@Test
  fun toJavaNetUrl() {
    val httpUrl = "http://username:password@host/path?query#fragment".toHttpUrl()
    val javaNetUrl = httpUrl.toUrl()
    assertThat(javaNetUrl.toString())
      .isEqualTo("http://username:password@host/path?query#fragment")
  }

  @Test
  fun toUri() {
    val httpUrl = "http://username:password@host/path?query#fragment".toHttpUrl()
    val uri = httpUrl.toUri()
    assertThat(uri.toString())

 *
 * 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;

		xhttp.AmzSignature,
	)

	// Add missing query parameters if any provided in the request URL
	for k, v := range req.Form {
		if !defaultSigParams.Contains(k) {
			query[k] = v
		}
	}

	// Get the encoded query.
	encodedQuery := query.Encode()

	// Verify if date query is same.
	if req.Form.Get(xhttp.AmzDate) != query.Get(xhttp.AmzDate) {
		return ErrSignatureDoesNotMatch
	}

## 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).

///

     *
     * @param query the search query string
     * @param params search request parameters including pagination and filters
     * @param userBean optional user information for personalized search
     * @return list of search result documents with fused ranking scores
     */
    public List<Map<String, Object>> search(final String query, final SearchRequestParams params,

# 💪 - 💗 🔢

🔜 👈 👥 ✔️ 👀 ❔ ⚙️ `Path` & `Query`, ➡️ 👀 🌅 🏧 ⚙️ 📨 💪 📄.

## 🌀 `Path`, `Query` & 💪 🔢

🥇, ↗️, 👆 💪 🌀 `Path`, `Query` & 📨 💪 🔢 📄 ➡ & **FastAPI** 🔜 💭 ⚫️❔.

& 👆 💪 📣 💪 🔢 📦, ⚒ 🔢 `None`:

{* ../../docs_src/body_multiple_params/tutorial001.py hl[19:21] *}

/// note

👀 👈, 👉 💼, `item` 👈 🔜 ✊ ⚪️➡️ 💪 📦. ⚫️ ✔️ `None` 🔢 💲.

///

## 💗 💪 🔢

        String query = "test query";
        SearchRequestParams params = createTestSearchRequestParams();
        OptionalThing<FessUserBean> userBean = OptionalThing.empty();

        SearchResult result = testSearcher.search(query, params, userBean);

        assertNotNull(result);
        assertEquals(query, testSearcher.lastQuery);

`Field`는 `Query`, `Path`와 `Body`와 같은 방식으로 동작하며, 모두 같은 매개변수들 등을 가집니다.

/// note | 기술적 세부사항

실제로 `Query`, `Path`등, 여러분이 앞으로 볼 다른 것들은 공통 클래스인 `Param` 클래스의 서브클래스 객체를 만드는데, 그 자체로 Pydantic의 `FieldInfo` 클래스의 서브클래스입니다.

그리고 Pydantic의 `Field` 또한 `FieldInfo`의 인스턴스를 반환합니다.

`Body` 또한 `FieldInfo`의 서브클래스 객체를 직접적으로 반환합니다. 그리고 `Body` 클래스의 서브클래스인 것들도 여러분이 나중에 보게될 것입니다.

import org.opensearch.core.action.ActionListener;
import org.opensearch.index.query.BoolQueryBuilder;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryBuilders;
import org.opensearch.index.query.functionscore.FunctionScoreQueryBuilder;
import org.opensearch.index.query.functionscore.ScoreFunctionBuilders;
import org.opensearch.search.SearchHit;

{"attributes":{"description":"","kibanaSavedObjectMeta":{"searchSourceJSON":"{\"query\":{\"query\":\"\",\"language\":\"kuery\"},\"filter\":[],\"indexRefName\":\"kibanaSavedObjectMeta.searchSourceJSON.index\"}"},"title":"search-query-counts-per-sec","uiStateJSON":"{}","version":1,"visState":"{\"title\":\"search-query-counts-per-sec\",\"type\":\"histogram\",\"params\":{\"type\":\"histogram\",\"grid\":{\"categoryLines\":false},\"categoryAxes\":[{\"...