TudorandClaude Opus 4.8
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Schools without KS2/KS4 results (special post-16 institutions, sixth-form centres, PRUs, new schools) come back from the marts LEFT JOIN with NaN in every numeric column. school_info passed those raw pandas values straight into JSONResponse, which renders with allow_nan=False, so the detail endpoint 500d and the frontend turned that into a 404 on every such SEO landing page. Run school_info values through convert_to_native (the same treatment yearly_data already gets), add backend unit tests plus a pytest step in PR checks, and an e2e journey that finds a results-less school via the search API and asserts its page renders. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
"""Regression tests for GET /api/schools/{urn}.
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Schools with no performance rows (special post-16 institutions, sixth-form
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centres, PRUs, brand-new schools) come back from the marts LEFT JOIN with
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NaN in every numeric column. The endpoint must still serialize them — a NaN
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that reaches Starlette's JSONResponse raises ValueError (allow_nan=False)
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and the route 500s, which the frontend then renders as a 404.
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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 _no_results_school_df() -> pd.DataFrame:
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"""One school row as produced by the marts query for a school with no
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performance data: GIAS/location fields partly populated, every
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results-linked column NaN (including year)."""
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return pd.DataFrame(
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[
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{
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"urn": 150275,
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"school_name": "West London Performing Arts Academy",
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"phase": "Secondary",
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"school_type": "Special post 16 institution",
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"trust_name": None,
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"religious_denomination": "Does not apply",
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"gender": None,
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"age_range": "16-25",
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"admissions_policy": None,
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"capacity": np.nan,
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"gias_total_pupils": np.nan,
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"headteacher_name": None,
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"website": None,
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"ofsted_grade": np.nan,
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"local_authority": "Ealing",
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"address": "268 Northfield Avenue, London, W5 4UB",
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"postcode": "W5 4UB",
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"latitude": 51.4986,
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"longitude": -0.3148,
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"year": np.nan,
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"total_pupils": np.nan,
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"eligible_pupils": np.nan,
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"rwm_expected_pct": np.nan,
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}
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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_school_data", _no_results_school_df)
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monkeypatch.setattr(
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app_module, "get_supplementary_data", lambda db, urn: {}
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)
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return TestClient(app_module.app, raise_server_exceptions=False)
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def test_school_without_performance_rows_returns_200(client):
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resp = client.get("/api/schools/150275")
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assert resp.status_code == 200, resp.text
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def test_nan_gias_fields_serialize_as_null(client):
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info = client.get("/api/schools/150275").json()["school_info"]
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assert info["capacity"] is None
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assert info["total_pupils"] is None
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assert info["school_name"] == "West London Performing Arts Academy"
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