Allow using pydantic for from_dict, schema for FastList

csp/impl/struct.py

@@ -147,6 +147,18 @@ def serializer(val, handler):
 
 
 class Struct(_csptypesimpl.PyStruct, metaclass=StructMeta):
+    @classmethod
+    def type_adapter(cls):
+        internal_type_adapter = getattr(cls, "_pydantic_type_adapter", None)
+        if internal_type_adapter:
+            return internal_type_adapter
+
+        # Late import to avoid autogen issues
+        from pydantic import TypeAdapter
+
+        cls._pydantic_type_adapter = TypeAdapter(cls)
+        return cls._pydantic_type_adapter
+
     @classmethod
     def metadata(cls, typed=False):
         if typed:
@@ -191,7 +203,8 @@ def _obj_from_python(cls, json, obj_type):
         if CspTypingUtils.is_generic_container(obj_type):
             if CspTypingUtils.get_origin(obj_type) in (typing.List, typing.Set, typing.Tuple, FastList):
                 return_type = ContainerTypeNormalizer.normalized_type_to_actual_python_type(obj_type)
-                (expected_item_type,) = obj_type.__args__
+                # We only take the first item, so like for a Tuple, we would ignore arguments after
+                expected_item_type = obj_type.__args__[0]
                 return_type = list if isinstance(return_type, list) else return_type
                 return return_type(cls._obj_from_python(v, expected_item_type) for v in json)
             elif CspTypingUtils.get_origin(obj_type) is typing.Dict:
@@ -223,7 +236,9 @@ def _obj_from_python(cls, json, obj_type):
                 return obj_type(json)
 
     @classmethod
-    def from_dict(cls, json: dict):
+    def from_dict(cls, json: dict, use_pydantic: bool = False):
+        if use_pydantic:
+            return cls.type_adapter().validate_python(json)
         return cls._obj_from_python(json, cls)
 
     def to_dict_depr(self):

csp/impl/types/typing_utils.py

@@ -15,6 +15,33 @@ class FastList(typing.List, typing.Generic[T]):  # Need to inherit from Generic[
     def __init__(self):
         raise NotImplementedError("Can not init FastList class")
 
+    @classmethod
+    def __get_pydantic_core_schema__(cls, source_type, handler):
+        from pydantic_core import core_schema
+
+        # Late import to not interfere with autogen
+        args = typing.get_args(source_type)
+        if args:
+            inner_type = args[0]
+            list_schema = handler.generate_schema(typing.List[inner_type])
+        else:
+            list_schema = handler.generate_schema(typing.List)
+
+        def create_instance(raw_data, validator):
+            if isinstance(raw_data, FastList):
+                return raw_data
+            return validator(raw_data)  # just return a list
+
+        return core_schema.no_info_wrap_validator_function(
+            function=create_instance,
+            schema=list_schema,
+            serialization=core_schema.plain_serializer_function_ser_schema(
+                lambda val: list(v for v in val),
+                return_schema=list_schema,
+                when_used="json",
+            ),
+        )
+
 
 class CspTypingUtils39:
     _ORIGIN_COMPAT_MAP = {list: typing.List, set: typing.Set, dict: typing.Dict, tuple: typing.Tuple}