],
            "msg": "value is not a valid integer",
            "type": "type_error.integer"
        }
    ]
}
```

вы получите текстовую версию:

```
Validation errors:
Field: ('path', 'item_id'), Error: Input should be a valid integer, unable to parse string as an integer
```

### Переопределите обработчик ошибок `HTTPException` { #override-the-httpexception-error-handler }

			return err
		}
	} else {
		// Evaluate the (only) argument
		val, err = e.SFunc.ArgsList[0].evalNode(r, tableAlias)
		if err != nil {
			return err
		}
	}

	if val.IsNull() {
		// E.g. the column or field does not exist in the
		// record - in all such cases the aggregation is not
		// updated.
		return nil
	}

	argVal := val
	if funcName != aggFnCount {
		// All aggregation functions, except COUNT require a

有一些区别：

* `table=True` 会告诉 SQLModel 这是一个*表模型*，它应该表示 SQL 数据库中的一个*表*，而不仅仅是一个*数据模型*（就像其他常规的 Pydantic 类一样）。

* `Field(primary_key=True)` 会告诉 SQLModel `id` 是 SQL 数据库中的**主键**（您可以在 SQLModel 文档中了解更多关于 SQL 主键的信息）。

    把类型设置为 `int | None` ，SQLModel 就能知道该列在 SQL 数据库中应该是 `INTEGER` 类型，并且应该是 `NULLABLE` 。

* `Field(index=True)` 会告诉 SQLModel 应该为此列创建一个 **SQL 索引**，这样在读取按此列过滤的数据时，程序能在数据库中进行更快的查找。

Puedes lograr eso usando <a href="https://docs.pydantic.dev/latest/concepts/validators/#field-after-validator" class="external-link" target="_blank">`AfterValidator` de Pydantic</a> dentro de `Annotated`.

/// tip | Consejo

Pydantic también tiene <a href="https://docs.pydantic.dev/latest/concepts/validators/#field-before-validator" class="external-link" target="_blank">`BeforeValidator`</a> y otros. 🤓

///

     * purposes, the "count" field, tracking the number of elements, serves as that volatile
     * variable ensuring visibility. This is convenient because this field needs to be read in many
     * read operations anyway:
     *
     * - All (unsynchronized) read operations must first read the "count" field, and should not
     * look at table entries if it is 0.
     *

Deployment-related operations.
     * Behavior change:
        * Deployment creates ReplicaSets instead of ReplicationControllers.
        * Scale subresource now has a new <code>targetSelector</code> field in its status. This field supports the new set-based selectors supported
by Deployments, but in a serialized format.
     * Spec change:

	Name      string
	Prefix    string
	KeyMarker string

	// When response is truncated (the IsTruncated element value in the response
	// is true), you can use the key name in this field as marker in the subsequent
	// request to get next set of objects. Server lists objects in alphabetical
	// order Note: This element is returned only if you have delimiter request parameter

type Reader struct {
	r             io.ReaderAt
	File          []*File
	Comment       string
	decompressors map[uint16]Decompressor

	// Some JAR files are zip files with a prefix that is a bash script.
	// The baseOffset field is the start of the zip file proper.
	baseOffset int64

	// fileList is a list of files sorted by ename,
	// for use by the Open method.
	fileListOnce sync.Once
	fileList     []fileListEntry
}

     * This is an unsynchronized read! After the read, the function returns immediately or acquires
     * the lock to check again. Since an IDLE state was observed inside the preceding synchronized
     * block, and reference field assignment is atomic, this may save reacquiring the lock when
     * another thread or the worker task has cleared the count and set the state.
     *
     * <p>When {@link #executor} is a directExecutor(), the value written to

     * This is an unsynchronized read! After the read, the function returns immediately or acquires
     * the lock to check again. Since an IDLE state was observed inside the preceding synchronized
     * block, and reference field assignment is atomic, this may save reacquiring the lock when
     * another thread or the worker task has cleared the count and set the state.
     *
     * <p>When {@link #executor} is a directExecutor(), the value written to