import pytest
from fastapi import FastAPI, Query
from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.testclient import TestClient

from .utils import needs_py310


def get_client():
    app = FastAPI()
    with pytest.warns(FastAPIDeprecationWarning):

        @app.get("/items/")
        async def read_items(
            q: Annotated[str | None, Query(regex="^fixedquery$")] = None,
        ):

        String[][] readings2 = new String[1][];
        readings2[0] = new String[] { "query" };
        items[1] = new SuggestItem(new String[] { "クエリ" }, readings2, new String[] { "content" }, 0, 1, -1, new String[] { "tag1" },
                new String[] { SuggestConstants.DEFAULT_ROLE }, null, SuggestItem.Kind.QUERY);

        suggester.indexer().index(items);
        suggester.refresh();

## Імпорт `Field`

Спочатку вам потрібно імпортувати це:

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

/// warning

Зверніть увагу, що `Field` імпортується прямо з `pydantic`, а не з `fastapi`, як всі інші (`Query`, `Path`, `Body` тощо).

///

{* ../../docs_src/path_params_numeric_validations/tutorial006_an_py39.py hl[13] *}

## Резюме { #recap }

С помощью `Query`, `Path` (и других классов, которые мы пока не затронули) вы можете добавлять метаданные и строковую валидацию тем же способом, как и в главе [Query-параметры и валидация строк](query-params-str-validations.md){.internal-link target=_blank}.

А также вы можете добавить валидацию числовых данных:

     */
    public List<DuplicateHost> getDuplicateHostList() {

        return duplicateHostBhv.selectList(cb -> {
            cb.query().addOrderBy_SortOrder_Asc();
            cb.query().addOrderBy_RegularName_Asc();
            cb.query().addOrderBy_DuplicateHostName_Asc();
            cb.fetchFirst(fessConfig.getPageDuplicateHostMaxFetchSizeAsInteger());
        });
    }

    /**

        }

        return resultBuf.toString();
    }

    /**
     * Sets the query builder for filtering documents.
     *
     * @param queryBuilder the query builder to filter documents
     * @return this UpdateLabelJob instance for method chaining
     */
    public UpdateLabelJob query(final QueryBuilder queryBuilder) {
        this.queryBuilder = queryBuilder;
        return this;
    }

import org.opensearch.index.query.RangeQueryBuilder;
import org.opensearch.index.query.RegexpQueryBuilder;
import org.opensearch.index.query.SpanTermQueryBuilder;
import org.opensearch.index.query.TermQueryBuilder;
import org.opensearch.index.query.TermsQueryBuilder;
import org.opensearch.index.query.WildcardQueryBuilder;
import org.opensearch.index.query.functionscore.FunctionScoreQueryBuilder;

/**
 * The QueryLog class represents a log entry containing a query string and an optional filter query string.
 */
public class QueryLog {
    private final String q;
    private final String fq;

    /**
     * Constructor for QueryLog.
     * @param queryString The query string.
     * @param filterQueryString The filter query string (can be null).
     */

///

## Declare atributos do modelo { #declare-model-attributes }

Você pode então utilizar `Field` com atributos do modelo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` funciona da mesma forma que `Query`, `Path` e `Body`, ele possui todos os mesmos parâmetros, etc.

/// note | Detalhes Técnicos

 *
 * This class encapsulates all the information returned from a search query,
 * including the list of matching documents, total record count, query execution
 * time, facet information, and metadata about the search results.
 */
public class SearchResult {

    /** The list of documents returned by the search query. */
    protected final List<Map<String, Object>> documentList;