feat(api): drive has_sixth_form filter and payloads from GIAS flag
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
+9
-4
@@ -416,10 +416,14 @@ async def get_schools(
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df_latest = df_latest[df_latest["gender"].str.lower() == gender.lower()]
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df_latest = df_latest[df_latest["gender"].str.lower() == gender.lower()]
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if admissions_policy:
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if admissions_policy:
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df_latest = df_latest[df_latest["admissions_policy"].str.lower() == admissions_policy.lower()]
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df_latest = df_latest[df_latest["admissions_policy"].str.lower() == admissions_policy.lower()]
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if has_sixth_form == "yes":
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# GIAS OfficialSixthForm flag (dim_school.has_sixth_form). NULL (flag not
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df_latest = df_latest[df_latest["age_range"].str.contains("18", na=False)]
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# yet populated by the pipeline) is treated as "no sixth form".
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elif has_sixth_form == "no":
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if has_sixth_form in ("yes", "no"):
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df_latest = df_latest[~df_latest["age_range"].str.contains("18", na=False)]
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if "has_sixth_form" in df_latest.columns:
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flag = df_latest["has_sixth_form"].eq(True)
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else: # DB predates the pipeline re-run — fall back to age range
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flag = df_latest["age_range"].str.contains("18", na=False)
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df_latest = df_latest[flag if has_sixth_form == "yes" else ~flag]
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# Include key result metrics for display on cards
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# Include key result metrics for display on cards
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location_cols = ["latitude", "longitude"]
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location_cols = ["latitude", "longitude"]
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@@ -596,6 +600,7 @@ async def get_school_details(request: Request, urn: int):
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"address": latest.get("address", ""),
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"address": latest.get("address", ""),
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"religious_denomination": latest.get("religious_denomination", ""),
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"religious_denomination": latest.get("religious_denomination", ""),
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"age_range": latest.get("age_range", ""),
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"age_range": latest.get("age_range", ""),
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"has_sixth_form": latest.get("has_sixth_form"),
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"latitude": latest.get("latitude"),
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"latitude": latest.get("latitude"),
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"longitude": latest.get("longitude"),
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"longitude": latest.get("longitude"),
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"phase": latest.get("phase"),
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"phase": latest.get("phase"),
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@@ -125,6 +125,7 @@ _MAIN_QUERY = text("""
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s.religious_character AS religious_denomination,
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s.religious_character AS religious_denomination,
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s.gender,
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s.gender,
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s.age_range,
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s.age_range,
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s.has_sixth_form,
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s.admissions_policy,
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s.admissions_policy,
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s.capacity,
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s.capacity,
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s.total_pupils AS gias_total_pupils,
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s.total_pupils AS gias_total_pupils,
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@@ -543,6 +543,7 @@ SCHOOL_COLUMNS = [
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"postcode",
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"postcode",
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"religious_denomination",
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"religious_denomination",
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"age_range",
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"age_range",
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"has_sixth_form",
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"gender",
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"gender",
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"admissions_policy",
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"admissions_policy",
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"ofsted_grade",
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"ofsted_grade",
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@@ -0,0 +1,97 @@
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"""Tests for the GIAS-driven has_sixth_form flag (spec 2026-07-07 §3).
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The filter and payloads must use dim_school.has_sixth_form, not the old
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age_range-contains-"18" substring heuristic. The key regression case is a
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16-19 sixth-form college: flag true, but "16-19" contains no "18".
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"""
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import numpy as np
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import pandas as pd
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import pytest
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from fastapi.testclient import TestClient
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def _schools_df() -> pd.DataFrame:
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"""Latest-year snapshot rows as produced by load_latest_school_data."""
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base = {
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"local_authority": "Testshire",
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"school_type": "Academy",
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"phase": "Secondary",
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"address": "1 Test Street",
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"town": "Testtown",
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"postcode": "TS1 1AA",
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"religious_denomination": None,
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"gender": "Mixed",
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"admissions_policy": None,
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"ofsted_grade": np.nan,
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"ofsted_date": None,
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"ofsted_framework": None,
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"latitude": 51.5,
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"longitude": -0.1,
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"year": 202425,
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"total_pupils": 1000,
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"rwm_expected_pct": np.nan,
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"attainment_8_score": 50.0,
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}
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return pd.DataFrame(
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[
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# 11-18 school WITH a registered sixth form
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{**base, "urn": 100001, "school_name": "Alpha High",
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"age_range": "11-18", "has_sixth_form": True},
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# 16-19 college: old heuristic said NO ("16-19" has no "18"),
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# GIAS flag says YES — must appear in the yes-filter results
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{**base, "urn": 100002, "school_name": "Beta Sixth Form College",
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"age_range": "16-19", "has_sixth_form": True},
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# 11-18 age range on paper but NO registered sixth form:
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# old heuristic said YES, GIAS flag says NO
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{**base, "urn": 100003, "school_name": "Gamma Academy",
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"age_range": "11-18", "has_sixth_form": False},
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# Missing flag (pipeline not yet re-run) — must not crash,
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# must not match the yes-filter
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{**base, "urn": 100004, "school_name": "Delta School",
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"age_range": "11-16", "has_sixth_form": None},
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]
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)
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@pytest.fixture()
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def client(monkeypatch):
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from backend import app as app_module
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monkeypatch.setattr(app_module, "load_latest_school_data", _schools_df)
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monkeypatch.setattr(app_module, "load_school_data", _schools_df)
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monkeypatch.setattr(app_module, "get_supplementary_data", lambda db, urn: {})
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return TestClient(app_module.app, raise_server_exceptions=False)
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def _urns(resp):
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return sorted(s["urn"] for s in resp.json()["schools"])
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def test_filter_yes_uses_flag_not_age_range(client):
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resp = client.get("/api/schools?has_sixth_form=yes")
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assert resp.status_code == 200, resp.text
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# 16-19 college included; 11-18-without-sixth-form excluded
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assert _urns(resp) == [100001, 100002]
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def test_filter_no_uses_flag_not_age_range(client):
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resp = client.get("/api/schools?has_sixth_form=no")
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assert resp.status_code == 200, resp.text
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# Gamma (flag false) and Delta (flag missing => not true)
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assert _urns(resp) == [100003, 100004]
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def test_list_payload_includes_flag(client):
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resp = client.get("/api/schools")
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assert resp.status_code == 200, resp.text
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by_urn = {s["urn"]: s for s in resp.json()["schools"]}
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assert by_urn[100002]["has_sixth_form"] is True
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assert by_urn[100003]["has_sixth_form"] is False
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assert by_urn[100004]["has_sixth_form"] is None
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def test_detail_payload_includes_flag(client):
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resp = client.get("/api/schools/100002")
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assert resp.status_code == 200, resp.text
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assert resp.json()["school_info"]["has_sixth_form"] is True
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