form of JUnit-based XML.
"""
import argparse
import datetime
import os
import re
from typing import Dict, Union
import xml.etree.ElementTree as ElemTree


ResultDictType = Dict[str, Dict[str, Union[str, int]]]

RESULT_STORE_LINK_RE = re.compile(
    r'^INFO: Streaming build results to: (https://[\w./\-]+)')

 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.kuromoji;

import java.util.ArrayList;
import java.util.Date;
import java.util.List;

import org.codelibs.fess.dict.DictionaryFile.PagingList;
import org.codelibs.fess.unit.UnitFessTestCase;

public class KuromojiFileTest extends UnitFessTestCase {

from typing import (
    Any,
    BinaryIO,
    Callable,
    Dict,
    Iterable,
    Optional,
    Type,
    TypeVar,
    cast,
)

from fastapi._compat import (
    PYDANTIC_V2,
    CoreSchema,
    GetJsonSchemaHandler,
    JsonSchemaValue,
    with_info_plain_validator_function,
)
from starlette.datastructures import URL as URL  # noqa: F401
from starlette.datastructures import Address as Address  # noqa: F401

Sie schreiben Standard-Python mit Typen:

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Deklarieren Sie eine Variable als ein `str`
# und bekommen Sie Editor-Unterstütung innerhalb der Funktion
def main(user_id: str):
    return user_id

```Python hl_lines="1  9  12"
{!../../docs_src/response_change_status_code/tutorial001.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

* OpenAPI *경로 작동*의 응답에 JSON 스키마 추가.
* 자동 생성 문서 시스템에 사용.

하지만 가장 중요한 것은:

* 해당 모델의 출력 데이터 제한. 이것이 얼마나 중요한지 아래에서 볼 것입니다.

/// note | "기술 세부사항"

응답 모델은 함수의 타입 어노테이션 대신 이 매개변수로 선언하는데, 경로 함수가 실제 응답 모델을 반환하지 않고 `dict`, 데이터베이스 객체나 기타 다른 모델을 `response_model`을 사용하여 필드 제한과 직렬화를 수행하고 반환할 수 있기 때문입니다

///

## 동일한 입력 데이터 반환

여기서 우리는 평문 비밀번호를 포함하는 `UserIn` 모델을 선언합니다:

```Python hl_lines="9  11"

👆 💪 📣 🔢 🆎 `Response` 👆 *➡ 🛠️ 🔢* (👆 💪 🍪).

& ⤴️ 👆 💪 ⚒ 🎚 👈 *🔀* 📨 🎚.

```Python hl_lines="1  7-8"
{!../../docs_src/response_headers/tutorial002.py!}
```

& ⤴️ 👆 💪 📨 🙆 🎚 👆 💪, 👆 🛎 🔜 ( `dict`, 💽 🏷, ♒️).

& 🚥 👆 📣 `response_model`, ⚫️ 🔜 ⚙️ ⛽ & 🗜 🎚 👆 📨.

**FastAPI** 🔜 ⚙️ 👈 *🔀* 📨 ⚗ 🎚 (🍪 & 👔 📟), & 🔜 🚮 👫 🏁 📨 👈 🔌 💲 👆 📨, ⛽ 🙆 `response_model`.

```Python hl_lines="1  9  12"
{!../../docs_src/response_change_status_code/tutorial001.py!}
```

E então você pode retornar qualquer objeto que você precise, como você faria normalmente (um `dict`, um modelo de banco de dados, etc.).

E se você declarar um `response_model`, ele ainda será utilizado para filtrar e converter o objeto que você retornou.

my_second_user: User = User(**second_user_data)
```

/// info | Información

`**second_user_data` significa:

Pasa las <abbr title="en español key se refiere a la guía de un diccionario">keys</abbr> y los valores del dict `second_user_data` directamente como argumentos de key-value, equivalente a: `User(id=4, name="Mary", joined="2018-11-30")`

///

### Soporte del editor

licenses(["notice"])

exports_files([
    "LICENSE",
    # The leakr files are used by //third_party/cloud_tpu and
    # //third_party/tensorboard/google:copybara_config_test.
    "leakr_badwords.dic",
    "leakr_badfiles.dic",
    "leakr_file_type_recipe.ftrcp",
])

# copybara:comment_begin(oss-only)
TENSORFLOW_API_INIT_FILES_V2 = (
    TENSORFLOW_API_INIT_FILES +
    get_compat_files(TENSORFLOW_API_INIT_FILES, 2) +