#!/usr/bin/env python3 from __future__ import annotations import argparse import ast import hashlib import json import re import subprocess import sys import xml.etree.ElementTree as ET from pathlib import Path FLOAT_RE = re.compile(r"(? bool: name = path.name.lower() return ( any(k in name for k in ("summary", "result", "report", "diagnosis")) or path.suffix.lower() in {".txt", ".csv", ".xy", ".result"} ) def is_nonempty_file(path: Path) -> bool: return path.exists() and path.is_file() and path.stat().st_size > 0 def read_text(path: Path) -> str: return path.read_text(encoding="utf-8", errors="ignore") def parse_floats(text: str) -> list[float]: out: list[float] = [] for token in FLOAT_RE.findall(text): try: out.append(float(token)) except (TypeError, ValueError): continue return out def write_result(path: Path, value: int) -> None: path.parent.mkdir(parents=True, exist_ok=True) path.write_text(json.dumps({"result": int(1 if value else 0)}, ensure_ascii=False) + "\n", encoding="utf-8") def sha256(path: Path) -> str: return hashlib.sha256(path.read_bytes()).hexdigest() def valid_xdmf(path: Path, expected_h5: str) -> bool: try: root = ET.parse(path).getroot() except (ET.ParseError, OSError): return False hdf_items = [ (node.text or "").strip() for node in root.iter() if node.tag.endswith("DataItem") and node.attrib.get("Format", "").upper() == "HDF" ] return bool(hdf_items) and all(item.startswith(expected_h5 + ":/") for item in hdf_items) def parse_report(path: Path) -> dict[str, object]: data: dict[str, object] = {} for raw_line in read_text(path).splitlines(): line = raw_line.strip() if (not line) or line.startswith("#"): continue parts = [p.strip() for p in line.split(",")] if len(parts) >= 3 and parts[0] in ("job_a", "job_b"): vals_1 = parse_floats(parts[1]) vals_2 = parse_floats(parts[2]) if vals_1 and vals_2: data[parts[0]] = (vals_1[0], vals_2[0]) continue if len(parts) >= 2 and parts[0] in ("Ratio_Mises", "Ratio_Displacement"): vals = parse_floats(parts[1]) if vals: data[parts[0]] = vals[0] return data def check_task(root: Path) -> bool: required = [ "job_a.py", "job_b.py", "run_pipeline.py", "compare.py", ] for rel in required: if not is_nonempty_file(root / rel): return False expected_job_hashes = { "job_a.py": "f09fb0fb7c90b5fe53135cc540c246f7398699455d98eecae12ef2120a5d205d", "job_b.py": "5ec8262a3a1fcdbce13175651d6b4cf8b53e2b0694e4eef084ba6c2fcbe712af", } if any(sha256(root / name) != digest for name, digest in expected_job_hashes.items()): return False pipeline_source = read_text(root / "run_pipeline.py") compare_source = read_text(root / "compare.py") try: ast.parse(pipeline_source, filename=str(root / "run_pipeline.py")) ast.parse(compare_source, filename=str(root / "compare.py")) except SyntaxError: return False generated = [ "job_a.xdmf", "job_a.h5", "job_a_metrics.json", "job_b.xdmf", "job_b.h5", "job_b_metrics.json", "comparison_report.txt", ] for rel in generated: (root / rel).unlink(missing_ok=True) try: pipeline = subprocess.run( [sys.executable, str(root / "run_pipeline.py")], cwd=root, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, timeout=300, check=False, ) if pipeline.returncode != 0: return False comparison = subprocess.run( [sys.executable, str(root / "compare.py")], cwd=root, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, timeout=60, check=False, ) except (OSError, subprocess.SubprocessError): return False if comparison.returncode != 0 or any(not is_nonempty_file(root / rel) for rel in generated): return False if not valid_xdmf(root / "job_a.xdmf", "job_a.h5") or not valid_xdmf(root / "job_b.xdmf", "job_b.h5"): return False data = parse_report(root / "comparison_report.txt") if "job_a" not in data or "job_b" not in data: return False report_lines = [line.strip() for line in read_text(root / "comparison_report.txt").splitlines() if line.strip()] if len(report_lines) != 4: return False expected_prefixes = ("job_a,", "job_b,", "Ratio_Mises,", "Ratio_Displacement,") if any(not line.startswith(prefix) for line, prefix in zip(report_lines, expected_prefixes)): return False mises_a, uy_a = data["job_a"] mises_b, uy_b = data["job_b"] metrics_a = json.loads(read_text(root / "job_a_metrics.json")) metrics_b = json.loads(read_text(root / "job_b_metrics.json")) if abs(mises_a - float(metrics_a["max_mises_mpa"])) > 1e-6 * max(1.0, abs(mises_a)): return False if abs(uy_a - float(metrics_a["tip_uy_mm"])) > 1e-6 * max(1.0, abs(uy_a)): return False if abs(mises_b - float(metrics_b["max_mises_mpa"])) > 1e-6 * max(1.0, abs(mises_b)): return False if abs(uy_b - float(metrics_b["tip_uy_mm"])) > 1e-6 * max(1.0, abs(uy_b)): return False if not (mises_a > 0.0 and mises_b > mises_a and uy_a < 0.0 and uy_b < uy_a): return False if "Ratio_Mises" not in data or abs(float(data["Ratio_Mises"]) - 2.0) > 0.02: return False if "Ratio_Displacement" not in data or abs(float(data["Ratio_Displacement"]) - 2.0) > 0.02: return False return True def evaluate() -> int: root = Path("/home/user/Desktop") try: ok = check_task(root) except Exception: ok = False return 1 if ok else 0 def main() -> int: result = evaluate() print("True" if result == 1 else "False") return 0 if __name__ == "__main__": raise SystemExit(main())