* <li>{@link #badWords} - List of bad words.
 * <li>{@link #parallel} - Flag for parallel processing.
 * <li>{@link #readingConverter} - Reading converter.
 * <li>{@link #contentsReadingConverter} - Contents reading converter.
 * <li>{@link #normalizer} - Normalizer.
 * <li>{@link #analyzer} - Suggest analyzer.
 * <li>{@link #contentsParser} - Contents parser.
 * <li>{@link #suggestWriter} - Suggest writer.

        // Test creating default reading converter
        ReadingConverter converter = SuggestUtil.createDefaultReadingConverter(client, settings);
        assertNotNull(converter);
    }

    @Test
    public void testCreateDefaultContentsReadingConverter() {
        // Test creating default contents reading converter
        ReadingConverter converter = SuggestUtil.createDefaultContentsReadingConverter(client, settings);

        return sb.toString();
    }

    /**
     * Checks if the client is connected to the witness service.
     *
     * @return true if connected
     */
    public boolean isConnected() {
        return connected && rpcHandle != null;
    }

    @Override
    public void close() {
        if (connected && rpcHandle != null) {
            try {

Então, mesmo com o código acima que não usa Pydantic explicitamente, o FastAPI está usando Pydantic para converter essas dataclasses padrão para a versão do Pydantic.

E claro, ele suporta o mesmo:

* validação de dados
* serialização de dados
* documentação de dados, etc.

  }

  /**
   * Returns a serializable {@code Converter} that converts strings from this format to {@code
   * targetFormat}.
   *
   * @since 16.0
   */
  public Converter<String, String> converterTo(CaseFormat targetFormat) {
    return new StringConverter(this, targetFormat);
  }

  private static final class StringConverter extends Converter<String, String>
      implements Serializable {

      T defaultType = (T) getFirstTypeParameter(type.getType());
      return defaultType;
    }
    if (type.getRawType() == Converter.class) {
      TypeToken<?> convertFromType = type.resolveType(Converter.class.getTypeParameters()[0]);
      TypeToken<?> convertToType = type.resolveType(Converter.class.getTypeParameters()[1]);
      @SuppressWarnings("unchecked") // returns default for both F and T

- The `EndpointSlice` API is now GA. The `EndpointSlice` topology field has been removed from the GA API and will be replaced by a new per Endpoint Zone field. If the topology field was previously used, it will be converted into an annotation in the v1 Resource. The `discovery.k8s.io/v1alpha1` API is removed. ([#99662](https://github.com/kubernetes/kubernetes/pull/99662), [@swetharepakula](https://github.com/swetharepakula))

- The systemd config files are now reloaded before kubelet starts, so changes can take effect([#65702](https://github.com/kubernetes/kubernetes/pull/65702), [@mborsz](https://github.com/mborsz))
- Hostnames are now converted to lowercase before being used for node lookups in the kubernetes-worker charm. ([#65487](https://github.com/kubernetes/kubernetes/pull/65487), [@dshcherb](https://github.com/dshcherb))

Mas se o dado não existir, você quer criá-lo e retornar um código de status HTTP de "CREATED" `201`.

Mas você ainda quer ser capaz de filtrar e converter o dado que você retornará com um `response_model`.

Para estes casos, você pode utilizar um parâmetro `Response`.

## Use um parâmetro `Response`

    assertEvents(
      "plan 1 TCP connected",
      "plan 0 cancel",
      "plan 1 TLS connecting...",
      "plan 1 TLS connected",
      "plan 2 TCP connecting...",
    )

    taskFaker.advanceUntil(270.ms)
    assertEvents(
      "plan 0 TCP connect canceled",
    )

    taskFaker.advanceUntil(280.ms)
    assertEvents(
      "plan 2 TCP connected",
      "plan 2 TLS connecting...",