Загрузить файлы в «venv/Lib/site-packages/pydantic/v1»

venv/Lib/site-packages/pydantic/v1/tools.py

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+import json
+from functools import lru_cache
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, Callable, Optional, Type, TypeVar, Union
+
+from pydantic.v1.parse import Protocol, load_file, load_str_bytes
+from pydantic.v1.types import StrBytes
+from pydantic.v1.typing import display_as_type
+
+__all__ = ('parse_file_as', 'parse_obj_as', 'parse_raw_as', 'schema_of', 'schema_json_of')
+
+NameFactory = Union[str, Callable[[Type[Any]], str]]
+
+if TYPE_CHECKING:
+    from pydantic.v1.typing import DictStrAny
+
+
+def _generate_parsing_type_name(type_: Any) -> str:
+    return f'ParsingModel[{display_as_type(type_)}]'
+
+
+@lru_cache(maxsize=2048)
+def _get_parsing_type(type_: Any, *, type_name: Optional[NameFactory] = None) -> Any:
+    from pydantic.v1.main import create_model
+
+    if type_name is None:
+        type_name = _generate_parsing_type_name
+    if not isinstance(type_name, str):
+        type_name = type_name(type_)
+    return create_model(type_name, __root__=(type_, ...))
+
+
+T = TypeVar('T')
+
+
+def parse_obj_as(type_: Type[T], obj: Any, *, type_name: Optional[NameFactory] = None) -> T:
+    model_type = _get_parsing_type(type_, type_name=type_name)  # type: ignore[arg-type]
+    return model_type(__root__=obj).__root__
+
+
+def parse_file_as(
+    type_: Type[T],
+    path: Union[str, Path],
+    *,
+    content_type: str = None,
+    encoding: str = 'utf8',
+    proto: Protocol = None,
+    allow_pickle: bool = False,
+    json_loads: Callable[[str], Any] = json.loads,
+    type_name: Optional[NameFactory] = None,
+) -> T:
+    obj = load_file(
+        path,
+        proto=proto,
+        content_type=content_type,
+        encoding=encoding,
+        allow_pickle=allow_pickle,
+        json_loads=json_loads,
+    )
+    return parse_obj_as(type_, obj, type_name=type_name)
+
+
+def parse_raw_as(
+    type_: Type[T],
+    b: StrBytes,
+    *,
+    content_type: str = None,
+    encoding: str = 'utf8',
+    proto: Protocol = None,
+    allow_pickle: bool = False,
+    json_loads: Callable[[str], Any] = json.loads,
+    type_name: Optional[NameFactory] = None,
+) -> T:
+    obj = load_str_bytes(
+        b,
+        proto=proto,
+        content_type=content_type,
+        encoding=encoding,
+        allow_pickle=allow_pickle,
+        json_loads=json_loads,
+    )
+    return parse_obj_as(type_, obj, type_name=type_name)
+
+
+def schema_of(type_: Any, *, title: Optional[NameFactory] = None, **schema_kwargs: Any) -> 'DictStrAny':
+    """Generate a JSON schema (as dict) for the passed model or dynamically generated one"""
+    return _get_parsing_type(type_, type_name=title).schema(**schema_kwargs)
+
+
+def schema_json_of(type_: Any, *, title: Optional[NameFactory] = None, **schema_json_kwargs: Any) -> str:
+    """Generate a JSON schema (as JSON) for the passed model or dynamically generated one"""
+    return _get_parsing_type(type_, type_name=title).schema_json(**schema_json_kwargs)

venv/Lib/site-packages/pydantic/v1/typing.py

@@ -0,0 +1,627 @@
+import functools
+import operator
+import sys
+import typing
+from collections.abc import Callable
+from os import PathLike
+from typing import (  # type: ignore
+    TYPE_CHECKING,
+    AbstractSet,
+    Any,
+    Callable as TypingCallable,
+    ClassVar,
+    Dict,
+    ForwardRef,
+    Generator,
+    Iterable,
+    List,
+    Mapping,
+    NewType,
+    Optional,
+    Sequence,
+    Set,
+    Tuple,
+    Type,
+    TypeVar,
+    Union,
+    _eval_type,
+    cast,
+    get_type_hints,
+)
+
+from typing_extensions import (
+    Annotated,
+    Final,
+    Literal,
+    NotRequired as TypedDictNotRequired,
+    Required as TypedDictRequired,
+)
+
+try:
+    from typing import _TypingBase as typing_base  # type: ignore
+except ImportError:
+    from typing import _Final as typing_base  # type: ignore
+
+try:
+    from typing import GenericAlias as TypingGenericAlias  # type: ignore
+except ImportError:
+    # python < 3.9 does not have GenericAlias (list[int], tuple[str, ...] and so on)
+    TypingGenericAlias = ()
+
+try:
+    from types import UnionType as TypesUnionType  # type: ignore
+except ImportError:
+    # python < 3.10 does not have UnionType (str | int, byte | bool and so on)
+    TypesUnionType = ()
+
+
+if sys.version_info < (3, 9):
+
+    def evaluate_forwardref(type_: ForwardRef, globalns: Any, localns: Any) -> Any:
+        return type_._evaluate(globalns, localns)
+
+elif sys.version_info < (3, 12, 4):
+
+    def evaluate_forwardref(type_: ForwardRef, globalns: Any, localns: Any) -> Any:
+        # Even though it is the right signature for python 3.9, mypy complains with
+        # `error: Too many arguments for "_evaluate" of "ForwardRef"` hence the cast...
+        # Python 3.13/3.12.4+ made `recursive_guard` a kwarg, so name it explicitly to avoid:
+        # TypeError: ForwardRef._evaluate() missing 1 required keyword-only argument: 'recursive_guard'
+        return cast(Any, type_)._evaluate(globalns, localns, recursive_guard=set())
+
+elif sys.version_info < (3, 14):
+
+    def evaluate_forwardref(type_: ForwardRef, globalns: Any, localns: Any) -> Any:
+        # Pydantic 1.x will not support PEP 695 syntax, but provide `type_params` to avoid
+        # warnings:
+        return cast(Any, type_)._evaluate(globalns, localns, type_params=(), recursive_guard=set())
+
+else:
+
+    def evaluate_forwardref(type_: ForwardRef, globalns: Any, localns: Any) -> Any:
+        # Pydantic 1.x will not support PEP 695 syntax, but provide `type_params` to avoid
+        # warnings:
+        return typing.evaluate_forward_ref(
+            type_,
+            globals=globalns,
+            locals=localns,
+            type_params=(),
+            _recursive_guard=set(),
+        )
+
+
+if sys.version_info < (3, 9):
+    # Ensure we always get all the whole `Annotated` hint, not just the annotated type.
+    # For 3.7 to 3.8, `get_type_hints` doesn't recognize `typing_extensions.Annotated`,
+    # so it already returns the full annotation
+    get_all_type_hints = get_type_hints
+
+else:
+
+    def get_all_type_hints(obj: Any, globalns: Any = None, localns: Any = None) -> Any:
+        return get_type_hints(obj, globalns, localns, include_extras=True)
+
+
+_T = TypeVar('_T')
+
+AnyCallable = TypingCallable[..., Any]
+NoArgAnyCallable = TypingCallable[[], Any]
+
+# workaround for https://github.com/python/mypy/issues/9496
+AnyArgTCallable = TypingCallable[..., _T]
+
+
+# Annotated[...] is implemented by returning an instance of one of these classes, depending on
+# python/typing_extensions version.
+AnnotatedTypeNames = {'AnnotatedMeta', '_AnnotatedAlias'}
+
+
+LITERAL_TYPES: Set[Any] = {Literal}
+if hasattr(typing, 'Literal'):
+    LITERAL_TYPES.add(typing.Literal)
+
+
+if sys.version_info < (3, 8):
+
+    def get_origin(t: Type[Any]) -> Optional[Type[Any]]:
+        if type(t).__name__ in AnnotatedTypeNames:
+            # weirdly this is a runtime requirement, as well as for mypy
+            return cast(Type[Any], Annotated)
+        return getattr(t, '__origin__', None)
+
+else:
+    from typing import get_origin as _typing_get_origin
+
+    def get_origin(tp: Type[Any]) -> Optional[Type[Any]]:
+        """
+        We can't directly use `typing.get_origin` since we need a fallback to support
+        custom generic classes like `ConstrainedList`
+        It should be useless once https://github.com/cython/cython/issues/3537 is
+        solved and https://github.com/pydantic/pydantic/pull/1753 is merged.
+        """
+        if type(tp).__name__ in AnnotatedTypeNames:
+            return cast(Type[Any], Annotated)  # mypy complains about _SpecialForm
+        return _typing_get_origin(tp) or getattr(tp, '__origin__', None)
+
+
+if sys.version_info < (3, 8):
+    from typing import _GenericAlias
+
+    def get_args(t: Type[Any]) -> Tuple[Any, ...]:
+        """Compatibility version of get_args for python 3.7.
+
+        Mostly compatible with the python 3.8 `typing` module version
+        and able to handle almost all use cases.
+        """
+        if type(t).__name__ in AnnotatedTypeNames:
+            return t.__args__ + t.__metadata__
+        if isinstance(t, _GenericAlias):
+            res = t.__args__
+            if t.__origin__ is Callable and res and res[0] is not Ellipsis:
+                res = (list(res[:-1]), res[-1])
+            return res
+        return getattr(t, '__args__', ())
+
+else:
+    from typing import get_args as _typing_get_args
+
+    def _generic_get_args(tp: Type[Any]) -> Tuple[Any, ...]:
+        """
+        In python 3.9, `typing.Dict`, `typing.List`, ...
+        do have an empty `__args__` by default (instead of the generic ~T for example).
+        In order to still support `Dict` for example and consider it as `Dict[Any, Any]`,
+        we retrieve the `_nparams` value that tells us how many parameters it needs.
+        """
+        if hasattr(tp, '_nparams'):
+            return (Any,) * tp._nparams
+        # Special case for `tuple[()]`, which used to return ((),) with `typing.Tuple`
+        # in python 3.10- but now returns () for `tuple` and `Tuple`.
+        # This will probably be clarified in pydantic v2
+        try:
+            if tp == Tuple[()] or sys.version_info >= (3, 9) and tp == tuple[()]:  # type: ignore[misc]
+                return ((),)
+        # there is a TypeError when compiled with cython
+        except TypeError:  # pragma: no cover
+            pass
+        return ()
+
+    def get_args(tp: Type[Any]) -> Tuple[Any, ...]:
+        """Get type arguments with all substitutions performed.
+
+        For unions, basic simplifications used by Union constructor are performed.
+        Examples::
+            get_args(Dict[str, int]) == (str, int)
+            get_args(int) == ()
+            get_args(Union[int, Union[T, int], str][int]) == (int, str)
+            get_args(Union[int, Tuple[T, int]][str]) == (int, Tuple[str, int])
+            get_args(Callable[[], T][int]) == ([], int)
+        """
+        if type(tp).__name__ in AnnotatedTypeNames:
+            return tp.__args__ + tp.__metadata__
+        # the fallback is needed for the same reasons as `get_origin` (see above)
+        return _typing_get_args(tp) or getattr(tp, '__args__', ()) or _generic_get_args(tp)
+
+
+if sys.version_info < (3, 9):
+
+    def convert_generics(tp: Type[Any]) -> Type[Any]:
+        """Python 3.9 and older only supports generics from `typing` module.
+        They convert strings to ForwardRef automatically.
+
+        Examples::
+            typing.List['Hero'] == typing.List[ForwardRef('Hero')]
+        """
+        return tp
+
+else:
+
+    def convert_generics(tp: Type[Any]) -> Type[Any]:
+        """
+        Recursively searches for `str` type hints and replaces them with ForwardRef.
+
+        Examples::
+            convert_generics(list['Hero']) == list[ForwardRef('Hero')]
+            convert_generics(dict['Hero', 'Team']) == dict[ForwardRef('Hero'), ForwardRef('Team')]
+            convert_generics(typing.Dict['Hero', 'Team']) == typing.Dict[ForwardRef('Hero'), ForwardRef('Team')]
+            convert_generics(list[str | 'Hero'] | int) == list[str | ForwardRef('Hero')] | int
+        """
+        origin = get_origin(tp)
+        if not origin or not hasattr(tp, '__args__'):
+            return tp
+
+        args = get_args(tp)
+
+        # typing.Annotated needs special treatment
+        if origin is Annotated:
+            return Annotated[(convert_generics(args[0]), *args[1:])]  # type: ignore
+
+        # recursively replace `str` instances inside of `GenericAlias` with `ForwardRef(arg)`
+        converted = tuple(
+            ForwardRef(arg) if isinstance(arg, str) and isinstance(tp, TypingGenericAlias) else convert_generics(arg)
+            for arg in args
+        )
+
+        if converted == args:
+            return tp
+        elif isinstance(tp, TypingGenericAlias):
+            return TypingGenericAlias(origin, converted)
+        elif isinstance(tp, TypesUnionType):
+            # recreate types.UnionType (PEP604, Python >= 3.10)
+            return functools.reduce(operator.or_, converted)  # type: ignore
+        else:
+            try:
+                setattr(tp, '__args__', converted)
+            except AttributeError:
+                pass
+            return tp
+
+
+if sys.version_info < (3, 10):
+
+    def is_union(tp: Optional[Type[Any]]) -> bool:
+        return tp is Union
+
+    WithArgsTypes = (TypingGenericAlias,)
+
+else:
+    import types
+    import typing
+
+    def is_union(tp: Optional[Type[Any]]) -> bool:
+        return tp is Union or tp is types.UnionType  # noqa: E721
+
+    WithArgsTypes = (typing._GenericAlias, types.GenericAlias, types.UnionType)
+
+
+StrPath = Union[str, PathLike]
+
+
+if TYPE_CHECKING:
+    from pydantic.v1.fields import ModelField
+
+    TupleGenerator = Generator[Tuple[str, Any], None, None]
+    DictStrAny = Dict[str, Any]
+    DictAny = Dict[Any, Any]
+    SetStr = Set[str]
+    ListStr = List[str]
+    IntStr = Union[int, str]
+    AbstractSetIntStr = AbstractSet[IntStr]
+    DictIntStrAny = Dict[IntStr, Any]
+    MappingIntStrAny = Mapping[IntStr, Any]
+    CallableGenerator = Generator[AnyCallable, None, None]
+    ReprArgs = Sequence[Tuple[Optional[str], Any]]
+
+    MYPY = False
+    if MYPY:
+        AnyClassMethod = classmethod[Any]
+    else:
+        # classmethod[TargetType, CallableParamSpecType, CallableReturnType]
+        AnyClassMethod = classmethod[Any, Any, Any]
+
+__all__ = (
+    'AnyCallable',
+    'NoArgAnyCallable',
+    'NoneType',
+    'is_none_type',
+    'display_as_type',
+    'resolve_annotations',
+    'is_callable_type',
+    'is_literal_type',
+    'all_literal_values',
+    'is_namedtuple',
+    'is_typeddict',
+    'is_typeddict_special',
+    'is_new_type',
+    'new_type_supertype',
+    'is_classvar',
+    'is_finalvar',
+    'update_field_forward_refs',
+    'update_model_forward_refs',
+    'TupleGenerator',
+    'DictStrAny',
+    'DictAny',
+    'SetStr',
+    'ListStr',
+    'IntStr',
+    'AbstractSetIntStr',
+    'DictIntStrAny',
+    'CallableGenerator',
+    'ReprArgs',
+    'AnyClassMethod',
+    'CallableGenerator',
+    'WithArgsTypes',
+    'get_args',
+    'get_origin',
+    'get_sub_types',
+    'typing_base',
+    'get_all_type_hints',
+    'is_union',
+    'StrPath',
+    'MappingIntStrAny',
+)
+
+
+NoneType = None.__class__
+
+
+NONE_TYPES: Tuple[Any, Any, Any] = (None, NoneType, Literal[None])
+
+
+if sys.version_info < (3, 8):
+    # Even though this implementation is slower, we need it for python 3.7:
+    # In python 3.7 "Literal" is not a builtin type and uses a different
+    # mechanism.
+    # for this reason `Literal[None] is Literal[None]` evaluates to `False`,
+    # breaking the faster implementation used for the other python versions.
+
+    def is_none_type(type_: Any) -> bool:
+        return type_ in NONE_TYPES
+
+elif sys.version_info[:2] == (3, 8):
+
+    def is_none_type(type_: Any) -> bool:
+        for none_type in NONE_TYPES:
+            if type_ is none_type:
+                return True
+        # With python 3.8, specifically 3.8.10, Literal "is" check sare very flakey
+        # can change on very subtle changes like use of types in other modules,
+        # hopefully this check avoids that issue.
+        if is_literal_type(type_):  # pragma: no cover
+            return all_literal_values(type_) == (None,)
+        return False
+
+else:
+
+    def is_none_type(type_: Any) -> bool:
+        return type_ in NONE_TYPES
+
+
+def display_as_type(v: Type[Any]) -> str:
+    if not isinstance(v, typing_base) and not isinstance(v, WithArgsTypes) and not isinstance(v, type):
+        v = v.__class__
+
+    if is_union(get_origin(v)):
+        return f'Union[{", ".join(map(display_as_type, get_args(v)))}]'
+
+    if isinstance(v, WithArgsTypes):
+        # Generic alias are constructs like `list[int]`
+        return str(v).replace('typing.', '')
+
+    try:
+        return v.__name__
+    except AttributeError:
+        # happens with typing objects
+        return str(v).replace('typing.', '')
+
+
+def resolve_annotations(raw_annotations: Dict[str, Type[Any]], module_name: Optional[str]) -> Dict[str, Type[Any]]:
+    """
+    Partially taken from typing.get_type_hints.
+
+    Resolve string or ForwardRef annotations into type objects if possible.
+    """
+    base_globals: Optional[Dict[str, Any]] = None
+    if module_name:
+        try:
+            module = sys.modules[module_name]
+        except KeyError:
+            # happens occasionally, see https://github.com/pydantic/pydantic/issues/2363
+            pass
+        else:
+            base_globals = module.__dict__
+
+    annotations = {}
+    for name, value in raw_annotations.items():
+        if isinstance(value, str):
+            if (3, 10) > sys.version_info >= (3, 9, 8) or sys.version_info >= (3, 10, 1):
+                value = ForwardRef(value, is_argument=False, is_class=True)
+            else:
+                value = ForwardRef(value, is_argument=False)
+        try:
+            if sys.version_info >= (3, 13):
+                value = _eval_type(value, base_globals, None, type_params=())
+            else:
+                value = _eval_type(value, base_globals, None)
+        except NameError:
+            # this is ok, it can be fixed with update_forward_refs
+            pass
+        annotations[name] = value
+    return annotations
+
+
+def is_callable_type(type_: Type[Any]) -> bool:
+    return type_ is Callable or get_origin(type_) is Callable
+
+
+def is_literal_type(type_: Type[Any]) -> bool:
+    return Literal is not None and get_origin(type_) in LITERAL_TYPES
+
+
+def literal_values(type_: Type[Any]) -> Tuple[Any, ...]:
+    return get_args(type_)
+
+
+def all_literal_values(type_: Type[Any]) -> Tuple[Any, ...]:
+    """
+    This method is used to retrieve all Literal values as
+    Literal can be used recursively (see https://www.python.org/dev/peps/pep-0586)
+    e.g. `Literal[Literal[Literal[1, 2, 3], "foo"], 5, None]`
+    """
+    if not is_literal_type(type_):
+        return (type_,)
+
+    values = literal_values(type_)
+    return tuple(x for value in values for x in all_literal_values(value))
+
+
+def is_namedtuple(type_: Type[Any]) -> bool:
+    """
+    Check if a given class is a named tuple.
+    It can be either a `typing.NamedTuple` or `collections.namedtuple`
+    """
+    from pydantic.v1.utils import lenient_issubclass
+
+    return lenient_issubclass(type_, tuple) and hasattr(type_, '_fields')
+
+
+def is_typeddict(type_: Type[Any]) -> bool:
+    """
+    Check if a given class is a typed dict (from `typing` or `typing_extensions`)
+    In 3.10, there will be a public method (https://docs.python.org/3.10/library/typing.html#typing.is_typeddict)
+    """
+    from pydantic.v1.utils import lenient_issubclass
+
+    return lenient_issubclass(type_, dict) and hasattr(type_, '__total__')
+
+
+def _check_typeddict_special(type_: Any) -> bool:
+    return type_ is TypedDictRequired or type_ is TypedDictNotRequired
+
+
+def is_typeddict_special(type_: Any) -> bool:
+    """
+    Check if type is a TypedDict special form (Required or NotRequired).
+    """
+    return _check_typeddict_special(type_) or _check_typeddict_special(get_origin(type_))
+
+
+test_type = NewType('test_type', str)
+
+
+def is_new_type(type_: Type[Any]) -> bool:
+    """
+    Check whether type_ was created using typing.NewType
+    """
+    return isinstance(type_, test_type.__class__) and hasattr(type_, '__supertype__')  # type: ignore
+
+
+def new_type_supertype(type_: Type[Any]) -> Type[Any]:
+    while hasattr(type_, '__supertype__'):
+        type_ = type_.__supertype__
+    return type_
+
+
+def _check_classvar(v: Optional[Type[Any]]) -> bool:
+    if v is None:
+        return False
+
+    return v.__class__ == ClassVar.__class__ and getattr(v, '_name', None) == 'ClassVar'
+
+
+def _check_finalvar(v: Optional[Type[Any]]) -> bool:
+    """
+    Check if a given type is a `typing.Final` type.
+    """
+    if v is None:
+        return False
+
+    return v.__class__ == Final.__class__ and (sys.version_info < (3, 8) or getattr(v, '_name', None) == 'Final')
+
+
+def is_classvar(ann_type: Type[Any]) -> bool:
+    if _check_classvar(ann_type) or _check_classvar(get_origin(ann_type)):
+        return True
+
+    # this is an ugly workaround for class vars that contain forward references and are therefore themselves
+    # forward references, see #3679
+    if ann_type.__class__ == ForwardRef and ann_type.__forward_arg__.startswith('ClassVar['):
+        return True
+
+    return False
+
+
+def is_finalvar(ann_type: Type[Any]) -> bool:
+    return _check_finalvar(ann_type) or _check_finalvar(get_origin(ann_type))
+
+
+def update_field_forward_refs(field: 'ModelField', globalns: Any, localns: Any) -> None:
+    """
+    Try to update ForwardRefs on fields based on this ModelField, globalns and localns.
+    """
+    prepare = False
+    if field.type_.__class__ == ForwardRef:
+        prepare = True
+        field.type_ = evaluate_forwardref(field.type_, globalns, localns or None)
+    if field.outer_type_.__class__ == ForwardRef:
+        prepare = True
+        field.outer_type_ = evaluate_forwardref(field.outer_type_, globalns, localns or None)
+    if prepare:
+        field.prepare()
+
+    if field.sub_fields:
+        for sub_f in field.sub_fields:
+            update_field_forward_refs(sub_f, globalns=globalns, localns=localns)
+
+    if field.discriminator_key is not None:
+        field.prepare_discriminated_union_sub_fields()
+
+
+def update_model_forward_refs(
+    model: Type[Any],
+    fields: Iterable['ModelField'],
+    json_encoders: Dict[Union[Type[Any], str, ForwardRef], AnyCallable],
+    localns: 'DictStrAny',
+    exc_to_suppress: Tuple[Type[BaseException], ...] = (),
+) -> None:
+    """
+    Try to update model fields ForwardRefs based on model and localns.
+    """
+    if model.__module__ in sys.modules:
+        globalns = sys.modules[model.__module__].__dict__.copy()
+    else:
+        globalns = {}
+
+    globalns.setdefault(model.__name__, model)
+
+    for f in fields:
+        try:
+            update_field_forward_refs(f, globalns=globalns, localns=localns)
+        except exc_to_suppress:
+            pass
+
+    for key in set(json_encoders.keys()):
+        if isinstance(key, str):
+            fr: ForwardRef = ForwardRef(key)
+        elif isinstance(key, ForwardRef):
+            fr = key
+        else:
+            continue
+
+        try:
+            new_key = evaluate_forwardref(fr, globalns, localns or None)
+        except exc_to_suppress:  # pragma: no cover
+            continue
+
+        json_encoders[new_key] = json_encoders.pop(key)
+
+
+def get_class(type_: Type[Any]) -> Union[None, bool, Type[Any]]:
+    """
+    Tries to get the class of a Type[T] annotation. Returns True if Type is used
+    without brackets. Otherwise returns None.
+    """
+    if type_ is type:
+        return True
+
+    if get_origin(type_) is None:
+        return None
+
+    args = get_args(type_)
+    if not args or not isinstance(args[0], type):
+        return True
+    else:
+        return args[0]
+
+
+def get_sub_types(tp: Any) -> List[Any]:
+    """
+    Return all the types that are allowed by type `tp`
+    `tp` can be a `Union` of allowed types or an `Annotated` type
+    """
+    origin = get_origin(tp)
+    if origin is Annotated:
+        return get_sub_types(get_args(tp)[0])
+    elif is_union(origin):
+        return [x for t in get_args(tp) for x in get_sub_types(t)]
+    else:
+        return [tp]

venv/Lib/site-packages/pydantic/v1/utils.py

@@ -0,0 +1,807 @@
+import keyword
+import warnings
+import weakref
+from collections import OrderedDict, defaultdict, deque
+from copy import deepcopy
+from itertools import islice, zip_longest
+from types import BuiltinFunctionType, CodeType, FunctionType, GeneratorType, LambdaType, ModuleType
+from typing import (
+    TYPE_CHECKING,
+    AbstractSet,
+    Any,
+    Callable,
+    Collection,
+    Dict,
+    Generator,
+    Iterable,
+    Iterator,
+    List,
+    Mapping,
+    NoReturn,
+    Optional,
+    Set,
+    Tuple,
+    Type,
+    TypeVar,
+    Union,
+)
+
+from typing_extensions import Annotated
+
+from pydantic.v1.errors import ConfigError
+from pydantic.v1.typing import (
+    NoneType,
+    WithArgsTypes,
+    all_literal_values,
+    display_as_type,
+    get_args,
+    get_origin,
+    is_literal_type,
+    is_union,
+)
+from pydantic.v1.version import version_info
+
+if TYPE_CHECKING:
+    from inspect import Signature
+    from pathlib import Path
+
+    from pydantic.v1.config import BaseConfig
+    from pydantic.v1.dataclasses import Dataclass
+    from pydantic.v1.fields import ModelField
+    from pydantic.v1.main import BaseModel
+    from pydantic.v1.typing import AbstractSetIntStr, DictIntStrAny, IntStr, MappingIntStrAny, ReprArgs
+
+    RichReprResult = Iterable[Union[Any, Tuple[Any], Tuple[str, Any], Tuple[str, Any, Any]]]
+
+__all__ = (
+    'import_string',
+    'sequence_like',
+    'validate_field_name',
+    'lenient_isinstance',
+    'lenient_issubclass',
+    'in_ipython',
+    'is_valid_identifier',
+    'deep_update',
+    'update_not_none',
+    'almost_equal_floats',
+    'get_model',
+    'to_camel',
+    'to_lower_camel',
+    'is_valid_field',
+    'smart_deepcopy',
+    'PyObjectStr',
+    'Representation',
+    'GetterDict',
+    'ValueItems',
+    'version_info',  # required here to match behaviour in v1.3
+    'ClassAttribute',
+    'path_type',
+    'ROOT_KEY',
+    'get_unique_discriminator_alias',
+    'get_discriminator_alias_and_values',
+    'DUNDER_ATTRIBUTES',
+)
+
+ROOT_KEY = '__root__'
+# these are types that are returned unchanged by deepcopy
+IMMUTABLE_NON_COLLECTIONS_TYPES: Set[Type[Any]] = {
+    int,
+    float,
+    complex,
+    str,
+    bool,
+    bytes,
+    type,
+    NoneType,
+    FunctionType,
+    BuiltinFunctionType,
+    LambdaType,
+    weakref.ref,
+    CodeType,
+    # note: including ModuleType will differ from behaviour of deepcopy by not producing error.
+    # It might be not a good idea in general, but considering that this function used only internally
+    # against default values of fields, this will allow to actually have a field with module as default value
+    ModuleType,
+    NotImplemented.__class__,
+    Ellipsis.__class__,
+}
+
+# these are types that if empty, might be copied with simple copy() instead of deepcopy()
+BUILTIN_COLLECTIONS: Set[Type[Any]] = {
+    list,
+    set,
+    tuple,
+    frozenset,
+    dict,
+    OrderedDict,
+    defaultdict,
+    deque,
+}
+
+
+def import_string(dotted_path: str) -> Any:
+    """
+    Stolen approximately from django. Import a dotted module path and return the attribute/class designated by the
+    last name in the path. Raise ImportError if the import fails.
+    """
+    from importlib import import_module
+
+    try:
+        module_path, class_name = dotted_path.strip(' ').rsplit('.', 1)
+    except ValueError as e:
+        raise ImportError(f'"{dotted_path}" doesn\'t look like a module path') from e
+
+    module = import_module(module_path)
+    try:
+        return getattr(module, class_name)
+    except AttributeError as e:
+        raise ImportError(f'Module "{module_path}" does not define a "{class_name}" attribute') from e
+
+
+def truncate(v: Union[str], *, max_len: int = 80) -> str:
+    """
+    Truncate a value and add a unicode ellipsis (three dots) to the end if it was too long
+    """
+    warnings.warn('`truncate` is no-longer used by pydantic and is deprecated', DeprecationWarning)
+    if isinstance(v, str) and len(v) > (max_len - 2):
+        # -3 so quote + string + … + quote has correct length
+        return (v[: (max_len - 3)] + '…').__repr__()
+    try:
+        v = v.__repr__()
+    except TypeError:
+        v = v.__class__.__repr__(v)  # in case v is a type
+    if len(v) > max_len:
+        v = v[: max_len - 1] + '…'
+    return v
+
+
+def sequence_like(v: Any) -> bool:
+    return isinstance(v, (list, tuple, set, frozenset, GeneratorType, deque))
+
+
+def validate_field_name(bases: Iterable[Type[Any]], field_name: str) -> None:
+    """
+    Ensure that the field's name does not shadow an existing attribute of the model.
+    """
+    for base in bases:
+        if getattr(base, field_name, None):
+            raise NameError(
+                f'Field name "{field_name}" shadows a BaseModel attribute; '
+                f'use a different field name with "alias=\'{field_name}\'".'
+            )
+
+
+def lenient_isinstance(o: Any, class_or_tuple: Union[Type[Any], Tuple[Type[Any], ...], None]) -> bool:
+    try:
+        return isinstance(o, class_or_tuple)  # type: ignore[arg-type]
+    except TypeError:
+        return False
+
+
+def lenient_issubclass(cls: Any, class_or_tuple: Union[Type[Any], Tuple[Type[Any], ...], None]) -> bool:
+    try:
+        return isinstance(cls, type) and issubclass(cls, class_or_tuple)  # type: ignore[arg-type]
+    except TypeError:
+        if isinstance(cls, WithArgsTypes):
+            return False
+        raise  # pragma: no cover
+
+
+def in_ipython() -> bool:
+    """
+    Check whether we're in an ipython environment, including jupyter notebooks.
+    """
+    try:
+        eval('__IPYTHON__')
+    except NameError:
+        return False
+    else:  # pragma: no cover
+        return True
+
+
+def is_valid_identifier(identifier: str) -> bool:
+    """
+    Checks that a string is a valid identifier and not a Python keyword.
+    :param identifier: The identifier to test.
+    :return: True if the identifier is valid.
+    """
+    return identifier.isidentifier() and not keyword.iskeyword(identifier)
+
+
+KeyType = TypeVar('KeyType')
+
+
+def deep_update(mapping: Dict[KeyType, Any], *updating_mappings: Dict[KeyType, Any]) -> Dict[KeyType, Any]:
+    updated_mapping = mapping.copy()
+    for updating_mapping in updating_mappings:
+        for k, v in updating_mapping.items():
+            if k in updated_mapping and isinstance(updated_mapping[k], dict) and isinstance(v, dict):
+                updated_mapping[k] = deep_update(updated_mapping[k], v)
+            else:
+                updated_mapping[k] = v
+    return updated_mapping
+
+
+def update_not_none(mapping: Dict[Any, Any], **update: Any) -> None:
+    mapping.update({k: v for k, v in update.items() if v is not None})
+
+
+def almost_equal_floats(value_1: float, value_2: float, *, delta: float = 1e-8) -> bool:
+    """
+    Return True if two floats are almost equal
+    """
+    return abs(value_1 - value_2) <= delta
+
+
+def generate_model_signature(
+    init: Callable[..., None], fields: Dict[str, 'ModelField'], config: Type['BaseConfig']
+) -> 'Signature':
+    """
+    Generate signature for model based on its fields
+    """
+    from inspect import Parameter, Signature, signature
+
+    from pydantic.v1.config import Extra
+
+    present_params = signature(init).parameters.values()
+    merged_params: Dict[str, Parameter] = {}
+    var_kw = None
+    use_var_kw = False
+
+    for param in islice(present_params, 1, None):  # skip self arg
+        if param.kind is param.VAR_KEYWORD:
+            var_kw = param
+            continue
+        merged_params[param.name] = param
+
+    if var_kw:  # if custom init has no var_kw, fields which are not declared in it cannot be passed through
+        allow_names = config.allow_population_by_field_name
+        for field_name, field in fields.items():
+            param_name = field.alias
+            if field_name in merged_params or param_name in merged_params:
+                continue
+            elif not is_valid_identifier(param_name):
+                if allow_names and is_valid_identifier(field_name):
+                    param_name = field_name
+                else:
+                    use_var_kw = True
+                    continue
+
+            # TODO: replace annotation with actual expected types once #1055 solved
+            kwargs = {'default': field.default} if not field.required else {}
+            merged_params[param_name] = Parameter(
+                param_name, Parameter.KEYWORD_ONLY, annotation=field.annotation, **kwargs
+            )
+
+    if config.extra is Extra.allow:
+        use_var_kw = True
+
+    if var_kw and use_var_kw:
+        # Make sure the parameter for extra kwargs
+        # does not have the same name as a field
+        default_model_signature = [
+            ('__pydantic_self__', Parameter.POSITIONAL_OR_KEYWORD),
+            ('data', Parameter.VAR_KEYWORD),
+        ]
+        if [(p.name, p.kind) for p in present_params] == default_model_signature:
+            # if this is the standard model signature, use extra_data as the extra args name
+            var_kw_name = 'extra_data'
+        else:
+            # else start from var_kw
+            var_kw_name = var_kw.name
+
+        # generate a name that's definitely unique
+        while var_kw_name in fields:
+            var_kw_name += '_'
+        merged_params[var_kw_name] = var_kw.replace(name=var_kw_name)
+
+    return Signature(parameters=list(merged_params.values()), return_annotation=None)
+
+
+def get_model(obj: Union[Type['BaseModel'], Type['Dataclass']]) -> Type['BaseModel']:
+    from pydantic.v1.main import BaseModel
+
+    try:
+        model_cls = obj.__pydantic_model__  # type: ignore
+    except AttributeError:
+        model_cls = obj
+
+    if not issubclass(model_cls, BaseModel):
+        raise TypeError('Unsupported type, must be either BaseModel or dataclass')
+    return model_cls
+
+
+def to_camel(string: str) -> str:
+    return ''.join(word.capitalize() for word in string.split('_'))
+
+
+def to_lower_camel(string: str) -> str:
+    if len(string) >= 1:
+        pascal_string = to_camel(string)
+        return pascal_string[0].lower() + pascal_string[1:]
+    return string.lower()
+
+
+T = TypeVar('T')
+
+
+def unique_list(
+    input_list: Union[List[T], Tuple[T, ...]],
+    *,
+    name_factory: Callable[[T], str] = str,
+) -> List[T]:
+    """
+    Make a list unique while maintaining order.
+    We update the list if another one with the same name is set
+    (e.g. root validator overridden in subclass)
+    """
+    result: List[T] = []
+    result_names: List[str] = []
+    for v in input_list:
+        v_name = name_factory(v)
+        if v_name not in result_names:
+            result_names.append(v_name)
+            result.append(v)
+        else:
+            result[result_names.index(v_name)] = v
+
+    return result
+
+
+class PyObjectStr(str):
+    """
+    String class where repr doesn't include quotes. Useful with Representation when you want to return a string
+    representation of something that valid (or pseudo-valid) python.
+    """
+
+    def __repr__(self) -> str:
+        return str(self)
+
+
+class Representation:
+    """
+    Mixin to provide __str__, __repr__, and __pretty__ methods. See #884 for more details.
+
+    __pretty__ is used by [devtools](https://python-devtools.helpmanual.io/) to provide human readable representations
+    of objects.
+    """
+
+    __slots__: Tuple[str, ...] = tuple()
+
+    def __repr_args__(self) -> 'ReprArgs':
+        """
+        Returns the attributes to show in __str__, __repr__, and __pretty__ this is generally overridden.
+
+        Can either return:
+        * name - value pairs, e.g.: `[('foo_name', 'foo'), ('bar_name', ['b', 'a', 'r'])]`
+        * or, just values, e.g.: `[(None, 'foo'), (None, ['b', 'a', 'r'])]`
+        """
+        attrs = ((s, getattr(self, s)) for s in self.__slots__)
+        return [(a, v) for a, v in attrs if v is not None]
+
+    def __repr_name__(self) -> str:
+        """
+        Name of the instance's class, used in __repr__.
+        """
+        return self.__class__.__name__
+
+    def __repr_str__(self, join_str: str) -> str:
+        return join_str.join(repr(v) if a is None else f'{a}={v!r}' for a, v in self.__repr_args__())
+
+    def __pretty__(self, fmt: Callable[[Any], Any], **kwargs: Any) -> Generator[Any, None, None]:
+        """
+        Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
+        """
+        yield self.__repr_name__() + '('
+        yield 1
+        for name, value in self.__repr_args__():
+            if name is not None:
+                yield name + '='
+            yield fmt(value)
+            yield ','
+            yield 0
+        yield -1
+        yield ')'
+
+    def __str__(self) -> str:
+        return self.__repr_str__(' ')
+
+    def __repr__(self) -> str:
+        return f'{self.__repr_name__()}({self.__repr_str__(", ")})'
+
+    def __rich_repr__(self) -> 'RichReprResult':
+        """Get fields for Rich library"""
+        for name, field_repr in self.__repr_args__():
+            if name is None:
+                yield field_repr
+            else:
+                yield name, field_repr
+
+
+class GetterDict(Representation):
+    """
+    Hack to make object's smell just enough like dicts for validate_model.
+
+    We can't inherit from Mapping[str, Any] because it upsets cython so we have to implement all methods ourselves.
+    """
+
+    __slots__ = ('_obj',)
+
+    def __init__(self, obj: Any):
+        self._obj = obj
+
+    def __getitem__(self, key: str) -> Any:
+        try:
+            return getattr(self._obj, key)
+        except AttributeError as e:
+            raise KeyError(key) from e
+
+    def get(self, key: Any, default: Any = None) -> Any:
+        return getattr(self._obj, key, default)
+
+    def extra_keys(self) -> Set[Any]:
+        """
+        We don't want to get any other attributes of obj if the model didn't explicitly ask for them
+        """
+        return set()
+
+    def keys(self) -> List[Any]:
+        """
+        Keys of the pseudo dictionary, uses a list not set so order information can be maintained like python
+        dictionaries.
+        """
+        return list(self)
+
+    def values(self) -> List[Any]:
+        return [self[k] for k in self]
+
+    def items(self) -> Iterator[Tuple[str, Any]]:
+        for k in self:
+            yield k, self.get(k)
+
+    def __iter__(self) -> Iterator[str]:
+        for name in dir(self._obj):
+            if not name.startswith('_'):
+                yield name
+
+    def __len__(self) -> int:
+        return sum(1 for _ in self)
+
+    def __contains__(self, item: Any) -> bool:
+        return item in self.keys()
+
+    def __eq__(self, other: Any) -> bool:
+        return dict(self) == dict(other.items())
+
+    def __repr_args__(self) -> 'ReprArgs':
+        return [(None, dict(self))]
+
+    def __repr_name__(self) -> str:
+        return f'GetterDict[{display_as_type(self._obj)}]'
+
+
+class ValueItems(Representation):
+    """
+    Class for more convenient calculation of excluded or included fields on values.
+    """
+
+    __slots__ = ('_items', '_type')
+
+    def __init__(self, value: Any, items: Union['AbstractSetIntStr', 'MappingIntStrAny']) -> None:
+        items = self._coerce_items(items)
+
+        if isinstance(value, (list, tuple)):
+            items = self._normalize_indexes(items, len(value))
+
+        self._items: 'MappingIntStrAny' = items
+
+    def is_excluded(self, item: Any) -> bool:
+        """
+        Check if item is fully excluded.
+
+        :param item: key or index of a value
+        """
+        return self.is_true(self._items.get(item))
+
+    def is_included(self, item: Any) -> bool:
+        """
+        Check if value is contained in self._items
+
+        :param item: key or index of value
+        """
+        return item in self._items
+
+    def for_element(self, e: 'IntStr') -> Optional[Union['AbstractSetIntStr', 'MappingIntStrAny']]:
+        """
+        :param e: key or index of element on value
+        :return: raw values for element if self._items is dict and contain needed element
+        """
+
+        item = self._items.get(e)
+        return item if not self.is_true(item) else None
+
+    def _normalize_indexes(self, items: 'MappingIntStrAny', v_length: int) -> 'DictIntStrAny':
+        """
+        :param items: dict or set of indexes which will be normalized
+        :param v_length: length of sequence indexes of which will be
+
+        >>> self._normalize_indexes({0: True, -2: True, -1: True}, 4)
+        {0: True, 2: True, 3: True}
+        >>> self._normalize_indexes({'__all__': True}, 4)
+        {0: True, 1: True, 2: True, 3: True}
+        """
+
+        normalized_items: 'DictIntStrAny' = {}
+        all_items = None
+        for i, v in items.items():
+            if not (isinstance(v, Mapping) or isinstance(v, AbstractSet) or self.is_true(v)):
+                raise TypeError(f'Unexpected type of exclude value for index "{i}" {v.__class__}')
+            if i == '__all__':
+                all_items = self._coerce_value(v)
+                continue
+            if not isinstance(i, int):
+                raise TypeError(
+                    'Excluding fields from a sequence of sub-models or dicts must be performed index-wise: '
+                    'expected integer keys or keyword "__all__"'
+                )
+            normalized_i = v_length + i if i < 0 else i
+            normalized_items[normalized_i] = self.merge(v, normalized_items.get(normalized_i))
+
+        if not all_items:
+            return normalized_items
+        if self.is_true(all_items):
+            for i in range(v_length):
+                normalized_items.setdefault(i, ...)
+            return normalized_items
+        for i in range(v_length):
+            normalized_item = normalized_items.setdefault(i, {})
+            if not self.is_true(normalized_item):
+                normalized_items[i] = self.merge(all_items, normalized_item)
+        return normalized_items
+
+    @classmethod
+    def merge(cls, base: Any, override: Any, intersect: bool = False) -> Any:
+        """
+        Merge a ``base`` item with an ``override`` item.
+
+        Both ``base`` and ``override`` are converted to dictionaries if possible.
+        Sets are converted to dictionaries with the sets entries as keys and
+        Ellipsis as values.
+
+        Each key-value pair existing in ``base`` is merged with ``override``,
+        while the rest of the key-value pairs are updated recursively with this function.
+
+        Merging takes place based on the "union" of keys if ``intersect`` is
+        set to ``False`` (default) and on the intersection of keys if
+        ``intersect`` is set to ``True``.
+        """
+        override = cls._coerce_value(override)
+        base = cls._coerce_value(base)
+        if override is None:
+            return base
+        if cls.is_true(base) or base is None:
+            return override
+        if cls.is_true(override):
+            return base if intersect else override
+
+        # intersection or union of keys while preserving ordering:
+        if intersect:
+            merge_keys = [k for k in base if k in override] + [k for k in override if k in base]
+        else:
+            merge_keys = list(base) + [k for k in override if k not in base]
+
+        merged: 'DictIntStrAny' = {}
+        for k in merge_keys:
+            merged_item = cls.merge(base.get(k), override.get(k), intersect=intersect)
+            if merged_item is not None:
+                merged[k] = merged_item
+
+        return merged
+
+    @staticmethod
+    def _coerce_items(items: Union['AbstractSetIntStr', 'MappingIntStrAny']) -> 'MappingIntStrAny':
+        if isinstance(items, Mapping):
+            pass
+        elif isinstance(items, AbstractSet):
+            items = dict.fromkeys(items, ...)
+        else:
+            class_name = getattr(items, '__class__', '???')
+            assert_never(
+                items,
+                f'Unexpected type of exclude value {class_name}',
+            )
+        return items
+
+    @classmethod
+    def _coerce_value(cls, value: Any) -> Any:
+        if value is None or cls.is_true(value):
+            return value
+        return cls._coerce_items(value)
+
+    @staticmethod
+    def is_true(v: Any) -> bool:
+        return v is True or v is ...
+
+    def __repr_args__(self) -> 'ReprArgs':
+        return [(None, self._items)]
+
+
+class ClassAttribute:
+    """
+    Hide class attribute from its instances
+    """
+
+    __slots__ = (
+        'name',
+        'value',
+    )
+
+    def __init__(self, name: str, value: Any) -> None:
+        self.name = name
+        self.value = value
+
+    def __get__(self, instance: Any, owner: Type[Any]) -> None:
+        if instance is None:
+            return self.value
+        raise AttributeError(f'{self.name!r} attribute of {owner.__name__!r} is class-only')
+
+
+path_types = {
+    'is_dir': 'directory',
+    'is_file': 'file',
+    'is_mount': 'mount point',
+    'is_symlink': 'symlink',
+    'is_block_device': 'block device',
+    'is_char_device': 'char device',
+    'is_fifo': 'FIFO',
+    'is_socket': 'socket',
+}
+
+
+def path_type(p: 'Path') -> str:
+    """
+    Find out what sort of thing a path is.
+    """
+    assert p.exists(), 'path does not exist'
+    for method, name in path_types.items():
+        if getattr(p, method)():
+            return name
+
+    return 'unknown'
+
+
+Obj = TypeVar('Obj')
+
+
+def smart_deepcopy(obj: Obj) -> Obj:
+    """
+    Return type as is for immutable built-in types
+    Use obj.copy() for built-in empty collections
+    Use copy.deepcopy() for non-empty collections and unknown objects
+    """
+
+    obj_type = obj.__class__
+    if obj_type in IMMUTABLE_NON_COLLECTIONS_TYPES:
+        return obj  # fastest case: obj is immutable and not collection therefore will not be copied anyway
+    try:
+        if not obj and obj_type in BUILTIN_COLLECTIONS:
+            # faster way for empty collections, no need to copy its members
+            return obj if obj_type is tuple else obj.copy()  # type: ignore  # tuple doesn't have copy method
+    except (TypeError, ValueError, RuntimeError):
+        # do we really dare to catch ALL errors? Seems a bit risky
+        pass
+
+    return deepcopy(obj)  # slowest way when we actually might need a deepcopy
+
+
+def is_valid_field(name: str) -> bool:
+    if not name.startswith('_'):
+        return True
+    return ROOT_KEY == name
+
+
+DUNDER_ATTRIBUTES = {
+    '__annotations__',
+    '__classcell__',
+    '__doc__',
+    '__module__',
+    '__orig_bases__',
+    '__orig_class__',
+    '__qualname__',
+    '__firstlineno__',
+    '__static_attributes__',
+    '__classdictcell__',
+}
+
+
+def is_valid_private_name(name: str) -> bool:
+    return not is_valid_field(name) and name not in DUNDER_ATTRIBUTES
+
+
+_EMPTY = object()
+
+
+def all_identical(left: Iterable[Any], right: Iterable[Any]) -> bool:
+    """
+    Check that the items of `left` are the same objects as those in `right`.
+
+    >>> a, b = object(), object()
+    >>> all_identical([a, b, a], [a, b, a])
+    True
+    >>> all_identical([a, b, [a]], [a, b, [a]])  # new list object, while "equal" is not "identical"
+    False
+    """
+    for left_item, right_item in zip_longest(left, right, fillvalue=_EMPTY):
+        if left_item is not right_item:
+            return False
+    return True
+
+
+def assert_never(obj: NoReturn, msg: str) -> NoReturn:
+    """
+    Helper to make sure that we have covered all possible types.
+
+    This is mostly useful for ``mypy``, docs:
+    https://mypy.readthedocs.io/en/latest/literal_types.html#exhaustive-checks
+    """
+    raise TypeError(msg)
+
+
+def get_unique_discriminator_alias(all_aliases: Collection[str], discriminator_key: str) -> str:
+    """Validate that all aliases are the same and if that's the case return the alias"""
+    unique_aliases = set(all_aliases)
+    if len(unique_aliases) > 1:
+        raise ConfigError(
+            f'Aliases for discriminator {discriminator_key!r} must be the same (got {", ".join(sorted(all_aliases))})'
+        )
+    return unique_aliases.pop()
+
+
+def get_discriminator_alias_and_values(tp: Any, discriminator_key: str) -> Tuple[str, Tuple[str, ...]]:
+    """
+    Get alias and all valid values in the `Literal` type of the discriminator field
+    `tp` can be a `BaseModel` class or directly an `Annotated` `Union` of many.
+    """
+    is_root_model = getattr(tp, '__custom_root_type__', False)
+
+    if get_origin(tp) is Annotated:
+        tp = get_args(tp)[0]
+
+    if hasattr(tp, '__pydantic_model__'):
+        tp = tp.__pydantic_model__
+
+    if is_union(get_origin(tp)):
+        alias, all_values = _get_union_alias_and_all_values(tp, discriminator_key)
+        return alias, tuple(v for values in all_values for v in values)
+    elif is_root_model:
+        union_type = tp.__fields__[ROOT_KEY].type_
+        alias, all_values = _get_union_alias_and_all_values(union_type, discriminator_key)
+
+        if len(set(all_values)) > 1:
+            raise ConfigError(
+                f'Field {discriminator_key!r} is not the same for all submodels of {display_as_type(tp)!r}'
+            )
+
+        return alias, all_values[0]
+
+    else:
+        try:
+            t_discriminator_type = tp.__fields__[discriminator_key].type_
+        except AttributeError as e:
+            raise TypeError(f'Type {tp.__name__!r} is not a valid `BaseModel` or `dataclass`') from e
+        except KeyError as e:
+            raise ConfigError(f'Model {tp.__name__!r} needs a discriminator field for key {discriminator_key!r}') from e
+
+        if not is_literal_type(t_discriminator_type):
+            raise ConfigError(f'Field {discriminator_key!r} of model {tp.__name__!r} needs to be a `Literal`')
+
+        return tp.__fields__[discriminator_key].alias, all_literal_values(t_discriminator_type)
+
+
+def _get_union_alias_and_all_values(
+    union_type: Type[Any], discriminator_key: str
+) -> Tuple[str, Tuple[Tuple[str, ...], ...]]:
+    zipped_aliases_values = [get_discriminator_alias_and_values(t, discriminator_key) for t in get_args(union_type)]
+    # unzip: [('alias_a',('v1', 'v2)), ('alias_b', ('v3',))] => [('alias_a', 'alias_b'), (('v1', 'v2'), ('v3',))]
+    all_aliases, all_values = zip(*zipped_aliases_values)
+    return get_unique_discriminator_alias(all_aliases, discriminator_key), all_values