labels.search_result_sort_click_count_asc=par nombre de clics (asc)
labels.search_result_sort_click_count_desc=par nombre de clics (desc)
labels.search_result_sort_favorite_count_asc=par nombre de favoris (asc)
labels.search_result_sort_favorite_count_desc=par nombre de favoris (desc)
labels.search_result_sort_multiple=Multiple
labels.search_result_size={0} octets
labels.search_result_created=Créé :
labels.search_result_last_modified=Dernière modification :

labels.search_result_sort_click_count_asc=Klikken (oplopend)
labels.search_result_sort_click_count_desc=Klikken (aflopend)
labels.search_result_sort_favorite_count_asc=Favorieten (oplopend)
labels.search_result_sort_favorite_count_desc=Favorieten (aflopend)
labels.search_result_sort_multiple=Meerdere
labels.search_result_size={0} bytes
labels.search_result_created=Registratiedatum:

indexer.unprocessed.document.size=1000
# Whether to enable click count tracking in the indexer.
indexer.click.count.enabled=true
# Whether to enable favorite count tracking in the indexer.
indexer.favorite.count.enabled=true
# Commit margin time (ms) for webfs in the indexer.
indexer.webfs.commit.margin.time=5000
# Maximum number of empty lists for webfs in the indexer.

    @Resource
    protected HttpServletRequest request;

    /** Flag indicating whether search logging is enabled. */
    protected boolean searchLogSupport;

    /** Flag indicating whether favorite functionality is enabled. */
    protected boolean favoriteSupport;

    /** Flag indicating whether thumbnail generation is enabled. */
    protected boolean thumbnailSupport;

    /**

    /** Property key for user information configuration. */
    public static final String USER_INFO_PROPERTY = "user.info";

    /** Property key for user favorite functionality configuration. */
    public static final String USER_FAVORITE_PROPERTY = "user.favorite";

    /** Property key for search log configuration. */
    public static final String SEARCH_LOG_PROPERTY = "search.log";

Você também pode devolver modelos Pydantic ( você verá mais sobre isso mais tarde).

Existem muitos outros objetos e modelos que serão convertidos automaticamente para JSON (incluindo ORMs, etc). Tente usar seus favoritos, é altamente provável que já sejam compatíveis.

### Passo 6: Faça o deploy { #step-6-deploy-it }

También puedes retornar modelos de Pydantic (verás más sobre eso más adelante).

Hay muchos otros objetos y modelos que serán automáticamente convertidos a JSON (incluyendo ORMs, etc). Intenta usar tus favoritos, es altamente probable que ya sean compatibles.

### Paso 6: Despliégalo { #step-6-deploy-it }

You can also return Pydantic models (you'll see more about that later).

There are many other objects and models that will be automatically converted to JSON (including ORMs, etc). Try using your favorite ones, it's highly probable that they are already supported.

### Step 6: Deploy it { #step-6-deploy-it }

Vous pouvez aussi retourner des models **Pydantic** (qui seront détaillés plus tard).

Il y a de nombreux autres objets et modèles qui seront automatiquement convertis en JSON. Essayez d'utiliser vos favoris, il est fort probable qu'ils soient déjà supportés.

## Récapitulatif

* Importez `FastAPI`.
* Créez une instance d'`app`.
* Ajoutez une **décorateur d'opération de chemin** (tel que `@app.get("/")`).

                        breakCursor = true;
                    }
                }
            });
        };
    }

    /**
     * Get the write call for favorite log ndjson.
     * @return The write call.
     */
    public static Consumer<Writer> getFavoriteLogNdjsonWriteCall() {
        final FessConfig fessConfig = ComponentUtil.getFessConfig();