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| import collections, glob, json, math, os, sys |
| import pyarrow as pa, pyarrow.compute as pc, pyarrow.parquet as pq |
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| H = sys.argv[1] |
| DROP_MONITORS = pa.array(["anthropic/claude-opus-4.8", "Qwen/Qwen3.5-27B"]) |
| DROP_COLUMNS = ["p_monitor_test_estimate", "p_monitor_test_answer"] |
| cnt = dict(rows=0, setting=collections.Counter(), bench=collections.Counter(), mon=collections.Counter(), js=collections.Counter()) |
| dropped = 0 |
| for f in sorted(glob.glob(f"{H}/data/reviews-*.parquet")): |
| pf = pq.ParquetFile(f); t = pf.read(); n0 = t.num_rows; rg = math.ceil(n0 / pf.metadata.num_row_groups) |
| drop = pc.or_(pc.equal(t["setting"], "live_traffic"), pc.is_in(t["monitor_model"], value_set=DROP_MONITORS)) |
| t = t.filter(pc.invert(drop)).drop_columns(DROP_COLUMNS) |
| assert t.num_rows, f |
| dropped += n0 - t.num_rows |
| pq.write_table(t, f, compression="zstd", row_group_size=rg) |
| cnt["rows"] += t.num_rows |
| for k, col in (("setting", "setting"), ("bench", "benchmark"), ("mon", "monitor_model")): |
| cnt[k].update(t[col].to_pylist()) |
| cnt["js"].update(f"{s}/{j}" for s, j in zip(t["setting"].to_pylist(), t["judge_status"].to_pylist())) |
| rep = json.load(open(f"{H}/build_report.json")) |
| rep.update(rows=cnt["rows"], rows_by_setting=dict(sorted(cnt["setting"].items())), rows_by_benchmark=dict(sorted(cnt["bench"].items())), |
| rows_by_monitor=dict(sorted(cnt["mon"].items())), judge_status=dict(sorted(cnt["js"].items())), |
| bytes=sum(os.path.getsize(f) for f in glob.glob(f"{H}/data/reviews-*.parquet")), |
| v1_4_patch="2026-11-08: live_traffic setting, Claude Opus 4.8 and Qwen3.5-27B reviews dropped (%d rows), " |
| "with columns p_monitor_test_estimate / p_monitor_test_answer" % dropped) |
| json.dump(rep, open(f"{H}/build_report.json", "w"), indent=1, sort_keys=True) |
| print("dropped", dropped, "rows", cnt["rows"]) |
| print(json.dumps({k: rep[k] for k in ("rows_by_setting", "rows_by_monitor", "rows_by_benchmark", "judge_status")}, indent=1)) |
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