* 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。

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

注意，函数内的参数有原生的数据类型，你可以，例如，执行正常的日期操作，如:

    * 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.

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.

* `Decimal`:
    * `Decimal` estándar de Python.
    * En requests y responses, manejado igual que un `float`.
* Puedes revisar todos los tipos de datos válidos de Pydantic aquí: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Tipos de datos de Pydantic</a>.

## Ejemplo { #example }

Aquí tienes un ejemplo de una *path operation* con parámetros usando algunos de los tipos anteriores.

     * @return The path to the suggest analyzer configuration file.
     */
    protected String getSuggestAnalyzerPath() {
        final Object typeObj = settings.get("search_engine.type");
        if (typeObj != null) {
            final String path = "suggest_indices/_" + typeObj.toString() + "/suggest_analyzer.json";
            if (ResourceUtil.getResourceNoException(path) != null) {
                return path;
            }

package cmd

// SetupType - enum for setup type.
type SetupType int

const (
	// UnknownSetupType - starts with unknown setup type.
	UnknownSetupType SetupType = iota

	// FSSetupType - FS setup type enum.
	FSSetupType

	// ErasureSDSetupType - Erasure single drive setup enum.
	ErasureSDSetupType

	// ErasureSetupType - Erasure setup type enum.
	ErasureSetupType

      }
    }

    // Write the payload.
    sink.writeAll(content)
  }

  /**
   * Execute [block] with a new namespace for type hints. Type hints from the enclosing type are no
   * longer usable by the current type's members.
   */
  fun <T> withTypeHint(block: () -> T): T {
    typeHintStack.add(null)
    try {
      return block()
    } finally {

	stsRouter.Methods(http.MethodPost).MatcherFunc(func(r *http.Request, rm *mux.RouteMatch) bool {
		ctypeOk := wildcard.MatchSimple("application/x-www-form-urlencoded*", r.Header.Get(xhttp.ContentType))
		authOk := wildcard.MatchSimple(signV4Algorithm+"*", r.Header.Get(xhttp.Authorization))
		noQueries := len(r.URL.RawQuery) == 0
		return ctypeOk && authOk && noQueries
	}).HandlerFunc(httpTraceAll(sts.AssumeRole))

		Value: schema.Table,
	}

	var (
		typeName = polymorphic + "Type"
		typeId   = polymorphic + "ID"
	)

	if value, ok := field.TagSettings["POLYMORPHICTYPE"]; ok {
		typeName = strings.TrimSpace(value)
	}

	if value, ok := field.TagSettings["POLYMORPHICID"]; ok {
		typeId = strings.TrimSpace(value)
	}

#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/test.h"

using ::tensorflow::string;

typedef std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)>
    unique_tensor_ptr;

TF_Tensor* BoolTensor(int32_t v);

// Create a tensor with values of type TF_INT8 provided by `values`.