You caught me trying to escape some embarrassment. Here's an example: To set some context: The code handles isolated execution of machine learning code. Origi

You caught me trying to escape some embarrassment. Here's an example: To set some context: The code handles isolated execution of machine learning code. Original version: def run_code(code, timeout=3600): try: p = Process(target=exec, args=(code,)) p.start() p.join(timeout) if p.is_alive(): p.terminate() return "Timeout" return "Success" except Exception as e: return f"Failed: {str(e)}" New version: class ProcessExecutor(Executor): def __init__(self, execution_id: str, code: str, working_dir: Path, dataset: pd.DataFrame, timeout: int = 3600): super().__init__(code, timeout) self.working_dir = Path(working_dir).resolve() / execution_id self.working_dir.mkdir(parents=True, exist_ok=True) self.dataset = dataset def run(self) -> ExecutionResult: start_time = time.time() code_file: Path = self.working_dir / self.code_file_name with open(code_file, "w") as f: f.write(self.code) try: process = subprocess.Popen( [sys.executable, str(code_file)], stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=str(self.working_dir), text=True, ) stdout, stderr = process.communicate(timeout=self.timeout) return ExecutionResult( term_out=[stdout], exec_time=time.time() - start_time, model_artifacts=self._collect_artifacts(), performance=extract_performance(stdout), ) except subprocess.TimeoutExpired: process.kill() return ExecutionResult( term_out=[], exec_time=self.timeout, exception=TimeoutError( f"Execution exceeded {self.timeout}s timeout" ), )