}

    /**
     * Converts the given object to a {@link Date}.
     *
     * @param src
     *            The source object to convert.
     * @return The converted {@link Date}.
     */
    public static Date toDate(final Object src) {
        return toDate(src, null, LocaleUtil.getDefault());
    }

    /**
     * Converts the given object to a {@link Date}.
     *

* `frozenset`:
    * In requests and responses, treated the same as a `set`:
        * In requests, a list will be read, eliminating duplicates and converting it to a `set`.
        * In responses, the `set` will be converted to a `list`.
        * The generated schema will specify that the `set` values are unique (using JSON Schema's `uniqueItems`).
* `bytes`:
    * Standard Python `bytes`.

     * @return the converted {@link Date}
     */
    public static Date toDate(final Object src, final String pattern) {
        return toDate(src, pattern, LocaleUtil.getDefault());
    }

    /**
     * Converts an object to {@link Date}.
     *
     * @param src the source object
     * @param locale the locale (must not be {@literal null})
     * @return the converted {@link Date}
     */

    }

    @GwtIncompatible @J2ktIncompatible private static final long serialVersionUID = 1;
  }

  /**
   * Returns a serializable converter object that converts between strings and shorts using {@link
   * Short#decode} and {@link Short#toString()}. The returned converter throws {@link
   * NumberFormatException} if the input string is invalid.
   *

Você não conseguiria este tipo de suporte de editor se estivesse trabalhando diretamente com `dict` em vez de modelos Pydantic.

Mas você também não precisa se preocupar com eles, os dicts de entrada são convertidos automaticamente e sua saída é convertida automaticamente para JSON também.

## Corpos de `dict`s arbitrários { #bodies-of-arbitrary-dicts }

Você também pode declarar um corpo como um `dict` com chaves de algum tipo e valores de outro tipo.

import org.opensearch.search.SearchHit;

/**
 * Utility class for search engine operations and content formatting.
 * Provides helper methods for working with XContent builders, scrolling through search results,
 * and converting XContent objects to different output formats.
 */
public final class SearchEngineUtil {

    private static final Logger logger = LogManager.getLogger(SearchEngineUtil.class);

    /**

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.

    FastAPI is still capable of <dfn title="converting the data to a format that can be transmitted">serializing</dfn> the data to JSON.

7. Here the `response_model` is using a type annotation of a list of `Author` dataclasses.

    }

    @GwtIncompatible @J2ktIncompatible private static final long serialVersionUID = 1;
  }

  /**
   * Returns a serializable converter object that converts between strings and integers using {@link
   * Integer#decode} and {@link Integer#toString()}. The returned converter throws {@link
   * NumberFormatException} if the input string is invalid.
   *

a `response_class` with a JSON media type (`application/json`), like is the case with the `JSONResponse`, the data you return will be automatically converted (and filtered) with any Pydantic `response_model` that you declared in the *path operation decorator*. But the data won't be serialized to JSON bytes with Pydantic, instead it will be converted with the `jsonable_encoder` and then passed to the `JSONResponse` class, which will serialize it to bytes using the standard JSON library in Python....

        };
        request.setReadingConverter(converter);

        QueryBuilder result = request.buildQuery("test", Collections.emptyList());
        assertNotNull(result);

        String queryString = result.toString();
        // Should have both readings
        assertTrue("Should contain original text", queryString.contains("test"));
        assertTrue("Should contain converted reading", queryString.contains("test_reading"));
    }