Вы можете использовать все те же возможности валидации и инструменты, что и для Pydantic‑моделей, например разные типы данных и дополнительную валидацию через `Field()`.

//// tab | Pydantic v2

{* ../../docs_src/settings/tutorial001_py39.py hl[2,5:8,11] *}

////

//// tab | Pydantic v1

/// info | Информация

	globalDirSuffix                = "__XLDIR__"
	globalDirSuffixWithSlash       = globalDirSuffix + slashSeparator

	// Add new global values here.
)

const (
	// Limit fields size (except file) to 1Mib since Policy document
	// can reach that size according to https://aws.amazon.com/articles/1434
	maxFormFieldSize = int64(1 * humanize.MiByte)

		fi.Metadata[ReservedMetadataPrefix+"actual-size"] = strconv.FormatInt(objectActualSize, 10)
	}

	if opts.DataMovement {
		fi.SetDataMov()
	}

	// Update all erasure metadata, make sure to not modify fields like
	// checksum which are different on each disks.
	for index := range partsMetadata {
		if partsMetadata[index].IsValid() {
			partsMetadata[index].Size = fi.Size
			partsMetadata[index].ModTime = fi.ModTime

You can use all the same validation features and tools you use for Pydantic models, like different data types and additional validations with `Field()`.

{* ../../docs_src/settings/tutorial001_py39.py hl[2,5:8,11] *}

/// tip

If you want something quick to copy and paste, don't use this example, use the last one below.

///

		return nil
	}
	return map[string]string{
		c.Type.String():       c.Encoded,
		xhttp.AmzChecksumType: c.Type.ObjType(),
	}
}

// Equal returns whether two checksum structs are equal in all their fields.
func (c *Checksum) Equal(s *Checksum) bool {
	if c == nil || s == nil {
		return c == s
	}
	return c.Type == s.Type &&
		c.Encoded == s.Encoded &&
		bytes.Equal(c.Raw, s.Raw) &&

	default:
		lookup = minio.BucketLookupAuto
	}
	return lookup
}

// BatchJobPrefix - to support prefix field yaml unmarshalling with string or slice of strings
type BatchJobPrefix []string

var _ yaml.Unmarshaler = &BatchJobPrefix{}

// UnmarshalYAML - to support prefix field yaml unmarshalling with string or slice of strings
func (b *BatchJobPrefix) UnmarshalYAML(value *yaml.Node) error {
	// try slice first

pkg debug/dwarf, const ClassStringAlt = 14
pkg debug/dwarf, const ClassStringAlt Class
pkg debug/dwarf, method (*Data) LineReader(*Entry) (*LineReader, error)
pkg debug/dwarf, method (*Entry) AttrField(Attr) *Field
pkg debug/dwarf, method (*LineReader) Next(*LineEntry) error
pkg debug/dwarf, method (*LineReader) Reset()
pkg debug/dwarf, method (*LineReader) Seek(LineReaderPos)

///

#### Данные со значениями для полей, имеющих значения по умолчанию { #data-with-values-for-fields-with-defaults }

Но если в ваших данных есть значения для полей модели, для которых указаны значения по умолчанию, как у элемента с ID `bar`:

```Python hl_lines="3  5"
{
    "name": "Bar",

	}
	return xlMeta
}

// Compare the unmarshaled XLMetaV1 with the one obtained from jsoniter parsing.
func compareXLMetaV1(t *testing.T, unMarshalXLMeta, jsoniterXLMeta xlMetaV1Object) {
	// Start comparing the fields of xlMetaV1Object obtained from jsoniter parsing with one parsed using json unmarshalling.
	if unMarshalXLMeta.Version != jsoniterXLMeta.Version {

	if errCode != ErrUnsignedHeaders {
		t.Fatalf("Expected the APIErrorCode to %d, but got %d", ErrUnsignedHeaders, errCode)
	}

	// case where the list of signed headers doesn't contain the host field.
	signedHeaders = signedHeaders[2:5]
	// expected to fail with `ErrUnsignedHeaders`.
	_, errCode = extractSignedHeaders(signedHeaders, r)
	if errCode != ErrUnsignedHeaders {