"""Reproduce CrossCodeEval v2 from pinned v1 Parquets and the recorded pass@16 results. pip install pyarrow huggingface_hub python patch.py --out ./rebuilt Use --source-dir PATH to reuse the two original v1 Parquets locally. """ import argparse import copy import hashlib import json import io import tarfile from pathlib import Path import pyarrow as pa import pyarrow.parquet as pq MODELS = {'instruct_successes': 'qwen3-30b-instruct-2507', 'thinking_successes': 'qwen3-30b-thinking'} def rows(path): table = pq.ParquetFile(path) for i in range(table.num_row_groups): yield from table.read_row_group(i).to_pylist() def restrict_images(manifest, names): result = copy.deepcopy(manifest) result['tasks'] = {k: v for k, v in manifest['tasks'].items() if k in names} bundles = {e['bundle'] for t in result['tasks'].values() for e in t['environments']} result['bundles'] = {k: v for k, v in manifest['bundles'].items() if k in bundles} result['missing'] = [] return result def build(source_dir, out, selection_path): selection = json.loads(selection_path.read_text()) out.mkdir(parents=True, exist_ok=True) if any((out / n).exists() for n in ('tasks.parquet', 'archive.parquet')): raise ValueError('Output Parquets already exist; choose an empty output directory') sources = {} for name in ('tasks.parquet', 'archive.parquet'): if source_dir is None: from huggingface_hub import hf_hub_download path = Path(hf_hub_download(selection['repo_id'], selection['source_folder'] + '/' + name, repo_type='dataset', revision=selection['source_revision'], cache_dir=out / '.source-cache')) else: path = source_dir / name with path.open('rb') as handle: digest = hashlib.file_digest(handle, 'sha256').hexdigest() if digest != selection['source_sha256'][name]: raise ValueError('Pinned source hash mismatch: ' + name) sources[name] = path tasks = selection['tasks'] kept = {name for name, task in tasks.items() if task['kept']} assert len(tasks) == 6710 and len(kept) == 863 original_schema = pq.read_schema(sources['tasks.parquet']) image_manifest = json.loads(original_schema.metadata[b'ot.images.v1']) images = restrict_images(image_manifest, kept) assert set(images['tasks']) == kept release = {k: v for k, v in selection.items() if k != 'tasks'} release['selection_file'] = 'assets/selection.json' metadata = {b'ot.release.v2': json.dumps(release).encode(), b'ot.images.v1': json.dumps(images).encode()} schema = original_schema.remove_metadata().append(pa.field('instruct_successes', pa.int64())).append( pa.field('thinking_successes', pa.int64())).append(pa.field('attempts_per_model', pa.int64())).append(pa.field('archive_category', pa.string())) seen, audit = set(), {} with pq.ParquetWriter(out / 'tasks.parquet', schema.with_metadata(metadata), compression='zstd') as retain, \ pq.ParquetWriter(out / 'archive.parquet', schema.with_metadata({b'ot.release.v2': json.dumps(release).encode()}), compression='zstd') as archive: counts = {'retained': 0, 'newly_archived': 0, 'prior_archived': 0} for row in rows(sources['tasks.parquet']): name = row['path'] if name in seen or name not in tasks: raise ValueError('Duplicate or unexpected task: ' + name) seen.add(name) result = tasks[name] assert row['content_sha256'] == result['content_sha256'] for column, model in MODELS.items(): rewards = result['models'][model]['rewards'] assert len(rewards) == 16 and result['models'][model]['complete'] and result['models'][model]['missing'] == 0 row[column] = sum(reward >= 1 for reward in rewards) assert row[column] == result['models'][model]['solved_attempts'] row['attempts_per_model'] = 16 selected = row['instruct_successes'] > 0 or row['thinking_successes'] > 0 assert selected == result['kept'] audit[name] = {'binary_sha256': hashlib.sha256(row['task_binary']).hexdigest(), 'content_sha256': row['content_sha256'], 'kept': selected} if selected: row['stages_passed'] = ','.join(dict.fromkeys(row['stages_passed'].split(',') + ['6'])) retain.write_table(pa.Table.from_pylist([row], schema=schema.with_metadata(metadata))) counts['retained'] += 1 else: row['archive_stage'] = 6 row['archive_reason'] = 'pass16-unsolved: no successful attempt in 16 Instruct and 16 Thinking trials; this is not a confirmed task defect.' row['archive_labels'] = list(row.get('archive_labels') or []) + ['pass16-unsolved'] archive.write_table(pa.Table.from_pylist([row], schema=schema)) counts['newly_archived'] += 1 assert seen == set(tasks) for row in rows(sources['archive.parquet']): assert row['path'] not in seen seen.add(row['path']) # V1's original-source archive predates the validation columns. # Preserve its category and reason while computing its content hash. with tarfile.open(fileobj=io.BytesIO(row['task_binary']), mode='r:*') as archive_tar: files = [(str(Path(m.name)), archive_tar.extractfile(m).read()) for m in archive_tar.getmembers() if m.isfile()] digest = hashlib.sha256() for name, content in sorted(files): encoded = name.encode() digest.update(len(encoded).to_bytes(8, 'big')); digest.update(encoded) digest.update(len(content).to_bytes(8, 'big')); digest.update(content) row['content_sha256'] = digest.hexdigest() row['archive_stage'] = 0 row['stages_passed'] = '' for column in MODELS: row[column] = None row['attempts_per_model'] = None audit[row['path']] = {'binary_sha256': hashlib.sha256(row['task_binary']).hexdigest(), 'content_sha256': row['content_sha256'], 'kept': False} archive.write_table(pa.Table.from_pylist([row], schema=schema)) counts['prior_archived'] += 1 assert counts == {'retained': 863, 'newly_archived': 5847, 'prior_archived': 1053} checked = set() for filename, expected_kept in [('tasks.parquet', True), ('archive.parquet', False)]: for row in rows(out / filename): prior = audit[row['path']] assert row['path'] not in checked and prior['kept'] == expected_kept assert hashlib.sha256(row['task_binary']).hexdigest() == prior['binary_sha256'] assert row['content_sha256'] == prior['content_sha256'] checked.add(row['path']) assert checked == seen print(json.dumps(dict(counts, preserved_task_payloads=len(checked), cached_bundles_reused=len(images['bundles'])))) if __name__ == '__main__': parser = argparse.ArgumentParser(description=__doc__) parser.add_argument('--source-dir', type=Path) parser.add_argument('--out', type=Path, required=True) parser.add_argument('--selection', type=Path, default=Path(__file__).parent / 'assets' / 'selection.json') parser.add_argument('--include-archive', action='store_true', help='Also reconstruct excluded payloads locally') args = parser.parse_args() build(args.source_dir, args.out, args.selection) if not args.include_archive: (args.out / 'archive.parquet').unlink()