// Note: Duplicate Columns
				{Field: &schema.Field{Name: "FieldD"}},
			},
		},
		{
			Name:  "uniq_field_e1_e2",
			Class: "UNIQUE",
			Fields: []schema.IndexOption{
				{Field: &schema.Field{Name: "FieldE1"}},
				{Field: &schema.Field{Name: "FieldE2"}},
			},
		},
		{
			Name:  "uniq_field_f1_f2",
			Class: "UNIQUE",
			Fields: []schema.IndexOption{

            stream.forEach(field -> {
                count.incrementAndGet();
                assertTrue(field.equals("field1") || field.equals("field2") || field.equals("field3"));
            });
        });

        assertEquals(3, count.get());
    }

    @Test
    public void test_highlightedFields_empty() {
        String[] fields = {};
        queryFieldConfig.setHighlightedFields(fields);

        for (String field : queryFieldConfig.searchFields) {
            assertTrue("Search field " + field + " should be in Set", queryFieldConfig.searchFieldSet.contains(field));
        }
        for (String field : queryFieldConfig.facetFields) {
            assertTrue("Facet field " + field + " should be in Set", queryFieldConfig.facetFieldSet.contains(field));
        }

        facetInfo.size = 20;
        facetInfo.sort = "term.asc";

        String result = facetInfo.toString();
        assertEquals("FacetInfo [field=[field1], query=null, size=20, minDocCount=null, sort=term.asc, missing=null]", result);
    }

    // Test field assignment
    @Test
    public void test_fieldAssignment() {
        String[] fields = new String[] { "field1", "field2", "field3" };

# 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

# Body - Поля { #body-fields }

Таким же способом, как вы объявляете дополнительную валидацию и метаданные в параметрах *функции обработки пути* с помощью функций `Query`, `Path` и `Body`, вы можете объявлять валидацию и метаданные внутри Pydantic моделей, используя функцию `Field` из Pydantic.

## Импорт `Field` { #import-field }

Сначала вы должны импортировать его:

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

/// warning | Внимание

# 请求体 - 字段 { #body-fields }

与在*路径操作函数*中使用 `Query`、`Path` 、`Body` 声明校验与元数据的方式一样，可以使用 Pydantic 的 `Field` 在 Pydantic 模型内部声明校验和元数据。

## 导入 `Field` { #import-field }

首先，从 Pydantic 中导入 `Field`：

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

/// warning | 警告

注意，与从 `fastapi` 导入 `Query`，`Path`、`Body` 不同，要直接从 `pydantic` 导入 `Field` 。

///

## 声明模型属性 { #declare-model-attributes }

然后，使用 `Field` 定义模型的属性：

        assertTrue(result.contains("field1"));
        assertTrue(result.contains("exclude1"));
    }

    @Test
    public void test_getCacheKey_sorting() {
        String seed = "test_seed";
        String[] tags = { "zzz", "aaa", "mmm" };
        String[] roles = { "role3", "role1", "role2" };
        String[] fields = { "field3", "field1", "field2" };

# Body - Alanlar { #body-fields }

`Query`, `Path` ve `Body` ile *path operation function* parametrelerinde ek doğrulama ve metadata tanımlayabildiğiniz gibi, Pydantic modellerinin içinde de Pydantic'in `Field`'ını kullanarak doğrulama ve metadata tanımlayabilirsiniz.

## `Field`'ı import edin { #import-field }

Önce import etmeniz gerekir:

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

/// warning | Uyarı

# Body - 欄位 { #body-fields }

就像你可以在「路徑操作函式 (path operation function)」的參數中用 `Query`、`Path` 和 `Body` 宣告額外的驗證與中繼資料一樣，你也可以在 Pydantic 模型中使用 Pydantic 的 `Field` 來宣告驗證與中繼資料。

## 匯入 `Field` { #import-field }

首先，你需要匯入它：

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


/// warning

請注意，`Field` 是直接從 `pydantic` 匯入的，不像其他（如 `Query`、`Path`、`Body` 等）是從 `fastapi` 匯入。

///

## 宣告模型屬性 { #declare-model-attributes }