chore: improve inline comments and move code

Author: BryanttV

openedx_events/event_bus/avro/deserializer.py

@@ -53,7 +53,7 @@ def _deserialized_avro_record_dict_to_object(data: dict, data_type, deserializer
         if arg_data_type[0] in SIMPLE_PYTHON_TYPE_TO_AVRO_MAPPING:
             return data
 
-        # Complex list items that need recursive deserialization
+        # Complex nested types like List[List[...]], List[Dict[...]], etc.
         item_type = arg_data_type[0]
         return [_deserialized_avro_record_dict_to_object(sub_data, item_type, deserializers) for sub_data in data]
     elif data_type_origin is dict:
@@ -73,10 +73,10 @@ def _deserialized_avro_record_dict_to_object(data: dict, data_type, deserializer
         if key_type is not str:
             raise TypeError("Avro maps only support string keys. The key type must be 'str'.")
 
-        # For complex nested types like Dict[str, Dict[...]], Dict[str, List[...]], etc.
+        # Complex nested types like Dict[str, Dict[...]], Dict[str, List[...]], etc.
         return {
-            k: _deserialized_avro_record_dict_to_object(v, value_type, deserializers)
-            for k, v in data.items()
+            key: _deserialized_avro_record_dict_to_object(value, value_type, deserializers)
+            for key, value in data.items()
         }
     elif hasattr(data_type, "__attrs_attrs__"):
         transformed = {}

openedx_events/event_bus/avro/tests/test_avro.py

@@ -122,8 +122,7 @@ def process_type(type_spec: Any) -> Any:
         defined types.
 
         Args:
-            type_spec (Any): A type specification which might be a string,
-                dict, or list
+            type_spec (Any): A type specification which might be a str, dict, or list
 
         Returns:
            Any: An appropriate test value for the specified type
@@ -166,7 +165,7 @@ def process_type(type_spec: Any) -> Any:
             # Array type (list)
             elif type_name == "array":
                 items = type_spec.get("items")
-                # We crate a list with a single element
+                # We create a list with a single element
                 return [process_type(items)]
 
             # Map type (dictionary/object)
@@ -252,6 +251,10 @@ def generate_test_event_data_for_data_type(data_type: Any) -> dict:  # pragma: n
 
             item_type = args[0]
 
+            # Handle List of simple types, e.g. List[str]
+            if item_type in defaults_per_type:
+                return [defaults_per_type[item_type]]
+
             # Handle List of Dicts, e.g. List[Dict[str, str]]
             if get_origin(item_type) is dict:
                 dict_key_type, dict_value_type = get_args(item_type)
@@ -270,10 +273,6 @@ def generate_test_event_data_for_data_type(data_type: Any) -> dict:  # pragma: n
 
                 return [sample_dict]
 
-            # Handle List of simple types, e.g. List[str]
-            if item_type in defaults_per_type:
-                return [defaults_per_type[item_type]]
-
             # Handle List of attrs classes, e.g. List[EventData]
             item_data = generate_test_event_data_for_data_type(item_type)
             return [item_data]