File size: 3,273 Bytes
2e511b5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | 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"
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