* 생성된 스키마는 이것이 `binary` "형식"의 `str`임을 명시합니다.
* `Decimal`:
    * 표준 파이썬의 `Decimal`.
    * 요청과 응답에서 `float`와 동일하게 다뤄집니다.
* 여기에서 모든 유효한 pydantic 데이터 자료형을 확인할 수 있습니다: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic 데이터 자료형</a>.

## 예시

위의 몇몇 자료형을 매개변수로 사용하는 *경로 작동* 예시입니다.

=== "Python 3.10+"

    ```Python hl_lines="1  3  12-16"

    * In requests and responses, handled the same as a `float`.
* You can check all the valid pydantic data types here: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Example

Here's an example *path operation* with parameters using some of the above types.

=== "Python 3.10+"

    ```Python hl_lines="1  3  12-16"

    * Стандартний Пайтонівський `Decimal`.
    * У запитах і відповідях це буде оброблено так само, як і `float`.
* Ви можете перевірити всі дійсні типи даних Pydantic тут: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">типи даних Pydantic</a>.

## Приклад

Ось приклад *path operation* з параметрами, використовуючи деякі з вищезазначених типів.

=== "Python 3.10+"

    * 生成的模式将指定这个 `str` 是 `binary` "格式"。
* `Decimal`:
    * 标准的 Python `Decimal`。
    * 在请求和响应中被当做 `float` 一样处理。
* 您可以在这里检查所有有效的pydantic数据类型: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic data types</a>.

## 例子

下面是一个*路径操作*的示例，其中的参数使用了上面的一些类型。

=== "Python 3.10+"

    ```Python hl_lines="1  3  12-16"
    {!> ../../../docs_src/extra_data_types/tutorial001_an_py310.py!}

// license that can be found in the LICENSE file.

package trace

import "fmt"

// Value is a dynamically-typed value obtained from a trace.
type Value struct {
	kind   ValueKind
	scalar uint64
}

// ValueKind is the type of a dynamically-typed value from a trace.
type ValueKind uint8

const (
	ValueBad ValueKind = iota
	ValueUint64
)

// Kind returns the ValueKind of the value.
//

// RUN: tf-opt %s -split-input-file -tfl-reduce-type-precision -verify-diagnostics

func.func @testI8ToI4WithinRange() -> (tensor<4xi8>) {
  %0 = arith.constant dense<[-8, 0, 1, 7]> : tensor<4xi8>
  // expected-error@+1 {{type of return operand 0 ('tensor<4xi4>') doesn't match function result type ('tensor<4xi8>')}}
  func.return %0 : tensor<4xi8>
}

func.func @testI8ToI4NotWithinRange() -> tensor<4xi8> {
  %0 = arith.constant dense<[-10, 2, 3, 8]> : tensor<4xi8>

import org.apache.maven.model.io.ModelParseException;
import org.apache.maven.model.io.ModelReader;
import org.apache.maven.model.locator.ModelLocator;
import org.eclipse.sisu.Typed;

/**
 *
 * Note: uses @Typed to limit the types it is available for injection to just ModelProcessor.
 *
 * This is because the ModelProcessor interface extends ModelLocator and ModelReader. If we

    ```

## `Union`, oder `anyOf`

Sie können deklarieren, dass eine Response eine <abbr title="Union – Verbund, Einheit‚ Vereinigung: Eines von Mehreren">`Union`</abbr> mehrerer Typen ist, sprich, einer dieser Typen.

Das wird in OpenAPI mit `anyOf` angezeigt.

/**
 *
 * Note: uses @Typed to limit the types it is available for injection to just ModelProcessor.
 *
 * This is because the ModelProcessor interface extends ModelLocator and ModelReader. If we
 * made this component available under all its interfaces then it could end up being injected
 * into itself leading to a stack overflow.
 *
 * A side effect of using @Typed is that it translates to explicit bindings in the container.

        expect:
        succeeds("runWork")

        and:
        file("build/workOutput").text == "foo"
        lib.file("build/workOutput").text == "foo"

        where:
        pluginId << [ 'typed-worker-plugin' ]
    }

    private void withTypedWorkerPluginInPluginBuild() {
        plugin.file("src/main/java/TypedParameter.java") << """
            import org.gradle.workers.WorkParameters;