* Pydantic'in veri yapıları aslında sadece senin tanımladığın classlar; Bu yüzden doğrulanmış dataların ile otomatik tamamlama, linting ve mypy'ı kullanarak sorunsuz bir şekilde çalışabilirsin
* **En kompleks** yapıları bile doğrula:
    * Hiyerarşik Pydantic modellerinin kullanımı ile beraber, Python `typing`’s `List` and `Dict`, vs gibi şeyleri doğrula.

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.

	if err != nil {
		c.Fatalf("unable to list policies: %v", err)
	}

	defaultPolicies := []string{
		"readwrite",
		"readonly",
		"writeonly",
		"diagnostics",
		"consoleAdmin",
	}

	for _, v := range defaultPolicies {
		if _, ok := policies[v]; !ok {
			c.Fatalf("Failed to find %s in policies list", v)
		}
	}

	bucket := getRandomBucketName()

    * 如果你知道 Python 型別，你就知道如何使用 Pydantic。
* 和你的 **<abbr title="Integrated Development Environment，和程式碼編輯器類似">IDE</abbr>/<abbr title="一個檢查程式碼錯誤的工具">linter</abbr>/brain** 都能好好配合：
    * 因為 Pydantic 的資料結構其實就是你自己定義的類別實例，所以自動補齊、linting、mypy 以及你的直覺都能很好地在經過驗證的資料上發揮作用。
* 驗證**複雜結構**：
    * 使用 Pydantic 模型時，你可以把資料結構分層設計，並且用 Python 的 `List` 和 `Dict` 等型別來定義。
    * 驗證器讓我們可以輕鬆地定義和檢查複雜的資料結構，並把它們轉換成 JSON Schema 進行記錄。
    * 你可以擁有深層**巢狀的 JSON** 物件，並對它們進行驗證和註釋。
* **可擴展**：

type WalkOptions struct {
	Filter       func(info FileInfo) bool // return WalkFilter returns 'true/false'
	Marker       string                   // set to skip until this object
	LatestOnly   bool                     // returns only latest versions for all matching objects
	AskDisks     string                   // dictates how many disks are being listed

 *
 * <p>For field types and method return types, you should generally use the immutable type (such as
 * {@link ImmutableList}) instead of the general collection interface type (such as {@link List}).
 * This communicates to your callers all of the semantic guarantees listed above, which is almost
 * always very useful information.
 *
 * <p>On the other hand, a <i>parameter</i> type of {@link ImmutableList} is generally a nuisance to

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{* ../../docs_src/custom_response/tutorial010.py hl[2,4] *}

/// tip | Tipp

Sie können dennoch weiterhin `response_class` in *Pfadoperationen* überschreiben, wie bisher.

///

## Zusätzliche Dokumentation

    }
    Object instance = createInstance(factory, args);
    List<Object> equalArgs = generateEqualFactoryArguments(factory, params, args);
    // Each group is a List of items, each item has a list of factory args.
    List<List<List<Object>>> argGroups = new ArrayList<>();
    argGroups.add(ImmutableList.of(args, equalArgs));
    EqualsTester tester =
        new EqualsTester(
            /* itemReporter= */ item -> {

    * Como as estruturas de dados do Pydantic são apenas instâncias de classes que você define, a auto completação, _linting_, _mypy_ e a sua intuição devem funcionar corretamente com seus dados validados.
* Valida **estruturas complexas**:
    * Use modelos hierárquicos do Pydantic, `List` e `Dict` do `typing` do Python, etc.