У такому разі ви можете просто замінити стандартні `dataclasses` на `pydantic.dataclasses`, що є взаємозамінником:

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. Ми все ще імпортуємо `field` зі стандартних `dataclasses`.

2. `pydantic.dataclasses` - це взаємозамінник для `dataclasses`.

3. Dataclass `Author` містить список dataclass `Item`.

4. Dataclass `Author` використовується як параметр `response_model`.

/**
 * Annotation used to mark fields that represent configuration properties.
 * This annotation provides metadata about how the configuration property
 * should be handled, including its source, type, default value, and whether it's read-only.
 *
 * @since 4.0.0
 */
@Experimental
@Documented
@Retention(RetentionPolicy.CLASS)
@Target(ElementType.FIELD)
public @interface Config {

    /**

 */
@GwtCompatible
@NullUnmarked
abstract class AbstractAbstractFutureTest extends TestCase {
  @SuppressWarnings("initialization.field.uninitialized")
  private TestedFuture<@Nullable Integer> future;

  @SuppressWarnings("initialization.field.uninitialized")
  private AbstractFuture<@Nullable Integer> delegate;

  abstract AbstractFuture<@Nullable Integer> newDelegate();

  @Override

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. Todavía importamos `field` de los `dataclasses` estándar.

2. `pydantic.dataclasses` es un reemplazo directo para `dataclasses`.

3. El dataclass `Author` incluye una lista de dataclasses `Item`.

Nesse caso, você pode simplesmente trocar as `dataclasses` padrão por `pydantic.dataclasses`, que é um substituto direto:

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. Ainda importamos `field` das `dataclasses` padrão.

2. `pydantic.dataclasses` é um substituto direto para `dataclasses`.

3. A dataclass `Author` inclui uma lista de dataclasses `Item`.

```JSON
{
  "detail": [
    {
      "type": "missing",
      "loc": [
        "query",
        "needy"
      ],
      "msg": "Field required",
      "input": null
    }
  ]
}
```

`needy` zorunlu bir parametre olduğundan, URL'de ayarlamanız gerekir:

```
http://127.0.0.1:8000/items/foo-item?needy=sooooneedy
```

```JSON
{
  "detail": [
    {
      "type": "missing",
      "loc": [
        "query",
        "needy"
      ],
      "msg": "Field required",
      "input": null
    }
  ]
}
```

Da `needy` ein erforderlicher Parameter ist, müssen Sie ihn in der URL setzen:

```
http://127.0.0.1:8000/items/foo-item?needy=sooooneedy
```

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. Nous continuons à importer `field` depuis les `dataclasses` standard.

2. `pydantic.dataclasses` est un remplacement drop‑in pour `dataclasses`.

3. La dataclass `Author` inclut une liste de dataclasses `Item`.

		return
	}
	// Expect (SB), (FP), (PC), or (SP)
	p.get('(')
	reg := p.get(scanner.Ident).String()
	p.get(')')
	p.setPseudoRegister(a, reg, isStatic, prefix)
}

// setPseudoRegister sets the NAME field of addr for a pseudo-register reference such as (SB).
func (p *Parser) setPseudoRegister(addr *obj.Addr, reg string, isStatic bool, prefix rune) {
	if addr.Reg != 0 {
		p.errorf("internal error: reg %s already set in pseudo", reg)

Birkaç fark var:

* `table=True`, SQLModel’e bunun bir *table model* olduğunu söyler; SQL veritabanında bir **table**’ı temsil etmelidir, sadece bir *data model* değildir (diğer normal Pydantic sınıflarında olduğu gibi).

* `Field(primary_key=True)`, SQLModel’e `id`’nin SQL veritabanındaki **primary key** olduğunu söyler (SQL primary key’leri hakkında daha fazlasını SQLModel dokümantasyonunda öğrenebilirsiniz).