Você pode definir parâmetros de Cabeçalho da mesma maneira que define paramêtros com `Query`, `Path` e `Cookie`.

## importe `Header`

Primeiro importe `Header`:

{* ../../docs_src/header_params/tutorial001_py310.py hl[1] *}

## Declare parâmetros de `Header`

Então declare os paramêtros de cabeçalho usando a mesma estrutura que em `Path`, `Query` e `Cookie`.

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;

     *
     * @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,

## Importe `Field`

Primeiro, você tem que importá-lo:

{* ../../docs_src/body_fields/tutorial001.py hl[4] *}

/// warning | Aviso

Note que `Field` é importado diretamente do `pydantic`, não do `fastapi` como todo o resto (`Query`, `Path`, `Body`, etc).

///

        QueryContext context = new QueryContext("*:*", false);
        MatchAllDocsQuery query = new MatchAllDocsQuery();
        float boost = 1.0f;

        QueryBuilder result = matchAllQueryCommand.execute(context, query, boost);

        assertNotNull(result);
        assertTrue(result instanceof MatchAllQueryBuilder);

        // Verify the query builder generates correct JSON

{
    "properties": {
      "urlId": {
        "type": "keyword"
      },
      "docId": {
        "type": "keyword"
      },
      "queryId": {
        "type": "keyword"
      },
      "userSessionId": {
        "type": "keyword"
      },
      "url": {
        "type": "keyword"
      },
      "order": {
        "type": "integer"
      },
      "requestedAt": {
        "type": "date",

# 💪 - 💗 🔢

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

## 🌀 `Path`, `Query` & 💪 🔢

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

& 👆 💪 📣 💪 🔢 📦, ⚒ 🔢 `None`:

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

/// note

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

///

## 💗 💪 🔢

## 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).

///

 *
 * 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;

                "Unknown q: " + query.getClass() + " => " + query);
    }

    /**
     * Converts a wildcard query to an appropriate OpenSearch QueryBuilder.
     *
     * @param context The query context containing field and search information
     * @param wildcardQuery The Lucene wildcard query to convert
     * @param boost The boost factor to apply to the query
     * @return The converted OpenSearch QueryBuilder