type checking improvements

Author: strawgate

key-value/key-value-aio/src/key_value/aio/adapters/pydantic/adapter.py

@@ -14,8 +14,8 @@
 class PydanticAdapter(BasePydanticAdapter[T]):
     """Adapter around a KVStore-compliant Store that allows type-safe persistence of Pydantic models."""
 
-    # Beartype doesn't like our `type[T] includes a bound on Sequence[...] as the subscript is not checkable at runtime
-    # For just the next 20 or so lines we are no longer bear bros but have no fear, we will be back soon!
+    # Beartype cannot handle the parameterized type annotation (type[T]) used here for this generic adapter.
+    # Using @bear_spray to bypass beartype's runtime checks for this specific method.
     @bear_spray
     def __init__(
         self,
@@ -32,12 +32,19 @@ def __init__(
             default_collection: The default collection to use.
             raise_on_validation_error: Whether to raise a DeserializationError if validation fails during reads. Otherwise,
                                        calls will return None if validation fails.
-        """
 
+        Raises:
+            TypeError: If pydantic_model is a sequence type other than list (e.g., tuple is not supported).
+        """
         self._key_value = key_value
 
         origin = get_origin(pydantic_model)
-        self._is_list_model = origin is not None and isinstance(origin, type) and issubclass(origin, Sequence)
+        self._is_list_model = origin is list
+
+        # Validate that if it's a generic type, it must be a list (not tuple, etc.)
+        if origin is not None and origin is not list:
+            msg = f"Only list[BaseModel] is supported for sequence types, got {pydantic_model}"
+            raise TypeError(msg)
 
         self._type_adapter = TypeAdapter[T](pydantic_model)
         self._default_collection = default_collection

key-value/key-value-sync/src/key_value/sync/code_gen/adapters/pydantic/adapter.py

@@ -17,8 +17,8 @@
 class PydanticAdapter(BasePydanticAdapter[T]):
     """Adapter around a KVStore-compliant Store that allows type-safe persistence of Pydantic models."""
 
-    # Beartype doesn't like our `type[T] includes a bound on Sequence[...] as the subscript is not checkable at runtime
-    # For just the next 20 or so lines we are no longer bear bros but have no fear, we will be back soon!
+    # Beartype cannot handle the parameterized type annotation (type[T]) used here for this generic adapter.
+    # Using @bear_spray to bypass beartype's runtime checks for this specific method.
 
     @bear_spray
     def __init__(
@@ -32,12 +32,19 @@ def __init__(
             default_collection: The default collection to use.
             raise_on_validation_error: Whether to raise a DeserializationError if validation fails during reads. Otherwise,
                                        calls will return None if validation fails.
-        """
 
+        Raises:
+            TypeError: If pydantic_model is a sequence type other than list (e.g., tuple is not supported).
+        """
         self._key_value = key_value
 
         origin = get_origin(pydantic_model)
-        self._is_list_model = origin is not None and isinstance(origin, type) and issubclass(origin, Sequence)
+        self._is_list_model = origin is list
+
+        # Validate that if it's a generic type, it must be a list (not tuple, etc.)
+        if origin is not None and origin is not list:
+            msg = f"Only list[BaseModel] is supported for sequence types, got {pydantic_model}"
+            raise TypeError(msg)
 
         self._type_adapter = TypeAdapter[T](pydantic_model)
         self._default_collection = default_collection