TudorandClaude Fable 5
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get_supplementary_data ran ~5 sequential DB round-trips per URN, so /api/compare scaled at ~37ms/school (measured on staging: 1 school 155ms, 3 schools 220ms, 6 schools 340ms). get_supplementary_data_batch fetches each table once with WHERE urn IN (...) and groups in Python, collapsing 5*N round-trips to a constant 5. get_supplementary_data is now a thin wrapper so the detail endpoint is unchanged; the compare endpoint makes one batched call. Each table degrades independently on failure. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
112 lines
4.0 KiB
Python
112 lines
4.0 KiB
Python
"""get_supplementary_data_batch fetches one query per table for all URNs
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(not ~5 per school) and returns the same per-URN block shape as the
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single-URN function, picking the latest row per URN where relevant."""
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import types
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from backend import data_loader
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from backend.data_loader import get_supplementary_data_batch
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class _FakeQuery:
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"""Records that a query ran and serves canned rows filtered by an in-list."""
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def __init__(self, recorder, model_name, rows):
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self._rec = recorder
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self._model = model_name
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self._rows = rows
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def filter(self, *args, **kwargs):
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return self
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def order_by(self, *args, **kwargs):
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return self
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def all(self):
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self._rec.append(self._model)
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return self._rows
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def first(self):
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self._rec.append(self._model)
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return self._rows[0] if self._rows else None
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class _FakeSession:
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def __init__(self, rows_by_model):
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self.rows_by_model = rows_by_model
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self.queries: list[str] = []
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def query(self, model):
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name = model.__name__
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return _FakeQuery(self.queries, name, self.rows_by_model.get(name, []))
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def rollback(self):
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pass
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def _ofsted_row(urn, date, oe):
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base = {f: None for f in (
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"framework", "inspection_type", "quality_of_education", "behaviour_attitudes",
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"personal_development", "leadership_management", "early_years_provision",
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"sixth_form_provision", "ungraded_outcome", "ungraded_grade",
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"rc_safeguarding_met", "rc_inclusion", "rc_curriculum_teaching", "rc_achievement",
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"rc_attendance_behaviour", "rc_personal_development", "rc_leadership_governance",
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"rc_early_years", "rc_sixth_form", "report_url",
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)}
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base.update(urn=urn, inspection_date=types.SimpleNamespace(isoformat=lambda: date),
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overall_effectiveness=oe, grade_source=None)
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return types.SimpleNamespace(**base)
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def _adm_row(urn, year):
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return types.SimpleNamespace(
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urn=urn, year=year, school_phase="Primary", places_offered=100,
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total_applications=200, first_preference_applications=150,
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first_preference_offers=140, first_preference_offer_pct=93.3,
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oversubscription_ratio=1.5, oversubscribed=True,
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total_offers=100, second_preference_offers=5, third_preference_offers=2,
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cross_la_applications=10, cross_la_offers=3,
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)
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def test_one_query_per_table_and_latest_row_per_urn():
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rows = {
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# URN 1 has two Ofsted rows; the batch must keep the most recent (2023).
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"FactOfstedInspection": [
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_ofsted_row(1, "2023-01-01", 2),
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_ofsted_row(1, "2019-01-01", 3),
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_ofsted_row(2, "2021-06-01", 1),
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],
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"FactAdmissions": [_adm_row(1, 202526), _adm_row(1, 202627), _adm_row(2, 202627)],
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"FactPupilCharacteristics": [],
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"FactDeprivation": [],
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"FactFinance": [],
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}
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session = _FakeSession(rows)
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out = get_supplementary_data_batch(session, [1, 2])
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# Exactly one query per table — five total, regardless of two URNs.
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assert sorted(session.queries) == [
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"FactAdmissions", "FactDeprivation", "FactFinance",
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"FactOfstedInspection", "FactPupilCharacteristics",
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]
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# Latest Ofsted kept per URN
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assert out[1]["ofsted"]["overall_effectiveness"] == 2
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assert out[2]["ofsted"]["overall_effectiveness"] == 1
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# Admissions history grouped per URN, latest exposed as `admissions`
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assert [r["year"] for r in out[1]["admissions_history"]] == [202526, 202627]
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assert out[1]["admissions"]["year"] == 202627
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assert out[2]["admissions_history"] == [{**out[2]["admissions_history"][0]}]
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# Empty tables degrade to the null block, not a crash
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assert out[1]["census"] is None and out[1]["deprivation"] is None
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def test_single_wrapper_matches_batch(monkeypatch):
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session = _FakeSession({"FactOfstedInspection": [_ofsted_row(5, "2022-01-01", 2)]})
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single = data_loader.get_supplementary_data(session, 5)
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assert single["ofsted"]["overall_effectiveness"] == 2
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assert single["admissions_history"] == []
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