_nearby_schools(client):
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resp = client.get("/api/schools/100001")
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assert resp.status_code == 200, resp.text
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similar = resp.json()["similar_schools"]
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similar = resp.json()["nearby_schools"]
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assert [s["school_name"] for s in similar] == ["Neighbour A", "Neighbour B"]
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assert similar[0]["metric_key"] == "rwm_expected_pct"
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@@ -377,7 +377,7 @@ def test_a_failure_in_selection_does_not_break_the_page(client, monkeypatch):
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def _explode(*args, **kwargs):
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raise ValueError("selection blew up")
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monkeypatch.setattr(app_module, "select_similar", _explode)
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monkeypatch.setattr(app_module, "select_nearby", _explode)
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resp = client.get("/api/schools/100001")
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assert resp.status_code == 200, resp.text
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assert resp.json()["similar_schools"] == []
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assert resp.json()["nearby_schools"] == []
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