同様に、このデータベースはPydanticモデル（属性を持つオブジェクト）を受け取らず、`dict`だけを受け取ります。

そのために`jsonable_encoder`を使用することができます。

Pydanticモデルのようなオブジェクトを受け取り、JSON互換版を返します:

{* ../../docs_src/encoder/tutorial001.py hl[5,22] *}

この例では、Pydanticモデルを`dict`に、`datetime`を`str`に変換します。

# JSON Compatible Encoder { #json-compatible-encoder }

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder` { #using-the-jsonable-encoder }

		return e, reedsolomon.ErrMaxShardNum
	}

	e = Erasure{
		dataBlocks:   dataBlocks,
		parityBlocks: parityBlocks,
		blockSize:    blockSize,
	}

	// Encoder when needed.
	var enc reedsolomon.Encoder
	var once sync.Once
	e.encoder = func() reedsolomon.Encoder {
		once.Do(func() {
			e, err := reedsolomon.New(dataBlocks, parityBlocks, reedsolomon.WithAutoGoroutines(int(e.ShardSize())))
			if err != nil {

By default, **FastAPI** would automatically convert that return value to JSON using the `jsonable_encoder` explained in [JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank}.

Then, behind the scenes, it would put that JSON-compatible data (e.g. a `dict`) inside of a `JSONResponse` that would be used to send the response to the client.

 * <li>{@link #settingsId}: ID of the settings.</li>
 * <li>{@link #settings}: SuggestSettings instance containing configuration settings.</li>
 * <li>{@link #encoder}: Base64 encoder instance for encoding IDs.</li>
 * </ul>
 */
public class ArraySettings {
    private static final Logger logger = LogManager.getLogger(ArraySettings.class);

    /** OpenSearch client. */

 */
package jcifs.internal.dfs;

import java.nio.charset.StandardCharsets;

import jcifs.Encodable;
import jcifs.internal.util.SMBUtil;

/**
 * DFS (Distributed File System) referral request buffer encoder.
 * Creates encoded request buffers for DFS referral requests, specifying the maximum
 * referral level and target path for which DFS resolution is requested.
 *
 * @author mbechler
 */

If you have a Pydantic model in your test and you want to send its data to the application during testing, you can use the `jsonable_encoder` described in [JSON Compatible Encoder](encoder.md){.internal-link target=_blank}.

///

## Run it { #run-it }

After that, you just need to install `pytest`.

## Convert any Data to JSON-compatible { #convert-any-data-to-json-compatible }

To convert any data to JSON-compatible, read the docs for [Tutorial - JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank}.

## OpenAPI Metadata - Docs { #openapi-metadata-docs }

По умолчанию **FastAPI** автоматически преобразует возвращаемое значение в JSON с помощью `jsonable_encoder`, как описано в [JSON кодировщик](../tutorial/encoder.md){.internal-link target=_blank}.

Затем "под капотом" эти данные, совместимые с JSON (например `dict`), помещаются в `JSONResponse`, который используется для отправки ответа клиенту.

	values.Set(storageRESTVolume, volume)
	values.Set(storageRESTTotalVersions, strconv.Itoa(len(versions)))

	var buffer bytes.Buffer
	encoder := msgp.NewWriter(&buffer)
	for _, version := range versions {
		version.EncodeMsg(encoder)
	}
	storageLogIf(ctx, encoder.Flush())

	errs = make([]error, len(versions))

	respBody, err := client.call(ctx, storageRESTMethodDeleteVersions, values, &buffer, -1)