← pod_r5_v1i

fastapi_14482

failed CONTEXT NO_PATCH UNSUBMITTED agent_error · 46 tool calls · 283 s · fastapi/fastapi

Task input

🐛 Fix handling arbitrary types when using `arbitrary_types_allowed=True`

🐛 Fix handling arbitrary types when using `arbitrary_types_allowed=True`

Related to https://github.com/fastapi/fastapi/discussions/14184, https://github.com/fastapi/fastapi/issues/14483

Tool calls (46)

#ToolArgumentsResult
1run_command
{
 "command": "grep -rn 'arbitrary_types_allowed' . | head -20"
}
{"status": "ok", "stdout": "./tests/test_inherited_custom_class.py:45: model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_inherited_custom_class.p
full
{"status": "ok", "stdout": "./tests/test_inherited_custom_class.py:45:        model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_inherited_custom_class.py:89:            arbitrary_types_allowed = True\n./tests/test_jsonable_encoder.py:248:            model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_jsonable_encoder.py:252:                arbitrary_types_allowed = True\n./tests/test_jsonable_encoder.py:264:            model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_jsonable_encoder.py:268:                arbitrary_types_allowed = True\n./tests/test_jsonable_encoder.py:279:            model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_jsonable_encoder.py:283:                arbitrary_types_allowed = True\n./tests/test_compat.py:87:        model_config = ConfigDict(arbitrary_types_allowed=True)\n./tests/test_compat.py:92:            arbitrary_types_allowed=True,\n", "stderr": "", "exit_code": 0}
2run_command
{
 "command": "grep -rn 'arbitrary_types_allowed' fastapi/ | head -20"
}
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
3run_command
{
 "command": "grep -rn 'arbitrary_types_allowed' . | head -40"
}
{"status": "ok", "stdout": "./tests/test_inherited_custom_class.py:45: model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_inherited_custom_class.p
full
{"status": "ok", "stdout": "./tests/test_inherited_custom_class.py:45:        model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_inherited_custom_class.py:89:            arbitrary_types_allowed = True\n./tests/test_jsonable_encoder.py:248:            model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_jsonable_encoder.py:252:                arbitrary_types_allowed = True\n./tests/test_jsonable_encoder.py:264:            model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_jsonable_encoder.py:268:                arbitrary_types_allowed = True\n./tests/test_jsonable_encoder.py:279:            model_config = {\"arbitrary_types_allowed\": True}\n./tests/test_jsonable_encoder.py:283:                arbitrary_types_allowed = True\n./tests/test_compat.py:87:        model_config = ConfigDict(arbitrary_types_allowed=True)\n./tests/test_compat.py:92:            arbitrary_types_allowed=True,\n", "stderr": "", "exit_code": 0}
4run_command
{
 "command": "grep -rn 'arbitrary_types_allowed' /usr/local/lib/python3.10/site-packages/pydantic/ | head -20"
}
{"status": "ok", "stdout": "", "stderr": "grep: /usr/local/lib/python3.10/site-packages/pydantic/: No such file or directory\n", "exit_code": 0}
full
{"status": "ok", "stdout": "", "stderr": "grep: /usr/local/lib/python3.10/site-packages/pydantic/: No such file or directory\n", "exit_code": 0}
5run_command
{
 "command": "grep -rn 'arbitrary_types_allowed' /usr/lib/python3.10/site-packages/pydantic/ | head -20"
}
{"status": "ok", "stdout": "", "stderr": "grep: /usr/lib/python3.10/site-packages/pydantic/: No such file or directory\n", "exit_code": 0}
full
{"status": "ok", "stdout": "", "stderr": "grep: /usr/lib/python3.10/site-packages/pydantic/: No such file or directory\n", "exit_code": 0}
6run_command
{
 "command": "find /workspace -name \"*.py\" | xargs grep -l 'arbitrary_types_allowed'"
}
{"status": "ok", "stdout": "/workspace/tests/test_inherited_custom_class.py\n/workspace/tests/test_jsonable_encoder.py\n/workspace/tests/test_compat.py\n", "std
full
{"status": "ok", "stdout": "/workspace/tests/test_inherited_custom_class.py\n/workspace/tests/test_jsonable_encoder.py\n/workspace/tests/test_compat.py\n", "stderr": "", "exit_code": 0}
7run_command
{
 "command": "cat /workspace/tests/test_jsonable_encoder.py | grep -C 10 'arbitrary_types_allowed' | head -40"
}
{"status": "ok", "stdout": " instance, custom_encoder={MyEnum: custom_enum_encoder}\n )\n assert encoded_instance == custom_enum_encoder(instance)\n\n\ndef test
full
{"status": "ok", "stdout": "        instance, custom_encoder={MyEnum: custom_enum_encoder}\n    )\n    assert encoded_instance == custom_enum_encoder(instance)\n\n\ndef test_encode_model_with_pure_path():\n    class ModelWithPath(BaseModel):\n        path: PurePath\n\n        if PYDANTIC_V2:\n            model_config = {\"arbitrary_types_allowed\": True}\n        else:\n\n            class Config:\n                arbitrary_types_allowed = True\n\n    test_path = PurePath(\"/foo\", \"bar\")\n    obj = ModelWithPath(path=test_path)\n    assert jsonable_encoder(obj) == {\"path\": str(test_path)}\n\n\ndef test_encode_model_with_pure_posix_path():\n    class ModelWithPath(BaseModel):\n        path: PurePosixPath\n\n        if PYDANTIC_V2:\n            model_config = {\"arbitrary_types_allowed\": True}\n        else:\n\n            class Config:\n                arbitrary_types_allowed = True\n\n    obj = ModelWithPath(path=PurePosixPath(\"/foo\", \"bar\"))\n    assert jsonable_encoder(obj) == {\"path\": \"/foo/bar\"}\n\n\ndef test_encode_model_with_pure_windows_path():\n    class ModelWithPath(BaseModel):\n        path: PureWindowsPath\n\n", "stderr": "", "exit_code": 0}
8run_command
{
 "command": "grep -rn 'jsonable_encoder' fastapi/ | head -20"
}
{"status": "ok", "stdout": "fastapi/exception_handlers.py:1:from fastapi.encoders import jsonable_encoder\nfastapi/exception_handlers.py:25: content={\"detail\"
full
{"status": "ok", "stdout": "fastapi/exception_handlers.py:1:from fastapi.encoders import jsonable_encoder\nfastapi/exception_handlers.py:25:        content={\"detail\": jsonable_encoder(exc.errors())},\nfastapi/exception_handlers.py:33:        code=WS_1008_POLICY_VIOLATION, reason=jsonable_encoder(exc.errors())\nfastapi/encoders.py:114:def jsonable_encoder(\nfastapi/encoders.py:247:        return jsonable_encoder(\nfastapi/encoders.py:258:        return jsonable_encoder(\nfastapi/encoders.py:294:                encoded_key = jsonable_encoder(\nfastapi/encoders.py:302:                encoded_value = jsonable_encoder(\nfastapi/encoders.py:316:                jsonable_encoder(\nfastapi/encoders.py:346:    return jsonable_encoder(\nfastapi/openapi/docs.py:5:from fastapi.encoders import jsonable_encoder\nfastapi/openapi/docs.py:137:        html += f\"{json.dumps(key)}: {json.dumps(jsonable_encoder(value))},\\n\"\nfastapi/openapi/docs.py:151:        ui.initOAuth({json.dumps(jsonable_encoder(init_oauth))})\nfastapi/openapi/utils.py:23:from fastapi.encoders import jsonable_encoder\nfastapi/openapi/utils.py:85:        security_definition = jsonable_encoder(\nfastapi/openapi/utils.py:168:                parameter[\"examples\"] = jsonable_encoder(openapi_examples)\nfastapi/openapi/utils.py:170:                parameter[\"example\"] = jsonable_encoder(example)\nfastapi/openapi/utils.py:203:        request_media_content[\"examples\"] = jsonable_encoder(\nfastapi/openapi/utils.py:207:        request_media_content[\"example\"] = jsonable_encoder(field_info.example)\nfastapi/openapi/utils.py:567:    return jsonable_encoder(OpenAPI(**output), by_alias=True, exclude_none=True)  # type: ignore\n", "stderr": "", "exit_code": 0}
9run_command
{
 "command": "sed -n '110,160p' fastapi/encoders.py"
}
{"status": "ok", "stdout": "\nencoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)\n\n\ndef jsonable_encoder(\n obj: Annotated[\n Any,
full
{"status": "ok", "stdout": "\nencoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)\n\n\ndef jsonable_encoder(\n    obj: Annotated[\n        Any,\n        Doc(\n            \"\"\"\n            The input object to convert to JSON.\n            \"\"\"\n        ),\n    ],\n    include: Annotated[\n        Optional[IncEx],\n        Doc(\n            \"\"\"\n            Pydantic's `include` parameter, passed to Pydantic models to set the\n            fields to include.\n            \"\"\"\n        ),\n    ] = None,\n    exclude: Annotated[\n        Optional[IncEx],\n        Doc(\n            \"\"\"\n            Pydantic's `exclude` parameter, passed to Pydantic models to set the\n            fields to exclude.\n            \"\"\"\n        ),\n    ] = None,\n    by_alias: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `by_alias` parameter, passed to Pydantic models to define if\n            the output should use the alias names (when provided) or the Python\n            attribute names. In an API, if you set an alias, it's probably because you\n            want to use it in the result, so you probably want to leave this set to\n            `True`.\n            \"\"\"\n        ),\n    ] = True,\n    exclude_unset: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `exclude_unset` parameter, passed to Pydantic models to define\n            if it should exclude from the output the fields that were not explicitly\n            set (and that only had their default values).\n            \"\"\"\n", "stderr": "", "exit_code": 0}
10run_command
{
 "command": "sed -n '110,350p' fastapi/encoders.py"
}
{"status": "ok", "stdout": "\nencoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)\n\n\ndef jsonable_encoder(\n obj: Annotated[\n Any,
full
{"status": "ok", "stdout": "\nencoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)\n\n\ndef jsonable_encoder(\n    obj: Annotated[\n        Any,\n        Doc(\n            \"\"\"\n            The input object to convert to JSON.\n            \"\"\"\n        ),\n    ],\n    include: Annotated[\n        Optional[IncEx],\n        Doc(\n            \"\"\"\n            Pydantic's `include` parameter, passed to Pydantic models to set the\n            fields to include.\n            \"\"\"\n        ),\n    ] = None,\n    exclude: Annotated[\n        Optional[IncEx],\n        Doc(\n            \"\"\"\n            Pydantic's `exclude` parameter, passed to Pydantic models to set the\n            fields to exclude.\n            \"\"\"\n        ),\n    ] = None,\n    by_alias: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `by_alias` parameter, passed to Pydantic models to define if\n            the output should use the alias names (when provided) or the Python\n            attribute names. In an API, if you set an alias, it's probably because you\n            want to use it in the result, so you probably want to leave this set to\n            `True`.\n            \"\"\"\n        ),\n    ] = True,\n    exclude_unset: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `exclude_unset` parameter, passed to Pydantic models to define\n            if it should exclude from the output the fields that were not explicitly\n            set (and that only had their default values).\n            \"\"\"\n        ),\n    ] = False,\n    exclude_defaults: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `exclude_defaults` parameter, passed to Pydantic models to define\n            if it should exclude from the output the fields that had the same default\n            value, even when they were explicitly set.\n            \"\"\"\n        ),\n    ] = False,\n    ex
11run_command
{
 "command": "sed -n '350,420p' fastapi/encoders.py"
}
{"status": "ok", "stdout": " by_alias=by_alias,\n exclude_unset=exclude_unset,\n exclude_defaults=exclude_defaults,\n exclude_none=exclude_none,\n custom_encode
full
{"status": "ok", "stdout": "        by_alias=by_alias,\n        exclude_unset=exclude_unset,\n        exclude_defaults=exclude_defaults,\n        exclude_none=exclude_none,\n        custom_encoder=custom_encoder,\n        sqlalchemy_safe=sqlalchemy_safe,\n    )\n", "stderr": "", "exit_code": 0}
12run_command
{
 "command": "cat /workspace/tests/test_inherited_custom_class.py | grep -C 10 'arbitrary_types_allowed' | head -40"
}
{"status": "ok", "stdout": " @app.get(\"/fast_uuid\")\n def return_fast_uuid():\n asyncpg_uuid = MyUuid(\"a10ff360-3b1e-4984-a26f-d3ab460bdb51\")\n assert isins
full
{"status": "ok", "stdout": "    @app.get(\"/fast_uuid\")\n    def return_fast_uuid():\n        asyncpg_uuid = MyUuid(\"a10ff360-3b1e-4984-a26f-d3ab460bdb51\")\n        assert isinstance(asyncpg_uuid, uuid.UUID)\n        assert type(asyncpg_uuid) is not uuid.UUID\n        with pytest.raises(TypeError):\n            vars(asyncpg_uuid)\n        return {\"fast_uuid\": asyncpg_uuid}\n\n    class SomeCustomClass(BaseModel):\n        model_config = {\"arbitrary_types_allowed\": True}\n\n        a_uuid: MyUuid\n\n        @field_serializer(\"a_uuid\")\n        def serialize_a_uuid(self, v):\n            return str(v)\n\n    @app.get(\"/get_custom_class\")\n    def return_some_user():\n        # Test that the fix also works for custom pydantic classes\n--\n    def return_fast_uuid():\n        asyncpg_uuid = MyUuid(\"a10ff360-3b1e-4984-a26f-d3ab460bdb51\")\n        assert isinstance(asyncpg_uuid, uuid.UUID)\n        assert type(asyncpg_uuid) is not uuid.UUID\n        with pytest.raises(TypeError):\n            vars(asyncpg_uuid)\n        return {\"fast_uuid\": asyncpg_uuid}\n\n    class SomeCustomClass(BaseModel):\n        class Config:\n            arbitrary_types_allowed = True\n            json_encoders = {uuid.UUID: str}\n\n        a_uuid: MyUuid\n\n    @app.get(\"/get_custom_class\")\n    def return_some_user():\n        # Test that the fix also works for custom pydantic classes\n", "stderr": "", "exit_code": 0}
13run_command
{
 "command": "cat /workspace/tests/test_inherited_custom_class.py"
}
{"status": "ok", "stdout": "import uuid\n\nimport pytest\nfrom fastapi import FastAPI\nfrom fastapi.testclient import TestClient\nfrom pydantic import BaseModel
full
{"status": "ok", "stdout": "import uuid\n\nimport pytest\nfrom fastapi import FastAPI\nfrom fastapi.testclient import TestClient\nfrom pydantic import BaseModel\n\nfrom .utils import needs_pydanticv1, needs_pydanticv2\n\n\nclass MyUuid:\n    def __init__(self, uuid_string: str):\n        self.uuid = uuid_string\n\n    def __str__(self):\n        return self.uuid\n\n    @property  # type: ignore\n    def __class__(self):\n        return uuid.UUID\n\n    @property\n    def __dict__(self):\n        \"\"\"Spoof a missing __dict__ by raising TypeError, this is how\n        asyncpg.pgroto.pgproto.UUID behaves\"\"\"\n        raise TypeError(\"vars() argument must have __dict__ attribute\")\n\n\n@needs_pydanticv2\ndef test_pydanticv2():\n    from pydantic import field_serializer\n\n    app = FastAPI()\n\n    @app.get(\"/fast_uuid\")\n    def return_fast_uuid():\n        asyncpg_uuid = MyUuid(\"a10ff360-3b1e-4984-a26f-d3ab460bdb51\")\n        assert isinstance(asyncpg_uuid, uuid.UUID)\n        assert type(asyncpg_uuid) is not uuid.UUID\n        with pytest.raises(TypeError):\n            vars(asyncpg_uuid)\n        return {\"fast_uuid\": asyncpg_uuid}\n\n    class SomeCustomClass(BaseModel):\n        model_config = {\"arbitrary_types_allowed\": True}\n\n        a_uuid: MyUuid\n\n        @field_serializer(\"a_uuid\")\n        def serialize_a_uuid(self, v):\n            return str(v)\n\n    @app.get(\"/get_custom_class\")\n    def return_some_user():\n        # Test that the fix also works for custom pydantic classes\n        return SomeCustomClass(a_uuid=MyUuid(\"b8799909-f914-42de-91bc-95c819218d01\"))\n\n    client = TestClient(app)\n\n    with client:\n        response_simple = client.get(\"/fast_uuid\")\n        response_pydantic = client.get(\"/get_custom_class\")\n\n    assert response_simple.json() == {\n        \"fast_uuid\": \"a10ff360-3b1e-4984-a26f-d3ab460bdb51\"\n    }\n\n    assert response_pydantic.json() == {\n        \"a_uuid\": \"b8799909-f914-42de-91bc-95c81
14run_command
{
 "command": "python3 -m pytest tests/test_inherited_custom_class.py"
}
{"status": "ok", "stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.13.15, pytest-9.1.1, p
full
{"status": "ok", "stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.13.15, pytest-9.1.1, pluggy-1.6.0\ncodspeed: 5.0.3 (disabled, mode: walltime, callgraph: not supported, timer_resolution: 41.7ns)\nrootdir: /private/workspace\nconfigfile: pytest.ini (WARNING: ignoring pytest config in pyproject.toml!)\nplugins: cov-7.1.0, xdist-3.8.0, timeout-2.4.0, codspeed-5.0.3, sugar-1.1.1, anyio-4.15.1, inline-snapshot-0.35.4\ncollected 2 items\n\ntests/test_inherited_custom_class.py .s                                  [100%]\n\n=============================== warnings summary ===============================\n../../../../../../../Users/jp/repos/kaggle-gemini-coding-agent-post-training/.envs/overlays/starlette-0.50.0-py3-none-any/starlette/testclient.py:45\n  /Users/jp/repos/kaggle-gemini-coding-agent-post-training/.envs/overlays/starlette-0.50.0-py3-none-any/starlette/testclient.py:45: DeprecationWarning: The anyio.abc.BlockingPortal alias is deprecated, use anyio.from_thread.BlockingPortal instead.\n    _PortalFactoryType = Callable[[], AbstractContextManager[anyio.abc.BlockingPortal]]\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=================== 1 passed, 1 skipped, 1 warning in 0.47s ====================\n", "stderr": "", "exit_code": 0}
15run_command
{
 "command": "python3 -m pytest tests/test_jsonable_encoder.py"
}
{"status": "ok", "stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.13.15, pytest-9.1.1, p
full
{"status": "ok", "stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.13.15, pytest-9.1.1, pluggy-1.6.0\ncodspeed: 5.0.3 (disabled, mode: walltime, callgraph: not supported, timer_resolution: 41.7ns)\nrootdir: /private/workspace\nconfigfile: pytest.ini (WARNING: ignoring pytest config in pyproject.toml!)\nplugins: cov-7.1.0, xdist-3.8.0, timeout-2.4.0, codspeed-5.0.3, sugar-1.1.1, anyio-4.15.1, inline-snapshot-0.35.4\ncollected 23 items\n\ntests/test_jsonable_encoder.py ......s....s....s......                   [100%]\n\n======================== 20 passed, 3 skipped in 0.33s =========================\n", "stderr": "", "exit_code": 0}
16run_command
{
 "command": "python3 -m pytest tests/test_compat.py"
}
{"status": "ok", "stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.13.15, pytest-9.1.1, p
full
{"status": "ok", "stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.13.15, pytest-9.1.1, pluggy-1.6.0\ncodspeed: 5.0.3 (disabled, mode: walltime, callgraph: not supported, timer_resolution: 41.7ns)\nrootdir: /private/workspace\nconfigfile: pytest.ini (WARNING: ignoring pytest config in pyproject.toml!)\nplugins: cov-7.1.0, xdist-3.8.0, timeout-2.4.0, codspeed-5.0.3, sugar-1.1.1, anyio-4.15.1, inline-snapshot-0.35.4\ncollected 13 items\n\ntests/test_compat.py .s.........ss                                       [100%]\n\n=============================== warnings summary ===============================\n../../../../../../../Users/jp/repos/kaggle-gemini-coding-agent-post-training/.envs/overlays/starlette-0.50.0-py3-none-any/starlette/testclient.py:45\n  /Users/jp/repos/kaggle-gemini-coding-agent-post-training/.envs/overlays/starlette-0.50.0-py3-none-any/starlette/testclient.py:45: DeprecationWarning: The anyio.abc.BlockingPortal alias is deprecated, use anyio.from_thread.BlockingPortal instead.\n    _PortalFactoryType = Callable[[], AbstractContextManager[anyio.abc.BlockingPortal]]\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=================== 10 passed, 3 skipped, 1 warning in 0.41s ===================\n", "stderr": "", "exit_code": 0}
17run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\nprint(f\"Object: {obj}\")\ntry:\n    encoded = jsonable_encoder(obj)\n    print(f\"Encoded: {encoded}\")\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "Object: attr=MyType(test)\nError: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "Object: attr=MyType(test)\nError: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
18run_command
{
 "command": "sed -n '110,420p' fastapi/encoders.py"
}
{"status": "ok", "stdout": "\nencoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)\n\n\ndef jsonable_encoder(\n obj: Annotated[\n Any,
full
{"status": "ok", "stdout": "\nencoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)\n\n\ndef jsonable_encoder(\n    obj: Annotated[\n        Any,\n        Doc(\n            \"\"\"\n            The input object to convert to JSON.\n            \"\"\"\n        ),\n    ],\n    include: Annotated[\n        Optional[IncEx],\n        Doc(\n            \"\"\"\n            Pydantic's `include` parameter, passed to Pydantic models to set the\n            fields to include.\n            \"\"\"\n        ),\n    ] = None,\n    exclude: Annotated[\n        Optional[IncEx],\n        Doc(\n            \"\"\"\n            Pydantic's `exclude` parameter, passed to Pydantic models to set the\n            fields to exclude.\n            \"\"\"\n        ),\n    ] = None,\n    by_alias: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `by_alias` parameter, passed to Pydantic models to define if\n            the output should use the alias names (when provided) or the Python\n            attribute names. In an API, if you set an alias, it's probably because you\n            want to use it in the result, so you probably want to leave this set to\n            `True`.\n            \"\"\"\n        ),\n    ] = True,\n    exclude_unset: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `exclude_unset` parameter, passed to Pydantic models to define\n            if it should exclude from the output the fields that were not explicitly\n            set (and that only had their default values).\n            \"\"\"\n        ),\n    ] = False,\n    exclude_defaults: Annotated[\n        bool,\n        Doc(\n            \"\"\"\n            Pydantic's `exclude_defaults` parameter, passed to Pydantic models to define\n            if it should exclude from the output the fields that had the same default\n            value, even when they were explicitly set.\n            \"\"\"\n        ),\n    ] = False,\n    ex
19run_command
{
 "command": "sed -n '410,420p' fastapi/encoders.py"
}
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
20run_command
{
 "command": "sed -n '1,430p' fastapi/encoders.py"
}
{"status": "ok", "stdout": "import dataclasses\nimport datetime\nfrom collections import defaultdict, deque\nfrom decimal import Decimal\nfrom enum import Enum\
full
{"status": "ok", "stdout": "import dataclasses\nimport datetime\nfrom collections import defaultdict, deque\nfrom decimal import Decimal\nfrom enum import Enum\nfrom ipaddress import (\n    IPv4Address,\n    IPv4Interface,\n    IPv4Network,\n    IPv6Address,\n    IPv6Interface,\n    IPv6Network,\n)\nfrom pathlib import Path, PurePath\nfrom re import Pattern\nfrom types import GeneratorType\nfrom typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union\nfrom uuid import UUID\n\nfrom annotated_doc import Doc\nfrom fastapi._compat import may_v1\nfrom fastapi.types import IncEx\nfrom pydantic import BaseModel\nfrom pydantic.color import Color\nfrom pydantic.networks import AnyUrl, NameEmail\nfrom pydantic.types import SecretBytes, SecretStr\nfrom typing_extensions import Annotated\n\nfrom ._compat import Url, _is_undefined, _model_dump\n\n\n# Taken from Pydantic v1 as is\ndef isoformat(o: Union[datetime.date, datetime.time]) -> str:\n    return o.isoformat()\n\n\n# Adapted from Pydantic v1\n# TODO: pv2 should this return strings instead?\ndef decimal_encoder(dec_value: Decimal) -> Union[int, float]:\n    \"\"\"\n    Encodes a Decimal as int if there's no exponent, otherwise float\n\n    This is useful when we use ConstrainedDecimal to represent Numeric(x,0)\n    where an integer (but not int typed) is used. Encoding this as a float\n    results in failed round-tripping between encode and parse.\n    Our Id type is a prime example of this.\n\n    >>> decimal_encoder(Decimal(\"1.0\"))\n    1.0\n\n    >>> decimal_encoder(Decimal(\"1\"))\n    1\n\n    >>> decimal_encoder(Decimal(\"NaN\"))\n    nan\n    \"\"\"\n    exponent = dec_value.as_tuple().exponent\n    if isinstance(exponent, int) and exponent >= 0:\n        return int(dec_value)\n    else:\n        return float(dec_value)\n\n\nENCODERS_BY_TYPE: Dict[Type[Any], Callable[[Any], Any]] = {\n    bytes: lambda o: o.decode(),\n    Color: str,\n    may_v1.Color: str,\n    datetime.date: isoformat,\n    datetime
21run_command
{
 "command": "sed -n '200,350p' fastapi/encoders.py"
}
{"status": "ok", "stdout": " \"\"\"\n ),\n ] = True,\n) -> Any:\n \"\"\"\n Convert any object to something that can be encoded in JSON.\n\n This is used interna
full
{"status": "ok", "stdout": "            \"\"\"\n        ),\n    ] = True,\n) -> Any:\n    \"\"\"\n    Convert any object to something that can be encoded in JSON.\n\n    This is used internally by FastAPI to make sure anything you return can be\n    encoded as JSON before it is sent to the client.\n\n    You can also use it yourself, for example to convert objects before saving them\n    in a database that supports only JSON.\n\n    Read more about it in the\n    [FastAPI docs for JSON Compatible Encoder](https://fastapi.tiangolo.com/tutorial/encoder/).\n    \"\"\"\n    custom_encoder = custom_encoder or {}\n    if custom_encoder:\n        if type(obj) in custom_encoder:\n            return custom_encoder[type(obj)](obj)\n        else:\n            for encoder_type, encoder_instance in custom_encoder.items():\n                if isinstance(obj, encoder_type):\n                    return encoder_instance(obj)\n    if include is not None and not isinstance(include, (set, dict)):\n        include = set(include)\n    if exclude is not None and not isinstance(exclude, (set, dict)):\n        exclude = set(exclude)\n    if isinstance(obj, (BaseModel, may_v1.BaseModel)):\n        # TODO: remove when deprecating Pydantic v1\n        encoders: Dict[Any, Any] = {}\n        if isinstance(obj, may_v1.BaseModel):\n            encoders = getattr(obj.__config__, \"json_encoders\", {})  # type: ignore[attr-defined]\n            if custom_encoder:\n                encoders = {**encoders, **custom_encoder}\n        obj_dict = _model_dump(\n            obj,\n            mode=\"json\",\n            include=include,\n            exclude=exclude,\n            by_alias=by_alias,\n            exclude_unset=exclude_unset,\n            exclude_none=exclude_none,\n            exclude_defaults=exclude_defaults,\n        )\n        if \"__root__\" in obj_dict:\n            obj_dict = obj_dict[\"__root__\"]\n        return jsonable_encoder(\n            obj_dict,\n            exclude_none=exclude
22run_command
{
 "command": "sed -n '340,360p' fastapi/encoders.py"
}
{"status": "ok", "stdout": " errors.append(e)\n try:\n data = vars(obj)\n except Exception as e:\n errors.append(e)\n raise ValueError(errors) from e\n return j
full
{"status": "ok", "stdout": "        errors.append(e)\n        try:\n            data = vars(obj)\n        except Exception as e:\n            errors.append(e)\n            raise ValueError(errors) from e\n    return jsonable_encoder(\n        data,\n        include=include,\n        exclude=exclude,\n        by_alias=by_alias,\n        exclude_unset=exclude_unset,\n        exclude_defaults=exclude_defaults,\n        exclude_none=exclude_none,\n        custom_encoder=custom_encoder,\n        sqlalchemy_safe=sqlalchemy_safe,\n    )\n", "stderr": "", "exit_code": 0}
23run_command
{
 "command": "sed -n '310,350p' fastapi/encoders.py"
}
{"status": "ok", "stdout": " encoded_dict[encoded_key] = encoded_value\n return encoded_dict\n if isinstance(obj, (list, set, frozenset, GeneratorType, tuple, d
full
{"status": "ok", "stdout": "                encoded_dict[encoded_key] = encoded_value\n        return encoded_dict\n    if isinstance(obj, (list, set, frozenset, GeneratorType, tuple, deque)):\n        encoded_list = []\n        for item in obj:\n            encoded_list.append(\n                jsonable_encoder(\n                    item,\n                    include=include,\n                    exclude=exclude,\n                    by_alias=by_alias,\n                    exclude_unset=exclude_unset,\n                    exclude_defaults=exclude_defaults,\n                    exclude_none=exclude_none,\n                    custom_encoder=custom_encoder,\n                    sqlalchemy_safe=sqlalchemy_safe,\n                )\n            )\n        return encoded_list\n\n    if type(obj) in ENCODERS_BY_TYPE:\n        return ENCODERS_BY_TYPE[type(obj)](obj)\n    for encoder, classes_tuple in encoders_by_class_tuples.items():\n        if isinstance(obj, classes_tuple):\n            return encoder(obj)\n\n    try:\n        data = dict(obj)\n    except Exception as e:\n        errors: List[Exception] = []\n        errors.append(e)\n        try:\n            data = vars(obj)\n        except Exception as e:\n            errors.append(e)\n            raise ValueError(errors) from e\n    return jsonable_encoder(\n        data,\n        include=include,\n        exclude=exclude,\n        by_alias=by_alias,\n", "stderr": "", "exit_code": 0}
24run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\nprint(f\"Object: {obj}\")\ntry:\n    encoded = jsonable_encoder(obj)\n    print(f\"Encoded: {encoded}\")\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "Object: attr=MyType(test)\nError: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "Object: attr=MyType(test)\nError: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
25run_command
{
 "command": "grep -rn 'Unable to serialize unknown type' ."
}
{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}
full
{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}
26run_command
{
 "command": "grep -rn 'Unable to serialize unknown type' /workspace/fastapi/encoders.py"
}
{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}
full
{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}
27run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\ntry:\n    encoded = jsonable_encoder(obj)\n    print(encoded)\nexcept Exception as e:\n    import traceback\n    traceback.print_exc()\nPY\n"
}
{"status": "ok", "stdout": "", "stderr": "Traceback (most recent call last):\n File \"<stdin>\", line 17, in <module>\n File \"/private/workspace/fastapi/encode
full
{"status": "ok", "stdout": "", "stderr": "Traceback (most recent call last):\n  File \"<stdin>\", line 17, in <module>\n  File \"/private/workspace/fastapi/encoders.py\", line 235, in jsonable_encoder\n    obj_dict = _model_dump(\n        obj,\n    ...<6 lines>...\n        exclude_defaults=exclude_defaults,\n    )\n  File \"/private/workspace/fastapi/_compat/main.py\", line 95, in _model_dump\n    return v2._model_dump(model, mode=mode, **kwargs)\n           ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/private/workspace/fastapi/_compat/v2.py\", line 167, in _model_dump\n    return model.model_dump(mode=mode, **kwargs)\n           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^\n  File \"/Users/jp/repos/kaggle-gemini-coding-agent-post-training/.envs/fastapi/lib/python3.13/site-packages/pydantic/main.py\", line 475, in model_dump\n    return self.__pydantic_serializer__.to_python(\n           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n        self,\n        ^^^^^\n    ...<13 lines>...\n        polymorphic_serialization=polymorphic_serialization,\n        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n    )\n    ^\npydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class '__main__.MyType'>\n", "exit_code": 0}
28run_command
{
 "command": "grep -rn 'Unable to serialize unknown type' /Users/jp/repos/kaggle-gemini-coding-agent-post-training/.envs/fastapi/lib/python3.13/site-packages/pydantic/main.py"
}
{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}
full
{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}
29run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\ntry:\n    # Change mode to 'python' to see if pydantic allows it\n    from fastapi._compat.v2 import _model_dump\n    # _model_dump is what fastapi uses\n    # let's try calling pydantic's model_dump directly with mode='python'\n    print(obj.model_dump(mode='python'))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "{'attr': MyType(test)}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': MyType(test)}\n", "stderr": "", "exit_code": 0}
30run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\ntry:\n    print(obj.model_dump(mode='json'))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "Error: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "Error: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
31run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\ntry:\n    # Try to see if we can use a custom serializer or something\n    # Actually the issue is that when mode='json', Pydantic tries to serialize everything to JSON\n    # If it doesn't know how, it fails even if arbitrary_types_allowed=True.\n    # But arbitrary_types_allowed=True is for VALIDATION, not SERIALIZATION.\n    # For serialization, we need to provide a way to serialize the type.\n    print(obj.model_dump(mode='python'))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "{'attr': MyType(test)}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': MyType(test)}\n", "stderr": "", "exit_code": 0}
32run_command
{
 "command": "sed -n '230,245p' fastapi/encoders.py"
}
{"status": "ok", "stdout": " encoders: Dict[Any, Any] = {}\n if isinstance(obj, may_v1.BaseModel):\n encoders = getattr(obj.__config__, \"json_encoders\", {}) #
full
{"status": "ok", "stdout": "        encoders: Dict[Any, Any] = {}\n        if isinstance(obj, may_v1.BaseModel):\n            encoders = getattr(obj.__config__, \"json_encoders\", {})  # type: ignore[attr-defined]\n            if custom_encoder:\n                encoders = {**encoders, **custom_encoder}\n        obj_dict = _model_dump(\n            obj,\n            mode=\"json\",\n            include=include,\n            exclude=exclude,\n            by_alias=by_alias,\n            exclude_unset=exclude_unset,\n            exclude_none=exclude_none,\n            exclude_defaults=exclude_defaults,\n        )\n        if \"__root__\" in obj_dict:\n", "stderr": "", "exit_code": 0}
33run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n# If we change mode to 'python' in _model_dump, it should work.\n# Then jsonable_encoder will recursively handle the results.\nfrom fastapi._compat import _model_dump\ntry:\n    res = _model_dump(obj, mode='python')\n    print(f\"Model dump python: {res}\")\n    # Now we need to make sure it's actually \"jsonable\"\n    # The original jsonable_encoder calls itself recursively.\n    # So if we use mode='python', it will return the MyType object,\n    # and the outer jsonable_encoder call will then try to handle it.\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "Model dump python: {'attr': MyType(test)}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "Model dump python: {'attr': MyType(test)}\n", "stderr": "", "exit_code": 0}
34run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# If we use jsonable_encoder, it uses mode='json'\ntry:\n    print(jsonable_encoder(obj))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "Error: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "Error: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
35run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# Let's try to manually do what jsonable_encoder should do if it wanted to support arbitrary types:\n# 1. model_dump(mode='python')\n# 2. recursively call jsonable_encoder on the result.\n\ndef custom_jsonable_encoder(obj):\n    if isinstance(obj, BaseModel):\n        return custom_jsonable_encoder(obj.model_dump(mode='python'))\n    if isinstance(obj, dict):\n        return {k: custom_jsonable_encoder(v) for k, v in obj.items()}\n    if isinstance(obj, list):\n        return [custom_jsonable_encoder(i) for i in obj]\n    # Fallback to some basic conversion or just return if it's a basic type\n    if isinstance(obj, (str, int, float, bool, type(None))):\n        return obj\n    return str(obj) # simplified\n\nprint(custom_jsonable_encoder(obj))\nPY\n"
}
{"status": "ok", "stdout": "{'attr': 'MyType(test)'}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': 'MyType(test)'}\n", "stderr": "", "exit_code": 0}
36run_command
{
 "command": "sed -n '235,245p' fastapi/encoders.py"
}
{"status": "ok", "stdout": " obj_dict = _model_dump(\n obj,\n mode=\"json\",\n include=include,\n exclude=exclude,\n by_alias=by_alias,\n exclude_unset=exclude_
full
{"status": "ok", "stdout": "        obj_dict = _model_dump(\n            obj,\n            mode=\"json\",\n            include=include,\n            exclude=exclude,\n            by_alias=by_alias,\n            exclude_unset=exclude_unset,\n            exclude_none=exclude_none,\n            exclude_defaults=exclude_defaults,\n        )\n        if \"__root__\" in obj_dict:\n", "stderr": "", "exit_code": 0}
37run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\ntry:\n    # Test if we can pass custom_encoder to handle MyType\n    print(jsonable_encoder(obj, custom_encoder={MyType: lambda x: str(x)}))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "Error: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "Error: Unable to serialize unknown type: <class '__main__.MyType'>\n", "stderr": "", "exit_code": 0}
38run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# Try to see what happens if we use a Pydantic v1 model\n# since the code has a TODO: remove when deprecating Pydantic v1\nPY\n"
}
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
39run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# I want to see if changing mode='json' to mode='python' in _model_dump fixes it\n# I will mock _model_dump in fastapi.encoders\nimport fastapi.encoders\nfrom fastapi._compat import _model_dump\n\noriginal_model_dump = _model_dump\n\ndef mocked_model_dump(obj, **kwargs):\n    if 'mode' in kwargs and kwargs['mode'] == 'json':\n        kwargs['mode'] = 'python'\n    return original_model_dump(obj, **kwargs)\n\n# This is a bit hacky because _model_dump is imported into encoders.py\n# Let's just try to see if it works.\nimport fastapi.encoders\nfastapi.encoders._model_dump = mocked_model_dump\n\ntry:\n    print(jsonable_encoder(obj))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
40run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# Let's see what happened when we used mode='python'\n# The result was {'attr': {'val': 'test'}}. \n# Wait, why did it become a dict? \n# Oh, maybe MyType has __dict__? \n# Let's check.\nprint(vars(MyType(\"test\")))\nPY\n"
}
{"status": "ok", "stdout": "{'val': 'test'}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'val': 'test'}\n", "stderr": "", "exit_code": 0}
41run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n    def __getattr__(self, name):\n        raise AttributeError\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\nimport fastapi.encoders\nfrom fastapi._compat import _model_dump\noriginal_model_dump = _model_dump\ndef mocked_model_dump(obj, **kwargs):\n    if 'mode' in kwargs and kwargs['mode'] == 'json':\n        kwargs['mode'] = 'python'\n    return original_model_dump(obj, **kwargs)\nfastapi.encoders._model_dump = mocked_model_dump\n\ntry:\n    print(jsonable_encoder(obj))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
42run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n    def __getattr__(self, name):\n        raise AttributeError\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# If we use mode='python', it will return MyType(test)\n# And then jsonable_encoder will call itself on MyType(test)\n# Then it will try dict(MyType(test)) or vars(MyType(test))\n# This will likely result in {'val': 'test'}\nPY\n"
}
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}
43run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\nimport fastapi.encoders\nfrom fastapi._compat import _model_dump\noriginal_model_dump = _model_dump\ndef mocked_model_dump(obj, **kwargs):\n    if 'mode' in kwargs and kwargs['mode'] == 'json':\n        kwargs['mode'] = 'python'\n    return original_model_dump(obj, **kwargs)\nfastapi.encoders._model_dump = mocked_model_dump\n\nprint(jsonable_encoder(obj))\nPY\n"
}
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
44run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# What if MyType does NOT have __dict__?\nclass NoDictType:\n    def __init__(self, val):\n        self.val = val\n    def __setattr__(self, name, value):\n        # store in a private way to avoid __dict__\n        self._data = {name: value} if not hasattr(self, '_data') else self._data\n        self._data[name] = value\n    def __getattr__(self, name):\n        return self._data[name]\n    def __repr__(self):\n        return f\"NoDictType({self._data})\"\n    def __dir__(self):\n        return list(self._data.keys())\n\nclass Model2(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: NoDictType\n\nobj2 = Model2(attr=NoDictType(\"test\"))\n\nimport fastapi.encoders\nfrom fastapi._compat import _model_dump\noriginal_model_dump = _model_dump\ndef mocked_model_dump(obj, **kwargs):\n    if 'mode' in kwargs and kwargs['mode'] == 'json':\n        kwargs['mode'] = 'python'\n    return original_model_dump(obj, **kwargs)\nfastapi.encoders._model_dump = mocked_model_dump\n\ntry:\n    print(jsonable_encoder(obj2))\nexcept Exception as e:\n    print(f\"Error: {e}\")\nPY\n"
}
{"status": "error", "error_type": "CommandError", "error_message": "Traceback (most recent call last):\n File \"<stdin>\", line 36, in <module>\n File \"<stdin>
full
{"status": "error", "error_type": "CommandError", "error_message": "Traceback (most recent call last):\n  File \"<stdin>\", line 36, in <module>\n  File \"<stdin>\", line 20, in __init__\n  File \"<stdin>\", line 23, in __setattr__\n  File \"<stdin>\", line 26, in __getattr__\n  File \"<stdin>\", line 26, in __getattr__\n  File \"<stdin>\", line 26, in __getattr__\n  [Previous line repeated 994 more times]\nRecursionError: maximum recursion depth exceeded\n", "details": {"stdout": "", "stderr": "Traceback (most recent call last):\n  File \"<stdin>\", line 36, in <module>\n  File \"<stdin>\", line 20, in __init__\n  File \"<stdin>\", line 23, in __setattr__\n  File \"<stdin>\", line 26, in __getattr__\n  File \"<stdin>\", line 26, in __getattr__\n  File \"<stdin>\", line 26, in __getattr__\n  [Previous line repeated 994 more times]\nRecursionError: maximum recursion depth exceeded\n", "exit_code": 1}}
45run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\nimport fastapi.encoders\nfrom fastapi._compat import _model_dump\noriginal_model_dump = _model_dump\ndef mocked_model_dump(obj, **kwargs):\n    if 'mode' in kwargs and kwargs['mode'] == 'json':\n        kwargs['mode'] = 'python'\n    return original_model_dump(obj, **kwargs)\nfastapi.encoders._model_dump = mocked_model_dump\n\nprint(jsonable_encoder(obj))\nPY\n"
}
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
46run_command
{
 "command": "python3 - <<'PY'\nfrom pydantic import BaseModel, ConfigDict\nfrom fastapi.encoders import jsonable_encoder\nimport uuid\n\nclass MyType:\n    def __init__(self, val):\n        self.val = val\n    def __repr__(self):\n        return f\"MyType({self.val})\"\n\nclass Model(BaseModel):\n    model_config = ConfigDict(arbitrary_types_allowed=True)\n    attr: MyType\n\nobj = Model(attr=MyType(\"test\"))\n\n# If we use mode='python', it will return MyType(test).\n# Then jsonable_encoder is called on MyType(test).\n# Inside jsonable_encoder:\n# 1. Not a BaseModel.\n# 2. Not a dataclass.\n# 3. Not an Enum, PurePath, str, int, float, None.\n# 4. Not undefined.\n# 5. Not a dict.\n# 6. Not a list/set/tuple/etc.\n# 7. Not in ENCODERS_BY_TYPE.\n# 8. Not in encoders_by_class_tuples.\n# 9. Try dict(obj) -> fails.\n# 10. Try vars(obj) -> succeeds! returns {'val': 'test'}.\n# 11. Call jsonable_encoder({'val': 'test'}) -> returns {'val': 'test'}.\n# This is exactly what we want!\n\nimport fastapi.encoders\nfrom fastapi._compat import _model_dump\noriginal_model_dump = _model_dump\ndef mocked_model_dump(obj, **kwargs):\n    if 'mode' in kwargs and kwargs['mode'] == 'json':\n        kwargs['mode'] = 'python'\n    return original_model_dump(obj, **kwargs)\nfastapi.encoders._model_dump = mocked_model_dump\n\nprint(jsonable_encoder(obj))\nPY\n"
}
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}
full
{"status": "ok", "stdout": "{'attr': {'val': 'test'}}\n", "stderr": "", "exit_code": 0}