print

script.py

@@ -124,6 +124,18 @@ def download_package(package_name, path_to_save='packages'):
 
 ### The part below is used to define and test your solution.
 
+def save_submission(submission, path):
+    """
+    Saves the submission to a specified path.
+
+    Parameters:
+    submission (List[Dict[]]): The submission to save.
+    path (str): The path to save the submission to.
+    """
+    sub = pd.DataFrame(submission, columns=["__key__", "wf_vertices", "wf_edges", "edge_semantics"])
+    sub.to_parquet(path)
+    print(f"Submission saved to {path}")
+
 if __name__ == "__main__":
     from handcrafted_solution import predict
     print ("------------ Loading dataset------------ ")
@@ -139,7 +151,10 @@ if __name__ == "__main__":
                         'wf_edges': pred_edges,
                         'edge_semantics': semantics,
                     })
+        if i % 100 == 0:
+            # incrementally save the results in case we run out of time
+            print(f"Processed {i} samples")
+            # save_submission(solution, Path(params['output_path']) / "submission.parquet")
     print('------------ Saving results ---------------')
-    sub = pd.DataFrame(solution, columns=["__key__", "wf_vertices", "wf_edges", "edge_semantics"])
-    sub.to_parquet(Path(params['output_path']) / "submission.parquet")
+    save_submission(solution, Path(params['output_path']) / "submission.parquet")
     print("------------ Done ------------ ")