two version of R2R are here HEAD master

1 files changed, 804 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/pydantic/v1/utils.py b/.venv/lib/python3.12/site-packages/pydantic/v1/utils.py
new file mode 100644
index 00000000..0bd238ee
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/pydantic/v1/utils.py
@@ -0,0 +1,804 @@
+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: List[Type['BaseModel']], 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__',
+}
+
+
+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