"accessResultData": {
        "properties": {
          "transformerName": {
            "type": "keyword"
          },
          "encoding": {
            "type": "keyword"
          },
          "data": {
            "type": "binary"
          }
        }
      },
      "contentLength": {
        "type": "long"
      },
      "lastModified": {
        "type": "long"
      },
      "ruleId": {

# Extra Data Types { #extra-data-types }

Up to now, you have been using common data types, like:

* `int`
* `float`
* `str`
* `bool`

But you can also use more complex data types.

And you will still have the same features as seen up to now:

* Great editor support.
* Data conversion from incoming requests.
* Data conversion for response data.
* Data validation.
* Automatic annotation and documentation.

    * In Requests und Responses wird es wie ein `float` behandelt.
* Sie können alle gültigen Pydantic-Datentypen hier überprüfen: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Beispiel

Hier ist ein Beispiel für eine *Pfadoperation* mit Parametern, die einige der oben genannten Typen verwenden.

{* ../../docs_src/extra_data_types/tutorial001_an_py310.py hl[1,3,12:16] *}

* `Decimal`:
    * Pythonの標準的な`Decimal`です。
    * リクエストやレスポンスでは`float`と同じように扱います。

* Pydanticの全ての有効な型はこちらで確認できます: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic data types</a>。
## 例

ここでは、上記の型のいくつかを使用したパラメータを持つ*path operation*の例を示します。

{* ../../docs_src/extra_data_types/tutorial001.py hl[1,2,12:16] *}

関数内のパラメータは自然なデータ型を持っていることに注意してください。そして、以下のように通常の日付操作を行うことができます:

}

// DataUsageInfo represents data usage stats of the underlying Object API
type DataUsageInfo struct {
	TotalCapacity     uint64 `json:"capacity,omitempty"`
	TotalUsedCapacity uint64 `json:"usedCapacity,omitempty"`
	TotalFreeCapacity uint64 `json:"freeCapacity,omitempty"`

	// LastUpdate is the timestamp of when the data usage info was last updated.
	// This does not indicate a full scan.

{* ../../docs_src/extra_data_types/tutorial001.py hl[1,3,12:16] *}

Note que os parâmetros dentro da função tem seu tipo de dados natural, e você pode, por exemplo, realizar manipulações normais de data, como:

		{data, cred1, false},
	}

	for _, test := range tests {
		t.Run("", func(t *testing.T) {
			ddata, err := madmin.DecryptData(test.cred.String(), bytes.NewReader(test.edata))
			if err != nil && test.success {
				t.Errorf("Expected success, saw failure %v", err)
			}
			if err == nil && !test.success {
				t.Error("Expected failure, saw success")
			}
			if test.success {
				if !bytes.Equal(ddata, data) {

Harshavardhana <******@****.***> 1715215894 -0700

Taran Pelkey <******@****.***> 1743296162 -0400

Sebastián Ramírez <******@****.***> 1735583217 +0000