Translate to Traditional Chinese (繁體中文).

Language code: zh-hant.

### Grammar and tone

1) Use clear, concise technical Traditional Chinese consistent with existing docs.
2) Address the reader naturally (commonly using “你/你的”).

### Headings

1) Follow existing Traditional Chinese heading style (short and descriptive).
2) Do not add trailing punctuation to headings.

### Quotes and punctuation

* 🌐 Add Korean translation for `docs/ko/docs/tutorial/header-param-models.md`. PR [#13001](https://github.com/fastapi/fastapi/pull/13001) by [@hard-coders](https://github.com/hard-coders).
* 🌐 Add Korean translation for `docs/ko/docs/tutorial/request-form-models.md`. PR [#13002](https://github.com/fastapi/fastapi/pull/13002) by [@hard-coders](https://github.com/hard-coders).

                    "post": {
                        "summary": "Create Invoice",

        if (
            isinstance(field_info, params.File)
            and is_bytes_field(field)
            and isinstance(value, UploadFile)
        ):
            value = await value.read()
        elif (
            is_bytes_sequence_field(field)
            and isinstance(field_info, params.File)
            and value_is_sequence(value)
        ):
            # For types

    assert response.json() == {"p": ["hello", "world"]}


# =====================================================================================
# Alias and validation alias


@app.post(
    "/optional-list-alias-and-validation-alias",
    operation_id="optional_list_alias_and_validation_alias",
)
def read_optional_list_alias_and_validation_alias(
    p: Annotated[

# Using Dataclasses { #using-dataclasses }

FastAPI is built on top of **Pydantic**, and I have been showing you how to use Pydantic models to declare requests and responses.

But FastAPI also supports using <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a> the same way:

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

        if (
            key in main_dict
            and isinstance(main_dict[key], dict)
            and isinstance(value, dict)
        ):
            deep_dict_update(main_dict[key], value)
        elif (
            key in main_dict
            and isinstance(main_dict[key], list)
            and isinstance(update_dict[key], list)
        ):

Url: type[Any]


# Copy of Pydantic v2, compatible with v1
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:  # pragma: no cover
        if isinstance(cls, WithArgsTypes):
            return False
        raise  # pragma: no cover

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

description = "Provides a set of plugins that are shared between the Gradle and build-logic builds"

tasks.register("check") {
    dependsOn(subprojects.map { "${it.name}:check" })

 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

class VersionedSettingsBranchTest {
    @ParameterizedTest
    @CsvSource(
        value = [
            "master,    0",
            "release,   1",