*
 * <p>Each mapping item consists of one or more input character sequences that are mapped to a single output
 * character sequence. The mapping supports both original values and new values for update operations.</p>
 */
public class CharMappingItem extends DictionaryItem {
    /**
     * Array of input character sequences that will be mapped to the output sequence.
     * These represent the original/current input values for this mapping rule.

    return new_field_info


def serialize_sequence_value(*, field: ModelField, value: Any) -> Sequence[Any]:
    origin_type = get_origin(field.field_info.annotation) or field.field_info.annotation
    if origin_type is Union or origin_type is UnionType:  # Handle optional sequences
        union_args = get_args(field.field_info.annotation)
        for union_arg in union_args:

        self,
        errors: Sequence[Any],
        *,
        body: Any = None,
        endpoint_ctx: Optional[EndpointContext] = None,
    ) -> None:
        super().__init__(errors, endpoint_ctx=endpoint_ctx)
        self.body = body


class WebSocketRequestValidationError(ValidationException):
    def __init__(
        self,
        errors: Sequence[Any],
        *,

import java.io.IOException;
import java.util.ArrayList;
import java.util.LinkedHashSet;
import java.util.List;
import java.util.Set;

/**
 * A chain of {@link ReadingConverter} implementations that applies each converter in sequence to generate possible reading variations of a given text.
 * It maintains a list of ReadingConverter instances and iterates through them, applying each converter to the input text and accumulating the results.

      throw AssertionError("full event sequence: $fullEventSequence", e)
    }
  }

  inline fun <reified T : CallEvent> removeUpToEvent(): T = removeUpToEvent(T::class.java)

  inline fun <reified T : CallEvent> findEvent(): T = eventSequence.first { it is T } as T

  /**
   * Remove and return the next event from the recorded sequence.
   *

  public void testIndexOf_genericPredicate() {
    List<CharSequence> sequences = new ArrayList<>();
    sequences.add("bob");
    sequences.add(new StringBuilder("charlie"));
    sequences.add(new StringBuilder("henry"));
    sequences.add(new StringBuilder("apple"));
    sequences.add("lemon");

    assertEquals(3, Iterables.indexOf(sequences, STARTSWITH_A));
  }

  public void testIndexOf_genericPredicate2() {

import sys
import types
import typing
import warnings
from collections import deque
from collections.abc import Mapping, Sequence
from dataclasses import is_dataclass
from typing import (
    Annotated,
    Any,
    Union,
)

from fastapi.types import UnionType
from pydantic import BaseModel
from pydantic.version import VERSION as PYDANTIC_VERSION
from starlette.datastructures import UploadFile

      if (Character.isISOControl(codePoint) && !Character.isWhitespace(codePoint)) {
        return false
      }
    }
    return true
  } catch (_: EOFException) {
    return false // Truncated UTF-8 sequence.
  }

def get_openapi(
    *,
    title: str,
    version: str,
    openapi_version: str = "3.1.0",
    summary: Optional[str] = None,
    description: Optional[str] = None,
    routes: Sequence[BaseRoute],
    webhooks: Optional[Sequence[BaseRoute]] = None,
    tags: Optional[list[dict[str, Any]]] = None,
    servers: Optional[list[dict[str, Union[str, Any]]]] = None,
    terms_of_service: Optional[str] = None,

def test_raises_pydantic_v1_model_in_sequence() -> None:
    class ModelV1A(BaseModel):
        name: str

    app = FastAPI()

    with pytest.raises(PydanticV1NotSupportedError):

        @app.post("/sequence")
        def endpoint(data: list[ModelV1A]):  # pragma: no cover