Fix snake case array discriminator

docs/cli-reference/field-customization.md

@@ -3585,14 +3585,14 @@ format as the default.
     # generated by datamodel-codegen:
     #   filename:  person.json
     #   timestamp: 2019-07-26T00:00:00+00:00
-
+    
     from __future__ import annotations
-
+    
     from typing import Any
-
+    
     from pydantic import BaseModel, conint
-
-
+    
+    
     class Person(BaseModel):
         firstName: str | None = None
         """The person's first name."""

src/datamodel_code_generator/parser/base.py

@@ -2125,7 +2125,11 @@ def __collapse_root_models(  # noqa: PLR0912, PLR0914, PLR0915
                                     if isinstance(discriminator, dict)
                                     else discriminator
                                 )
-                                copied_data_type.discriminator = prop_name
+                                field_name, _ = self.model_resolver.get_valid_field_name_and_alias(
+                                    field_name=prop_name,
+                                    model_type=self.field_name_model_type,
+                                )
+                                copied_data_type.discriminator = field_name
                         assert isinstance(data_type.parent, DataType)
                         data_type.parent.data_types.remove(data_type)
                         data_type.parent.data_types.append(copied_data_type)

tests/data/expected/main/openapi/discriminator/in_array_snake_case_pydantic_v2.py

@@ -0,0 +1,32 @@
+# generated by datamodel-codegen:
+#   filename:  discriminator_in_array_snake_case.yaml
+#   timestamp: 2023-07-27T00:00:00+00:00
+
+from __future__ import annotations
+
+from enum import StrEnum
+from typing import Annotated, Literal
+
+from pydantic import BaseModel, Field
+
+
+class ObjectType(StrEnum):
+    foo = 'FOO'
+
+
+class FooType(BaseModel):
+    object_type: Annotated[Literal['FOO'], Field(alias='objectType')]
+
+
+class ObjectType1(StrEnum):
+    bar = 'BAR'
+
+
+class BarType(BaseModel):
+    object_type: Annotated[Literal['BAR'], Field(alias='objectType')]
+
+
+class Container(BaseModel):
+    items: (
+        list[Annotated[FooType | BarType, Field(discriminator='object_type')]] | None
+    ) = None

tests/data/openapi/discriminator_in_array_snake_case.yaml

@@ -0,0 +1,36 @@
+openapi: "3.0.0"
+info:
+  title: Repro
+  version: "1.0"
+paths: {}
+components:
+  schemas:
+    FooType:
+      type: object
+      required:
+        - objectType
+      properties:
+        objectType:
+          type: string
+          enum:
+            - FOO
+    BarType:
+      type: object
+      required:
+        - objectType
+      properties:
+        objectType:
+          type: string
+          enum:
+            - BAR
+    Container:
+      type: object
+      properties:
+        items:
+          type: array
+          items:
+            discriminator:
+              propertyName: objectType
+            oneOf:
+              - $ref: "#/components/schemas/FooType"
+              - $ref: "#/components/schemas/BarType"

tests/main/openapi/test_main_openapi.py

@@ -2576,6 +2576,29 @@ def test_main_openapi_discriminator_in_array_underscore(output_file: Path) -> No
     )
 
 
+@LEGACY_BLACK_SKIP
+@freeze_time("2023-07-27")
+def test_main_openapi_discriminator_in_array_snake_case(output_file: Path) -> None:
+    """Test collapsed list item discriminator uses snake_case field name."""
+    run_main_and_assert(
+        input_path=OPEN_API_DATA_PATH / "discriminator_in_array_snake_case.yaml",
+        output_path=output_file,
+        input_file_type="openapi",
+        assert_func=assert_file_content,
+        expected_file="discriminator/in_array_snake_case_pydantic_v2.py",
+        extra_args=[
+            "--target-python-version",
+            "3.12",
+            "--output-model-type",
+            "pydantic_v2.BaseModel",
+            "--use-annotated",
+            "--snake-case-field",
+            "--collapse-root-models",
+        ],
+        force_exec_validation=True,
+    )
+
+
 @pytest.mark.parametrize(
     ("output_model", "expected_output"),
     [