fix(api): fall back to legacy name-column query when marts predate code migration
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PR Checks / Frontend Typecheck + Tests (pull_request) Successful in 9m41s
PR Checks / Backend Smoke (pull_request) Successful in 6s
PR Checks / Build Backend (no push) (pull_request) Successful in 19s
PR Checks / Build Frontend (no push) (pull_request) Successful in 47s
PR Checks / Build Pipeline (no push) (pull_request) Successful in 10s
PR Checks / AI Code Review (Claude) (pull_request) Failing after 3m8s
Closes the deploy window flagged by CI review — the backend now works against both the old (name) and new (code) mart schemas. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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@@ -42,3 +42,55 @@ def test_missing_code_columns_are_a_noop():
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out = translate_gias_code_columns(df)
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assert out.iloc[0]["phase"] == "Primary"
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assert out.iloc[0]["status"] == "Open"
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def test_load_school_data_survives_premigration_marts(monkeypatch):
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"""Real prod state until the nightly pipeline first rebuilds the mart with
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the GIAS code columns: marts.dim_school still has the old name columns
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(phase, school_type, religious_character, status, admissions_policy)
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instead of the new *_code columns. The first query raises UndefinedColumn
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on s.phase_code; load_school_data_as_dataframe must retry with the
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legacy name-column query rather than swallow the error and return (and
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then have load_school_data cache) an empty DataFrame."""
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import sqlalchemy.exc
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from backend import data_loader
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data_loader._df_cache = None
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data_loader._df_latest_cache = None
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good_df = pd.DataFrame(
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[
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{
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"urn": 1,
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"school_name": "Legacy School",
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"phase": "Primary",
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"school_type": "Academy",
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"status": "Open",
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}
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]
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)
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calls = []
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def fake_read_sql(query, con):
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calls.append(query)
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if len(calls) == 1:
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raise sqlalchemy.exc.ProgrammingError(
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"(psycopg2.errors.UndefinedColumn) column s.phase_code does not exist",
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None,
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None,
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)
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return good_df.copy()
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monkeypatch.setattr(data_loader.pd, "read_sql", fake_read_sql)
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try:
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df = data_loader.load_school_data_as_dataframe()
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finally:
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data_loader._df_cache = None
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data_loader._df_latest_cache = None
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assert len(calls) == 2, "must retry with the legacy name-column query variant"
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assert calls[1] is data_loader._MAIN_QUERY_LEGACY_NAMES
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assert not df.empty
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assert df["phase"].iloc[0] == "Primary"
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assert df["status"].iloc[0] == "Open"
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