Pero en este caso, la misma aplicación de **FastAPI** manejará la API y la autenticación.

Así que, revisémoslo desde ese punto de vista simplificado:

* El usuario escribe el `username` y `password` en el frontend, y presiona `Enter`.
* El frontend (ejecutándose en el navegador del usuario) envía ese `username` y `password` a una URL específica en nuestra API (declarada con `tokenUrl="token"`).

            assertTrue(bytesRead > 0);
            assertEquals(numReferrals, response.getDfsResponse().getNumReferrals());
        }
    }

    @Nested
    @DisplayName("DfsResponse Getter Tests")
    class DfsResponseGetterTests {

        @Test
        @DisplayName("Should return same DfsResponse instance")
        void testGetDfsResponseReturnsSameInstance() {

Betrachten wir es also aus dieser vereinfachten Sicht:

* Der Benutzer gibt den `username` und das `password` im Frontend ein und drückt `Enter`.
* Das Frontend (das im Browser des Benutzers läuft) sendet diesen `username` und das `password` an eine bestimmte URL in unserer API (deklariert mit `tokenUrl="token"`).

Но в нашем случае одно и то же приложение **FastAPI** будет работать с API и аутентификацией.

Итак, рассмотрим его с этой упрощенной точки зрения:

* Пользователь вводит на фронтенде `имя пользователя` и `пароль` и нажимает `Enter`.
* Фронтенд (работающий в браузере пользователя) отправляет эти `имя пользователя` и `пароль` на определенный URL в нашем API (объявленный с помощью параметра `tokenUrl="token"`).

 * if (forceCacheResponse.code() != 504) {
 *   // The resource was cached! Show it.
 * } else {
 *   // The resource was not cached.
 * }
 * ```
 *
 * This technique works even better in situations where a stale response is better than no response.
 * To permit stale cached responses, use the `max-stale` directive with the maximum staleness in
 * seconds:
 *
 * ```java
 * Request request = new Request.Builder()

If you are paying for 3 servers but you are using only a little bit of their RAM and CPU, you are probably **wasting money** 💸, and probably **wasting server electric power** 🌎, etc.

In that case, it could be better to have only 2 servers and use a higher percentage of their resources (CPU, memory, disk, network bandwidth, etc).

                    "Should throw DcerpcException for missing endpoint");
        }
    }

    @Nested
    @DisplayName("Getter Method Tests")
    class GetterTests {

        @Test
        @DisplayName("Should return correct transport context")
        void testGetTransportContext() throws Exception {

        when(response.getCommand()).thenReturn(command);
        response.setCommand(command);
        assertEquals(command, response.getCommand());

        // Test other setter methods
        doNothing().when(response).setUid(1000);
        response.setUid(1000);
        verify(response).setUid(1000);

        doNothing().when(response).setExtendedSecurity(true);

        // snapshot timestamp, or some other timestamp later encoded into the metadata.
        // TODO this needs to be repeated here so the merging doesn't interfere with the written metadata
        //  - we'd be much better having a pristine input, and an ongoing metadata for merging instead

        Map<ArtifactRepository, Metadata> previousMetadata = new HashMap<>();
        ArtifactRepository selected = null;

        assertEquals("In progress", statusMap.get(CrawlerStatus.RUNNING));
        assertEquals("Completed", statusMap.get(CrawlerStatus.DONE));

        // Test with EnumMap for better performance
        java.util.EnumMap<CrawlerStatus, String> enumMap = new java.util.EnumMap<>(CrawlerStatus.class);
        enumMap.put(CrawlerStatus.INITIALIZING, "Init");
        enumMap.put(CrawlerStatus.RUNNING, "Run");