return operation_id


def deep_dict_update(main_dict: dict[Any, Any], update_dict: dict[Any, Any]) -> None:
    for key, value in update_dict.items():
        if (
            key in main_dict
            and isinstance(main_dict[key], dict)
            and isinstance(value, dict)
        ):
            deep_dict_update(main_dict[key], value)
        elif (

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.stemmeroverride;

import java.util.Date;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.dict.DictionaryCreator;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;

import jakarta.annotation.PostConstruct;

/**

    response = client.put(
        "/items/5",
        json={"description": "A very nice Item"},
    )
    assert response.status_code == 422, response.text
    assert response.json() == {
        "detail": [
            {
                "loc": ["body", "name"],
                "input": {"description": "A very nice Item"},
                "msg": "Field required",
                "type": "missing",
            },

    return values


async def request_body_to_args(
    body_fields: list[ModelField],
    received_body: dict[str, Any] | FormData | bytes | None,
    embed_body_fields: bool,
) -> tuple[dict[str, Any], list[dict[str, Any]]]:
    values: dict[str, Any] = {}
    errors: list[dict[str, Any]] = []
    assert body_fields, "request_body_to_args() should be called with fields"

Si añadiste la anotación del tipo de retorno, las herramientas y editores se quejarían con un error (correcto) diciéndote que tu función está devolviendo un tipo (por ejemplo, un dict) que es diferente de lo que declaraste (por ejemplo, un modelo de Pydantic).

En esos casos, puedes usar el parámetro del *decorador de path operation* `response_model` en lugar del tipo de retorno.

    SecretStr: str,
    set: list,
    UUID: str,
    Url: str,
    AnyUrl: str,
}


def generate_encoders_by_class_tuples(
    type_encoder_map: dict[Any, Callable[[Any], Any]],
) -> dict[Callable[[Any], Any], tuple[Any, ...]]:
    encoders_by_class_tuples: dict[Callable[[Any], Any], tuple[Any, ...]] = defaultdict(
        tuple
    )
    for type_, encoder in type_encoder_map.items():

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.protwords;

import java.util.Date;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.dict.DictionaryCreator;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;

import jakarta.annotation.PostConstruct;

/**

#### Dict { #dict }

Чтобы определить `dict`, вы передаёте 2 параметра типов, разделённые запятой.

Первый параметр типа — для ключей `dict`.

Второй параметр типа — для значений `dict`:

{* ../../docs_src/python_types/tutorial008_py310.py hl[1] *}

Это означает:

* Переменная `prices` — это `dict`:
    * Ключи этого `dict` имеют тип `str` (скажем, название каждой позиции).

        translators=translators,
        authors=authors,
    )


def get_users_to_write(
    *,
    counter: Counter[str],
    authors: dict[str, Author],
    min_count: int = 2,
) -> dict[str, Any]:
    users: dict[str, Any] = {}
    for user, count in counter.most_common():
        if count >= min_count:
            author = authors[user]
            users[user] = {

    response = client.put(
        "/items/5",
        json={"description": "A very nice Item"},
    )
    assert response.status_code == 422, response.text
    assert response.json() == {
        "detail": [
            {
                "loc": ["body", "name"],
                "input": {"description": "A very nice Item"},
                "msg": "Field required",
                "type": "missing",
            },