fastapi_11355

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{"status": "ok", "stdout": "fastapi/datastructures.py:1:from typing import (\nfastapi/datastructures.py:26:from typing_extensions import Annotated\nfastapi/datastructures.py:45:    from typing import Annotated\nfastapi/dependencies/models.py:5:from typing import Any, Callable, List, Optional, Sequence, Union\nfastapi/dependencies/models.py:10:from typing_extensions import Literal\nfastapi/dependencies/utils.py:6:from typing import (\nfastapi/dependencies/utils.py:78:from typing_extensions import Annotated, Literal, get_args, get_origin\nfastapi/dependencies/utils.py:840:    # Check if it's a Union type (covers both typing.Union and types.UnionType in Python 3.10+)\nfastapi/_compat/may_v1.py:2:from typing import Any, Dict, List, Literal, Sequence, Tuple, Type, Union\nfastapi/_compat/shared.py:3:import typing\nfastapi/_compat/shared.py:6:from typing import (\nfastapi/_compat/shared.py:24:from typing_extensions import Annotated, get_args, get_origin\nfastapi/_compat/shared.py:34:    WithArgsTypes: tuple[Any, ...] = (typing._GenericAlias, types.GenericAlias)  # type: ignore[attr-defined]\nfastapi/_compat/shared.py:37:        typing._GenericAlias,  # type: ignore[attr-defined]\nfastapi/_compat/v1.py:4:from typing import (\nfastapi/_compat/v1.py:20:from typing_extensions import Literal\nfastapi/_compat/v1.py:25:# shadowing typing.Required.\nfastapi/_compat/v1.py:69:    from pydantic.typing import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/v1.py:122:    from pydantic.v1.typing import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/main.py:3:from typing import (\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "fastapi/dependencies/utils.py:33:    evaluate_forwardref,\nfastapi/dependencies/utils.py:213:        annotation = evaluate_forwardref(annotation, globalns, globalns)\nfastapi/_compat/__init__.py:17:from .main import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/v1.py:69:    from pydantic.typing import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/v1.py:122:    from pydantic.v1.typing import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/main.py:29:    from .v2 import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/main.py:45:    from .v1 import evaluate_forwardref as evaluate_forwardref\nfastapi/_compat/v2.py:50:evaluate_forwardref = eval_type_lenient\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "import re\nimport warnings\nfrom copy import copy, deepcopy\nfrom dataclasses import dataclass\nfrom enum import Enum\nfrom typing import (\n    Any,\n    Dict,\n    List,\n    Sequence,\n    Set,\n    Tuple,\n    Type,\n    Union,\n    cast,\n)\n\nfrom fastapi._compat import may_v1, shared\nfrom fastapi.openapi.constants import REF_TEMPLATE\nfrom fastapi.types import IncEx, ModelNameMap, UnionType\nfrom pydantic import BaseModel, TypeAdapter, create_model\nfrom pydantic import PydanticSchemaGenerationError as PydanticSchemaGenerationError\nfrom pydantic import PydanticUndefinedAnnotation as PydanticUndefinedAnnotation\nfrom pydantic import ValidationError as ValidationError\nfrom pydantic._internal._schema_generation_shared import (  # type: ignore[attr-defined]\n    GetJsonSchemaHandler as GetJsonSchemaHandler,\n)\nfrom pydantic._internal._typing_extra import eval_type_lenient\nfrom pydantic._internal._utils import lenient_issubclass as lenient_issubclass\nfrom pydantic.fields import FieldInfo as FieldInfo\nfrom pydantic.json_schema import GenerateJsonSchema as GenerateJsonSchema\nfrom pydantic.json_schema import JsonSchemaValue as JsonSchemaValue\nfrom pydantic_core import CoreSchema as CoreSchema\nfrom pydantic_core import PydanticUndefined, PydanticUndefinedType\nfrom pydantic_core import Url as Url\nfrom typing_extensions import Annotated, Literal, get_args, get_origin\n\ntry:\n    from pydantic_core.core_schema import (\n        with_info_plain_validator_function as with_info_plain_validator_function,\n    )\nexcept ImportError:  # pragma: no cover\n    from pydantic_core.core_schema import (\n        general_plain_validator_function as with_info_plain_validator_function,  # noqa: F401\n    )\n\nRequiredParam = PydanticUndefined\nUndefined = PydanticUndefined\nUndefinedType = PydanticUndefinedType\nevaluate_forwardref = eval_type_lenient\nValidator = Any\n\n\nclass BaseConfig:\n    pass\n\n\nclass ErrorWrapper(Exception):\n    pass

{"status": "ok", "stdout": "import dataclasses\nimport inspect\nfrom contextlib import AsyncExitStack, contextmanager\nfrom copy import copy, deepcopy\nfrom dataclasses import dataclass\nfrom typing import (\n    Any,\n    Callable,\n    Coroutine,\n    Dict,\n    ForwardRef,\n    List,\n    Mapping,\n    Optional,\n    Sequence,\n    Tuple,\n    Type,\n    Union,\n    cast,\n)\n\nimport anyio\nfrom fastapi import params\nfrom fastapi._compat import (\n    PYDANTIC_V2,\n    ModelField,\n    RequiredParam,\n    Undefined,\n    _is_error_wrapper,\n    _is_model_class,\n    copy_field_info,\n    create_body_model,\n    evaluate_forwardref,\n    field_annotation_is_scalar,\n    get_annotation_from_field_info,\n    get_cached_model_fields,\n    get_missing_field_error,\n    is_bytes_field,\n    is_bytes_sequence_field,\n    is_scalar_field,\n    is_scalar_sequence_field,\n    is_sequence_field,\n    is_uploadfile_or_nonable_uploadfile_annotation,\n    is_uploadfile_sequence_annotation,\n    lenient_issubclass,\n    may_v1,\n    sequence_types,\n    serialize_sequence_value,\n    value_is_sequence,\n)\nfrom fastapi._compat.shared import annotation_is_pydantic_v1\nfrom fastapi.background import BackgroundTasks\nfrom fastapi.concurrency import (\n    asynccontextmanager,\n    contextmanager_in_threadpool,\n)\nfrom fastapi.dependencies.models import Dependant, SecurityRequirement\nfrom fastapi.exceptions import DependencyScopeError\nfrom fastapi.logger import logger\nfrom fastapi.security.base import SecurityBase\nfrom fastapi.security.oauth2 import SecurityScopes\nfrom fastapi.types import DependencyCacheKey\nfrom fastapi.utils import create_model_field, get_path_param_names\nfrom pydantic import BaseModel\nfrom pydantic.fields import FieldInfo\nfrom starlette.background import BackgroundTasks as StarletteBackgroundTasks\nfrom starlette.concurrency import run_in_threadpool\nfrom starlette.datastructures import (\n    FormData,\n    Headers,\n    ImmutableMultiDict,\n    Que

{"status": "ok", "stdout": "            kind=param.kind,\n            default=param.default,\n            annotation=get_typed_annotation(param.annotation, globalns),\n        )\n        for param in signature.parameters.values()\n    ]\n    typed_signature = inspect.Signature(typed_params)\n    return typed_signature\n\n\ndef get_typed_annotation(annotation: Any, globalns: Dict[str, Any]) -> Any:\n    if isinstance(annotation, str):\n        annotation = ForwardRef(annotation)\n        annotation = evaluate_forwardref(annotation, globalns, globalns)\n        if annotation is type(None):\n            return None\n    return annotation\n\n\ndef get_typed_return_annotation(call: Callable[..., Any]) -> Any:\n    signature = inspect.signature(call)\n    unwrapped = inspect.unwrap(call)\n    annotation = signature.return_annotation\n\n    if annotation is inspect.Signature.empty:\n        return None\n\n    globalns = getattr(unwrapped, \"__globals__\", {})\n    return get_typed_annotation(annotation, globalns)\n\n\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "<function get_type_hints at 0x7a30ecdbf7e0>\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "Return type hints for an object.\n\nThis is often the same as inspect.get_annotations(obj) or obj.__annotations__,\nbut it handles forward references encoded as string literals and recursively replaces all\n'Annotated[T, ...]' with 'T' (unless 'include_extras=True').\n\nThe argument may be a module, class, method, or function. The annotations\nare returned as a dictionary. For classes, annotations include also\ninherited members.\n\nTypeError is raised if the argument is not of a type that can contain\nannotations, and an empty dictionary is returned if no annotations are\npresent.\n\nBEWARE -- the behavior of globalns and localns is counterintuitive\n(unless you are familiar with how eval() and exec() work).  The\nsearch order is locals first, then globals.\n\n- If no dict arguments are passed, an attempt is made to use the\n  globals from obj (or the respective module's globals for classes),\n  and these are also used as the locals.  If the object does not appear\n  to have globals, an empty dictionary is used.  For classes, the search\n  order is globals first then locals.\n\n- If one dict argument is passed, it is used for both globals and\n  locals.\n\n- If two dict arguments are passed, they specify globals and\n  locals, respectively.\n\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "Result: <class 'int'>\nSuccess\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "Result: <class 'int'>\nSuccess\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "Annotation: MyType, Type: <class 'str'>\nResult: <class '__main__.MyType'>\nSuccess\n", "stderr": "", "exit_code": 0}

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{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}