save best programs in checkpoints

Author: codelion

README.md

@@ -76,6 +76,7 @@ When resuming from a checkpoint:
 - The system loads all previously evolved programs and their metrics
 - Checkpoint numbering continues from where it left off (e.g., if loaded from checkpoint_50, the next checkpoint will be checkpoint_60)
 - All evolution state is preserved (best programs, feature maps, archives, etc.)
+- Each checkpoint directory contains a copy of the best program at that point in time
 
 Example workflow with checkpoints:
 
@@ -91,6 +92,32 @@ python openevolve-run.py examples/function_minimization/initial_program.py \
   --checkpoint examples/function_minimization/openevolve_output/checkpoints/checkpoint_50 \
   --iterations 50
 ```
+
+### Comparing Results Across Checkpoints
+
+Each checkpoint directory contains the best program found up to that point, making it easy to compare solutions over time:
+
+```
+checkpoints/
+  checkpoint_10/
+    best_program.py         # Best program at iteration 10
+    best_program_info.json  # Metrics and details
+    programs/               # All programs evaluated so far
+    metadata.json           # Database state
+  checkpoint_20/
+    best_program.py         # Best program at iteration 20
+    ...
+```
+
+You can compare the evolution of solutions by examining the best programs at different checkpoints:
+
+```bash
+# Compare best programs at different checkpoints
+diff -u checkpoints/checkpoint_10/best_program.py checkpoints/checkpoint_20/best_program.py
+
+# Compare metrics
+cat checkpoints/checkpoint_*/best_program_info.json | grep -A 10 metrics
+```
 ### Docker
 
 You can also install and execute via Docker:

openevolve/controller.py

@@ -346,17 +346,50 @@ def _log_iteration(
     def _save_checkpoint(self, iteration: int) -> None:
         """
         Save a checkpoint
-
+        
         Args:
             iteration: Current iteration number
         """
         checkpoint_dir = os.path.join(self.output_dir, "checkpoints")
         os.makedirs(checkpoint_dir, exist_ok=True)
-
-        # Save the database
+        
+        # Create specific checkpoint directory
         checkpoint_path = os.path.join(checkpoint_dir, f"checkpoint_{iteration}")
+        os.makedirs(checkpoint_path, exist_ok=True)
+        
+        # Save the database
         self.database.save(checkpoint_path, iteration)
-
+        
+        # Save the best program found so far
+        best_program = None
+        if self.database.best_program_id:
+            best_program = self.database.get(self.database.best_program_id)
+        else:
+            best_program = self.database.get_best_program()
+            
+        if best_program:
+            # Save the best program at this checkpoint
+            best_program_path = os.path.join(checkpoint_path, f"best_program{self.file_extension}")
+            with open(best_program_path, "w") as f:
+                f.write(best_program.code)
+                
+            # Save metrics
+            best_program_info_path = os.path.join(checkpoint_path, "best_program_info.json")
+            with open(best_program_info_path, "w") as f:
+                import json
+                json.dump({
+                    "id": best_program.id,
+                    "generation": best_program.generation,
+                    "iteration": iteration,
+                    "metrics": best_program.metrics,
+                    "language": best_program.language,
+                    "timestamp": best_program.timestamp,
+                    "saved_at": time.time()
+                }, f, indent=2)
+            
+            logger.info(f"Saved best program at checkpoint {iteration} with metrics: "
+                       f"{', '.join(f'{name}={value:.4f}' for name, value in best_program.metrics.items())}")
+        
         logger.info(f"Saved checkpoint at iteration {iteration} to {checkpoint_path}")
 
     def _save_best_program(self, program: Optional[Program] = None) -> None: