Map<String, Object> source;
        while ((source = reader.read()) != null) {
            assertTrue(source.get("field1").toString().startsWith("test"));
            valueSet.add(source.get("field1").toString());
            count++;
        }
        assertEquals(num, count);
        assertEquals(num, valueSet.size());
    }

    @Test

# Body - Fields { #body-fields }

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field` { #import-field }

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

			field.IgnoreMigration = true
		case "migration":
			field.IgnoreMigration = true
		}
	}

	if v, ok := field.TagSettings["->"]; ok {
		field.Creatable = false
		field.Updatable = false
		if strings.ToLower(v) == "false" {
			field.Readable = false
		} else {
			field.Readable = true
		}
	}

	if v, ok := field.TagSettings["<-"]; ok {
		field.Creatable = true
		field.Updatable = true

# Body – Felder { #body-fields }

So wie Sie zusätzliche Validierung und Metadaten in Parametern der *Pfadoperation-Funktion* mittels `Query`, `Path` und `Body` deklarieren, können Sie auch innerhalb von Pydantic-Modellen zusätzliche Validierung und Metadaten deklarieren, mittels Pydantics `Field`.

## `Field` importieren { #import-field }

Importieren Sie es zuerst:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Achtung

# Body - Campos { #body-fields }

De la misma manera que puedes declarar validaciones adicionales y metadatos en los parámetros de las *path operation function* con `Query`, `Path` y `Body`, puedes declarar validaciones y metadatos dentro de los modelos de Pydantic usando `Field` de Pydantic.

## Importar `Field` { #import-field }

Primero, tienes que importarlo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Advertencia

// JSON utilities with proper escaping
String escaped = JsonUtil.escape("Hello \"World\" with special chars");
String unescaped = JsonUtil.unescape(escaped);

// Text tokenization
Tokenizer tokenizer = new Tokenizer("field1,field2,field3", ",");
while (tokenizer.hasMoreTokens()) {
    String token = tokenizer.nextToken();
    // Process each token
}

// Decimal formatting

# Corpo - Campos { #body-fields }

Da mesma forma que você pode declarar validações adicionais e metadados nos parâmetros de uma *função de operação de rota* com `Query`, `Path` e `Body`, você pode declarar validações e metadados dentro de modelos do Pydantic usando `Field` do Pydantic.

## Importe `Field` { #import-field }

Primeiro, você tem que importá-lo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Atenção

        item.setReadings(newReadings);
        assertArrayEquals(newReadings, item.getReadings());

        // Test fields
        String[] fields = { "field1", "field2" };
        item.setFields(fields);
        assertArrayEquals(fields, item.getFields());

        // Test tags
        String[] tags = { "tag1", "tag2" };
        item.setTags(tags);

   * identity equality of its Thread field so that the task field is only accessed by a single
   * thread.
   */
  private static final class ThreadConfinedTaskQueue {
    /**
     * This field is only used for identity comparisons with the current thread. Field assignments
     * are atomic, but do not provide happens-before ordering; however:
     *
     * <ul>

                if (isExcludeSearchword(words[i], fields != null && fields.length > 0 ? fields[0] : "", langs, analyzer)) {
                    continue;
                }

                final String word = normalizer.normalize(words[i], fields != null && fields.length > 0 ? fields[0] : "", langs);
                final List<String> l = readingConverter.convert(word, fields != null && fields.length > 0 ? fields[0] : "", langs);