| |
| """Independently re-verify this evalpack: run every gold SQL with DuckDB |
| against the CSVs in tables/ and compare to the expected answers. |
| |
| Usage: python verify.py (exits 1 on any mismatch) |
| """ |
| import json |
| import sys |
| from pathlib import Path |
|
|
| import duckdb |
|
|
| HERE = Path(__file__).parent |
| con = duckdb.connect() |
| for csv in sorted((HERE / "tables").glob("*.csv")): |
| path = str(csv.resolve()).replace("'", "''") |
| con.execute( |
| 'CREATE VIEW "%s" AS SELECT * FROM read_csv_auto(\'%s\')' |
| % (csv.stem, path) |
| ) |
|
|
| failures = 0 |
| total = 0 |
| for line in (HERE / "questions.jsonl").read_text().splitlines(): |
| if not line.strip(): |
| continue |
| q = json.loads(line) |
| total += 1 |
| row = con.execute(q["gold_sql"]).fetchone() |
| observed = row[0] if row else None |
| expected = q["expected_answer"] |
| if q["answer_type"] == "string": |
| ok = str(observed) == str(expected) |
| else: |
| nd = q.get("round_decimals", 0) |
| try: |
| ok = ( |
| observed is not None |
| and abs(round(float(observed), nd) - round(float(expected), nd)) |
| < 1e-9 |
| ) |
| except (TypeError, ValueError): |
| ok = False |
| status = "OK " if ok else "FAIL" |
| if not ok: |
| failures += 1 |
| print(f"{status} {q['id']}: expected={expected} observed={observed}") |
| print(f" {q['gold_sql']}") |
| else: |
| print(f"{status} {q['id']}: {expected}") |
|
|
| print(f"\n{total - failures}/{total} verified exactly") |
| sys.exit(1 if failures else 0) |
|
|
