Method run

openevolve/controller.py:249–413

Run the evolution process with improved parallel processing Args: iterations: Maximum number of iterations (uses config if None) target_score: Target score to reach (continues until reached if specified) checkpoint_path: Path to resume from check

(
        self,
        iterations: Optional[int] = None,
        target_score: Optional[float] = None,
        checkpoint_path: Optional[str] = None,
    )

            return f.read()

    async def run(
        self,
        iterations: Optional[int] = None,
        target_score: Optional[float] = None,
        checkpoint_path: Optional[str] = None,
    ) -> Optional[Program]:
        """
        Run the evolution process with improved parallel processing

        Args:
            iterations: Maximum number of iterations (uses config if None)
            target_score: Target score to reach (continues until reached if specified)
            checkpoint_path: Path to resume from checkpoint

        Returns:
            Best program found
        """
        max_iterations = iterations or self.config.max_iterations

        # Determine starting iteration
        start_iteration = 0
        if checkpoint_path and os.path.exists(checkpoint_path):
            self._load_checkpoint(checkpoint_path)
            start_iteration = self.database.last_iteration + 1
            logger.info(f"Resuming from checkpoint at iteration {start_iteration}")
        else:
            start_iteration = self.database.last_iteration

        # Only add initial program if starting fresh (not resuming from checkpoint)
        should_add_initial = (
            start_iteration == 0
            and len(self.database.programs) == 0
            and not any(
                p.code == self.initial_program_code for p in self.database.programs.values()
            )
        )

        if should_add_initial:
            logger.info("Adding initial program to database")
            initial_program_id = str(uuid.uuid4())

            # Evaluate the initial program
            initial_metrics = await self.evaluator.evaluate_program(
                self.initial_program_code, initial_program_id
            )

            initial_program = Program(
                id=initial_program_id,
                code=self.initial_program_code,
                changes_description=self.config.prompt.initial_changes_description,
                language=self.config.language,
                metrics=initial_metrics,
                iteration_found=start_iteration,
            )

            self.database.add(initial_program)

            # Check if combined_score is present in the metrics