<small>* оцінка на основі тестів внутрішньої команди розробників, створення продуктових застосунків.</small>

## Спонсори

<!-- sponsors -->

{% if sponsors %}

      codec.encode(writer, value)
    }
  }

  /**
   * Returns a copy with a context tag. This should be used when the type is ambiguous on its own.
   * For example, the tags in this schema are 0 and 1:
   *
   * ```
   * Point ::= SEQUENCE {
   *   x [0] INTEGER OPTIONAL,
   *   y [1] INTEGER OPTIONAL
   * }
   * ```
   *

 *
 * <p>This class is commonly used to pass configuration parameters to data store
 * implementations during crawling operations, allowing for flexible parameter
 * handling without tight coupling to specific parameter schemas.</p>
 */
public class DataStoreParams {

    /**
     * Internal map storing parameter key-value pairs.
     * Uses ParamMap for automatic case format conversion between camelCase and snake_case.
     */

E o **FastAPI** vai manipulá-los, mandar para você os dados corretos na sua função, e validar e documentar o schema correto na *operação de rota*.

Você também pode declarar valores singulares para serem recebidos como parte do corpo.

/// check | **FastAPI** lo usa para

Manejar toda la validación de datos, serialización de datos y documentación automática de modelos (basada en JSON Schema).

**FastAPI** luego toma esos datos JSON Schema y los coloca en OpenAPI, aparte de todas las otras cosas que hace.

///

### <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a>

You can also use `dataclasses` in the `response_model` parameter:

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

The dataclass will be automatically converted to a Pydantic dataclass.

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses in Nested Data Structures { #dataclasses-in-nested-data-structures }

///

Das wird:

* Diesen Statuscode mit der Response zurücksenden.
* Ihn als solchen im OpenAPI-Schema dokumentieren (und somit in den Benutzeroberflächen):

<img src="/img/tutorial/response-status-code/image01.png">

/// note | Hinweis

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

Die Datenklasse wird automatisch in eine Pydantic-Datenklasse konvertiert.

Auf diese Weise wird deren Schema in der Benutzeroberfläche der API-Dokumentation angezeigt:

<img src="/img/tutorial/dataclasses/image01.png">

## Datenklassen in verschachtelten Datenstrukturen

package schema

import (
	"context"
	"fmt"
	"reflect"
	"regexp"
	"strings"

	"gorm.io/gorm/clause"
	"gorm.io/gorm/utils"
)

var embeddedCacheKey = "embedded_cache_store"

func ParseTagSetting(str string, sep string) map[string]string {
	settings := map[string]string{}
	names := strings.Split(str, sep)

	for i := 0; i < len(names); i++ {
		j := i
		if len(names[j]) > 0 {
			for {

				if err := query(&q); err != nil {
					db.AddError(err)
				}
			}

			relation, ok := db.Statement.Schema.Relationships.Relations[association]
			if !ok {
				if preloadFields := strings.Split(association, "."); len(preloadFields) > 1 {
					relationships := &db.Statement.Schema.Relationships
					for _, field := range preloadFields {
						var ok bool
						relation, ok = relationships.Relations[field]