full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// 정보

`**user_dict`에 대한 자세한 설명은 [**추가 모델** 문서](../extra-models.md#about-user_indict){.internal-link target=_blank}를 다시 읽어봅시다.

///

## 토큰 반환하기

`token` 엔드포인트의 응답은 JSON 객체여야 합니다.

`token_type`이 있어야 합니다. 여기서는 "Bearer" 토큰을 사용하므로 토큰 유형은 "`bearer`"여야 합니다.

All rights reserved.

All other contributions:

Copyright (c) 2014, the respective contributors
All rights reserved.

Caffe uses a shared copyright model: each contributor holds copyright over
their contributions to Caffe. The project versioning records all such
contribution and copyright details. If a contributor wants to further mark

	// but we must make sure there is always space to add 256 bytes:
	// https://github.com/aws/aws-sdk-java/blob/master/aws-java-sdk-s3/src/main/java/com/amazonaws/services/s3/model/SelectObjectContentEventStream.java#L197
	maxRecordMessageLength = (128 << 10) - 256
)

var bufLength = payloadLenForMsgLen(maxRecordMessageLength)

			minio.PutObjectOptions{DisableContentSha256: true},
		)
		return err
	}

	return NotImplemented{}
}

type listerAt []os.FileInfo

// Modeled after strings.Reader's ReadAt() implementation
func (f listerAt) ListAt(ls []os.FileInfo, offset int64) (int, error) {
	var n int
	if offset >= int64(len(f)) {
		return 0, io.EOF
	}
	n = copy(ls, f[offset:])

///

/// tip | "豆知識"

"AlexNet"、"ResNet"そして"LeNet"は機械学習<abbr title="Technically, Deep Learning model architectures">モデル</abbr>の名前です。

///

### *パスパラメータ*の宣言

次に、作成したenumクラスである`ModelName`を使用した型アノテーションをもつ*パスパラメータ*を作成します:

```Python hl_lines="16"
{!../../docs_src/path_params/tutorial005.py!}
```

////

추가 정보는 있는 그대로 해당 모델의 **JSON 스키마** 결과에 추가되고, API 문서에서 사용합니다.

//// tab | Pydantic v2

Pydantic 버전 2에서 <a href="https://docs.pydantic.dev/latest/usage/model_config/" class="external-link" target="_blank">Pydantic 공식 문서: Model Config</a>에 나와 있는 것처럼 `dict`를 받는 `model_config` 어트리뷰트를 사용할 것입니다.

`"json_schema_extra"`를 생성된 JSON 스키마에서 보여주고 싶은 별도의 데이터와 `examples`를 포함하는 `dict`으로 설정할 수 있습니다.

////

//// tab | Pydantic v1

import java.util.LinkedHashMap;
import java.util.List;
import java.util.Locale;
import java.util.Map;
import java.util.Set;
import java.util.function.Function;

import org.apache.maven.internal.impl.model.DefaultInterpolator;

/**
 * Enhancement of the standard <code>Properties</code>
 * managing the maintain of comments, etc.
 */
public class MavenProperties extends AbstractMap<String, String> {

	Float  DataType = "float"
	String DataType = "string"
	Time   DataType = "time"
	Bytes  DataType = "bytes"
)

const DefaultAutoIncrementIncrement int64 = 1

// Field is the representation of model schema's field
type Field struct {
	Name                   string
	DBName                 string
	BindNames              []string
	EmbeddedBindNames      []string
	DataType               DataType

Nur Standard-**Python+**.

Zum Beispiel für ein `int`:

```Python
item_id: int
```

oder für ein komplexeres `Item`-Modell:

```Python
item: Item
```

... und mit dieser einen Deklaration erhalten Sie:

* Editor-Unterstützung, einschließlich:
    * Code-Vervollständigung.
    * Typprüfungen.

   * stripes, the intended concurrency level, and the typical number of keys used in a {@code
   * bulkGet(keys)} operation. See <a href="http://www.mathpages.com/home/kmath199.htm">Balls in
   * Bins model</a> for mathematical formulas that can be used to estimate the probability of
   * collisions.
   *
   * @param keys arbitrary non-null keys