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3.27 kB
| import importlib.util | |
| import sys | |
| from pathlib import Path | |
| from openpyxl import Workbook | |
| # The converter is a standalone script; it lives at submission/ in the working | |
| # repo and at the bundle root in the published code repo. | |
| _ROOT = Path(__file__).resolve().parents[1] | |
| _SCRIPT = next( | |
| p for p in (_ROOT / "submission" / "convert_goldenset_to_jsonl.py", | |
| _ROOT / "convert_goldenset_to_jsonl.py") | |
| if p.exists() | |
| ) | |
| _spec = importlib.util.spec_from_file_location("convert_goldenset_to_jsonl", _SCRIPT) | |
| converter = importlib.util.module_from_spec(_spec) | |
| sys.modules["convert_goldenset_to_jsonl"] = converter | |
| _spec.loader.exec_module(converter) | |
| def _workbook(rows: list[dict]) -> Path: | |
| header = ["case_id", "Link", "full_text", *converter.SCHEMA_FIELDS, | |
| "comment", "original_input"] | |
| wb = Workbook() | |
| ws = wb.active | |
| ws.title = "GOLDENSET" | |
| ws.append(header) | |
| for row in rows: | |
| ws.append([row.get(h) for h in header]) | |
| return wb | |
| def _convert(tmp_path: Path, rows: list[dict]) -> list[dict]: | |
| path = tmp_path / "Goldenset_Test_final.xlsx" | |
| _workbook(rows).save(path) | |
| return converter.convert_workbook(path, fallback={}) | |
| def test_scrape_only_rows_are_dropped(tmp_path: Path) -> None: | |
| records = _convert(tmp_path, [ | |
| {"case_id": "A1", "Link": "http://x", "full_text": "t"}, | |
| {"case_id": "A2", "full_text": "t", "legal_subject_judgement": "Contract"}, | |
| ]) | |
| assert [r["case_id"] for r in records] == ["A2"] | |
| def test_reviewed_rows_without_legal_subject_are_kept(tmp_path: Path) -> None: | |
| records = _convert(tmp_path, [ | |
| # reviewed: real values but no legal subject (the marker convention fails | |
| # here) — kept, because its cells enter the scoring denominators | |
| {"case_id": "B1", "full_text": "t", "trial_end_date": "2024-01-31", | |
| "plaintiffs_all_count": 2, "legal_subject_judgement": "None"}, | |
| # only 'None' markers: contributes no scoreable cell -> dropped, exactly | |
| # like the scoring pipeline's row-inclusion rule | |
| {"case_id": "B2", "full_text": "t", "legal_subject_judgement": "None"}, | |
| ]) | |
| assert [r["case_id"] for r in records] == ["B1"] | |
| # the 'None' marker publishes as null | |
| assert records[0]["legal_subject_judgement"] is None | |
| assert records[0]["trial_end_date"] == "2024-01-31" | |
| def test_zero_values_keep_a_row(tmp_path: Path) -> None: | |
| records = _convert(tmp_path, [ | |
| {"case_id": "C1", "full_text": "t", "plaintiff_loosing_share": 0}, | |
| ]) | |
| assert [r["case_id"] for r in records] == ["C1"] | |
| assert records[0]["plaintiff_loosing_share"] == 0 | |
| def test_currency_only_rows_are_dropped_like_scoring(tmp_path: Path) -> None: | |
| # scoring ignores Currency_* for row inclusion; the converter must match | |
| records = _convert(tmp_path, [ | |
| {"case_id": "D1", "full_text": "t", "Currency_dispute_value_nominal": "CHF"}, | |
| ]) | |
| assert records == [] | |
| def test_nonpecuniary_is_normalised_to_the_schema_literal(tmp_path: Path) -> None: | |
| records = _convert(tmp_path, [ | |
| {"case_id": "E1", "full_text": "t", "legal_subject_judgement": "Claim", | |
| "dispute_value_nominal": "Nonpecuniary"}, | |
| ]) | |
| assert records[0]["dispute_value_nominal"] == "nonpecuniary" | |