Included cli commands update and serialize to simplify running metadata revision pipeline.

src/hdf5_ops.py

@@ -388,7 +388,7 @@ class HDF5DataOpsManager():
         # Parse value into HDF5 admissible type
         for key in dataset_dict['attributes'].keys():
             value = dataset_dict['attributes'][key] 
-            if isinstance(key, dict):
+            if isinstance(value, dict):
                 dataset_dict['attributes'][key] = utils.convert_attrdict_to_np_structured_array(value)
 
         if not group_name in self.file_obj:
@@ -573,5 +573,22 @@ def get_groups_at_a_level(file: h5py.File, level: str):
     return groups
 
 
+if __name__ == "__main__":
+    if len(sys.argv) < 4:
+        print("Usage: python hdf5_ops.py serialize <path/to/target_file.hdf5> <format=json|yaml>")
+        sys.exit(1)
 
+    if sys.argv[1] == 'serialize':
+        input_hdf5_file = sys.argv[2]
+        file_format = sys.argv[3]
+
+        try:
+            # Call the serialize_metadata function and capture the output path
+            path_to_file = serialize_metadata(input_hdf5_file, output_format=file_format)
+            print(f"Metadata serialized to {path_to_file}")
+        except Exception as e:
+            print(f"An error occurred during serialization: {e}")
+            sys.exit(1)
+
+    #run(sys.argv[2])