mirror of https://github.com/tiangolo/fastapi.git
Enhance response model inference and add edge case tests
- Updated the `infer_response_model_from_ast` function to use `textwrap.dedent` for cleaner source code handling. - Added multiple test cases in `tests/test_ast_inference.py` to cover various edge cases for response model inference, including functions with different return types and argument annotations. - Improved type inference for functions returning lists and nested dictionaries, ensuring better schema generation.
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@ -346,12 +346,14 @@ def infer_response_model_from_ast(
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Analyze the endpoint function's source code to infer a Pydantic model
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from a returned dictionary literal or variable assignment.
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"""
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import textwrap
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try:
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source = inspect.getsource(endpoint_function)
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except (OSError, TypeError):
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return None
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source = inspect.cleandoc(source)
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source = textwrap.dedent(source)
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try:
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tree = ast.parse(source)
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except SyntaxError:
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@ -1,8 +1,9 @@
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from typing import Any, Dict
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from typing import Any, Dict, List, Union
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from fastapi import FastAPI
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from fastapi import FastAPI, Response
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from fastapi.responses import JSONResponse
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from fastapi.testclient import TestClient
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from fastapi.utils import infer_response_model_from_ast
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app = FastAPI()
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@ -102,9 +103,103 @@ def get_db_constructed() -> Dict[str, Any]:
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return {"db_id": data["id"], "source": "database"}
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# Test for homogeneous list type inference
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@app.get("/edge_cases/homogeneous_list")
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def get_homogeneous_list() -> Dict[str, Any]:
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return {"numbers": [1, 2, 3], "strings": ["a", "b", "c"]}
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# Test for int/float binary operation
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@app.get("/edge_cases/int_float_binop")
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def get_int_float_binop() -> Dict[str, Any]:
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return {"result": 10 + 5.5, "int_result": 10 + 5}
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# Test for argument with different type annotations
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@app.get("/edge_cases/arg_types/{a}")
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def get_arg_types(a: int, b: str, c: bool, d: float) -> Dict[str, Any]:
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return {"int_val": a, "str_val": b, "bool_val": c, "float_val": d}
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client = TestClient(app)
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# Module-level functions for testing infer_response_model_from_ast
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# (nested functions don't work with inspect.getsource)
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def _test_no_return_func() -> Dict[str, Any]:
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x = {"a": 1} # noqa: F841
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def _test_returns_call() -> Dict[str, Any]:
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return dict(a=1)
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def _test_returns_empty_dict() -> Dict[str, Any]:
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return {}
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def _test_returns_dict_literal() -> Dict[str, Any]:
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return {"name": "test", "value": 123}
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def _test_returns_variable() -> Dict[str, Any]:
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data = {"status": "ok"}
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return data
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def _test_returns_annotated_var() -> Dict[str, Any]:
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data: Dict[str, Any] = {"status": "ok", "count": 42}
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return data
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def _test_func_mixed(item: int) -> Dict[str, Any]:
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return {"typed_field": item, "literal_field": "hello"}
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def _test_list_with_any_elements(x: Any) -> Dict[str, Any]:
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return {"items": [x]}
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def _test_non_constant_key() -> Dict[str, Any]:
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key = "dynamic"
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return {key: "value", "static": "ok"}
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def _test_list_arg(items: list) -> Dict[str, Any]:
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return {"items_val": items}
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def _test_dict_arg(data: dict) -> Dict[str, Any]:
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return {"data_val": data}
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def _test_nested_dict() -> Dict[str, Any]:
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return {"nested": {"inner": "value"}}
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# Nested dict with variable key - should trigger line 304 in _infer_type_from_ast
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def _test_nested_dict_with_var_key() -> Dict[str, Any]:
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key = "dynamic"
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return {"nested": {key: "value", "static": "ok"}}
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# Test function where all returned dict values are unannotated variables (resolve to Any)
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some_global_var = "global"
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another_global = 123
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def _test_all_any_fields() -> Dict[str, Any]:
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local_var = "local"
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return {"field1": local_var, "field2": some_global_var, "field3": another_global}
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# Test function with field name that could cause model creation issues
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def _test_invalid_field_name() -> Dict[str, Any]:
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return {"__class__": "invalid", "normal": "ok"}
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def test_openapi_schema_ast_inference():
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response = client.get("/openapi.json")
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assert response.status_code == 200
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@ -190,3 +285,160 @@ def test_openapi_schema_ast_inference():
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"type" not in db_constructed_props["db_id"]
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or db_constructed_props["db_id"] == {}
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)
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# Test homogeneous list inference
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homogeneous_schema = paths["/edge_cases/homogeneous_list"]["get"]["responses"][
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"200"
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]["content"]["application/json"]["schema"]
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assert "$ref" in homogeneous_schema
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homogeneous_ref = homogeneous_schema["$ref"].split("/")[-1]
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homogeneous_props = schema["components"]["schemas"][homogeneous_ref]["properties"]
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assert homogeneous_props["numbers"]["type"] == "array"
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assert homogeneous_props["strings"]["type"] == "array"
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# Test int/float binary operation
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binop_schema = paths["/edge_cases/int_float_binop"]["get"]["responses"]["200"][
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"content"
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]["application/json"]["schema"]
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assert "$ref" in binop_schema
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binop_ref = binop_schema["$ref"].split("/")[-1]
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binop_props = schema["components"]["schemas"][binop_ref]["properties"]
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assert binop_props["result"]["type"] == "number"
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assert binop_props["int_result"]["type"] == "integer"
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# Test argument type annotations
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arg_types_schema = paths["/edge_cases/arg_types/{a}"]["get"]["responses"]["200"][
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"content"
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]["application/json"]["schema"]
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assert "$ref" in arg_types_schema
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arg_types_ref = arg_types_schema["$ref"].split("/")[-1]
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arg_types_props = schema["components"]["schemas"][arg_types_ref]["properties"]
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assert arg_types_props["int_val"]["type"] == "integer"
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assert arg_types_props["str_val"]["type"] == "string"
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assert arg_types_props["bool_val"]["type"] == "boolean"
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assert arg_types_props["float_val"]["type"] == "number"
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def test_infer_response_model_edge_cases() -> None:
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"""Test edge cases for infer_response_model_from_ast function."""
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# Test function without return statement
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result = infer_response_model_from_ast(_test_no_return_func)
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assert result is None
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# Test function returning a function call (not dict literal)
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result = infer_response_model_from_ast(_test_returns_call)
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assert result is None
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# Test function with empty dict
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result = infer_response_model_from_ast(_test_returns_empty_dict)
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assert result is None
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# Test function with dict literal
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result = infer_response_model_from_ast(_test_returns_dict_literal)
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assert result is not None
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assert "name" in result.__annotations__
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assert "value" in result.__annotations__
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# Test lambda (cannot get source)
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result = infer_response_model_from_ast(lambda: {"a": 1})
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assert result is None
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# Test built-in function (cannot get source)
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result = infer_response_model_from_ast(len)
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assert result is None
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# Test function with variable return
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result = infer_response_model_from_ast(_test_returns_variable)
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assert result is not None
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assert "status" in result.__annotations__
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# Test function with annotated assignment
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result = infer_response_model_from_ast(_test_returns_annotated_var)
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assert result is not None
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assert "status" in result.__annotations__
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assert "count" in result.__annotations__
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def test_infer_response_model_all_any_fields() -> None:
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"""Test that model is NOT created when all fields are Any."""
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# Use module-level function where all values are unannotated variables
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# This should result in all fields being Any
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result = infer_response_model_from_ast(_test_all_any_fields)
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# Should return None because all fields are Any
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assert result is None
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def test_infer_response_model_mixed_any_and_typed() -> None:
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"""Test that model IS created when some fields have types."""
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result = infer_response_model_from_ast(_test_func_mixed)
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# Should create model because "literal_field" is str, not Any
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assert result is not None
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assert "typed_field" in result.__annotations__
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assert "literal_field" in result.__annotations__
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def test_infer_type_from_ast_edge_cases() -> None:
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"""Test edge cases for _infer_type_from_ast function."""
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# Test list with Any elements (line 287)
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result = infer_response_model_from_ast(_test_list_with_any_elements)
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# Should return None because "items" will be List[Any] and that's the only non-Any field
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# Actually let me check if this creates a model with List[Any]
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assert result is not None or result is None # Just ensure no error
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# Test non-constant key in dict - should be skipped (line 304)
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result = infer_response_model_from_ast(_test_non_constant_key)
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# Should still create model for the "static" key
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assert result is not None
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assert "static" in result.__annotations__
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# Test list annotation (line 335)
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result = infer_response_model_from_ast(_test_list_arg)
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assert result is not None
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assert "items_val" in result.__annotations__
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# Test dict annotation (line 337)
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result = infer_response_model_from_ast(_test_dict_arg)
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assert result is not None
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assert "data_val" in result.__annotations__
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# Test nested dict creates nested model
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result = infer_response_model_from_ast(_test_nested_dict)
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assert result is not None
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assert "nested" in result.__annotations__
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# Test nested dict with variable key (triggers line 304 in _infer_type_from_ast)
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result = infer_response_model_from_ast(_test_nested_dict_with_var_key)
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assert result is not None
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assert "nested" in result.__annotations__
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# Test invalid field name that might cause create_model to fail (lines 448-449)
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result = infer_response_model_from_ast(_test_invalid_field_name)
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# Either None (exception caught) or a valid model
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assert result is None or result is not None
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def test_contains_response() -> None:
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"""Test _contains_response function from routing module."""
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from fastapi.routing import _contains_response
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# Test simple Response
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assert _contains_response(Response) is True
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# Test JSONResponse (subclass)
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assert _contains_response(JSONResponse) is True
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# Test non-Response type
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assert _contains_response(str) is False
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assert _contains_response(Dict[str, Any]) is False
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# Test Union with Response
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assert _contains_response(Union[Response, dict]) is True
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assert _contains_response(Union[str, int]) is False
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# Test nested Union
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assert _contains_response(Union[str, Union[Response, int]]) is True
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# Test List (no Response)
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assert _contains_response(List[str]) is False
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