#!/usr/bin/env python3 """Check the integer-literal property over the whole packaged corpus. The response answers ssUK Q4 -- decimals in Figure 1 versus the integer parameter claim -- with an audit of 156,500 sampled programs finding no non-integer literal, and commits to running it "over the full released corpus so the property is verifiable, not asserted". This is that run: all 4,006,182 programs, read straight out of the parquet shards, no sampling. Reports the counterexamples rather than a verdict. A property that holds on four million programs is worth stating precisely; one that holds on 3,999,998 is worth stating precisely too, and the difference only shows up if the failures are kept. python audit_integer_literals.py --parquet-root ./data \\ --out ./integer_audit.json """ from __future__ import annotations import argparse import json import re import time from collections import Counter from pathlib import Path import pyarrow.parquet as pq OPS = ["extrude", "revolve", "sweep", "loft"] # A float literal is a digit sequence with a decimal point that is not part of an # attribute access. Scientific notation counts too: 1e-3 is not an integer either. FLOAT_RE = re.compile(r"(? None: ap = argparse.ArgumentParser() ap.add_argument("--parquet-root", required=True) ap.add_argument("--out", required=True) ap.add_argument("--examples", type=int, default=20, help="how many offending programs to keep verbatim") args = ap.parse_args() root = Path(args.parquet_root) per_op, examples = {}, [] lo_all, hi_all = 10 ** 9, -10 ** 9 t0 = time.time() for op in OPS: files = sorted((root / op).glob("*.parquet")) n = n_float = 0 lo, hi = 10 ** 9, -10 ** 9 by_split = Counter() for f in files: # Only the program column: the mesh blobs are the bulk of the corpus # and reading them would turn a text scan into an I/O job. for batch in pq.ParquetFile(f).iter_batches(batch_size=4096, columns=["id", "split", "program"]): for rid, split, code in zip(batch["id"].to_pylist(), batch["split"].to_pylist(), batch["program"].to_pylist()): n += 1 if FLOAT_RE.search(code): n_float += 1 by_split[split] += 1 if len(examples) < args.examples: examples.append({"op": op, "id": rid, "split": split, "program": code}) v = INT_RE.findall(code) if v: iv = [int(x) for x in v] lo, hi = min(lo, min(iv)), max(hi, max(iv)) print(f" {op} {f.name}: {n} programs, {n_float} with a float literal, " f"{time.time() - t0:.0f}s", flush=True) per_op[op] = {"programs": n, "with_float_literal": n_float, "by_split": dict(by_split), "integer_range": [lo, hi] if n else None} lo_all, hi_all = min(lo_all, lo), max(hi_all, hi) print(f"{op}: {n} programs, {n_float} with a float literal, " f"integers in [{lo}, {hi}]", flush=True) total = sum(v["programs"] for v in per_op.values()) bad = sum(v["with_float_literal"] for v in per_op.values()) out = {"total_programs": total, "with_float_literal": bad, "pct_with_float_literal": 100.0 * bad / max(1, total), "integer_range": [lo_all, hi_all], "per_operation": per_op, "examples": examples, "elapsed_sec": round(time.time() - t0)} Path(args.out).write_text(json.dumps(out, indent=1)) print(f"\n{total} programs, {bad} containing a float literal " f"({100.0 * bad / max(1, total):.6f}%), integers in [{lo_all}, {hi_all}]") print(f"wrote {args.out}") if __name__ == "__main__": main()