app.include_router(router)


client = TestClient(app)


def test_a():
    response = client.get("/a")
    assert response.status_code == 200, response.text
    assert response.json() == "a"


def test_b():
    response = client.get("/b")
    assert response.status_code == 200, response.text
    assert response.json() == "b"


def test_c():
    response = client.get("/c")

        assertTrue(result.isPresent(), "Expected " + result + ".isPresent() to return true");
        assertEquals(asList("test:B", "test:D"), result.get().getRemainingProjects());
    }

    private MavenProject createMavenProject(String artifactId) {
        MavenProject project = new MavenProject();
        project.setGroupId("test");
        project.setArtifactId(artifactId);
        return project;
    }

And it will be annotated / documented accordingly too.

## Nested Models { #nested-models }

Each attribute of a Pydantic model has a type.

But that type can itself be another Pydantic model.

So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.

All that, arbitrarily nested.

### Define a submodel { #define-a-submodel }

    tester = new ListenableFutureTester(future);
    tester.setUp();
  }

  public void testDefaultState() throws Exception {
    assertThrows(TimeoutException.class, () -> future.get(5, MILLISECONDS));
  }

  public void testSetValue() throws Exception {
    assertTrue(future.set("value"));
    tester.testCompletedFuture("value");
  }

  public void testSetFailure() throws Exception {

# Body – Verschachtelte Modelle { #body-nested-models }

Mit **FastAPI** können Sie (dank Pydantic) beliebig tief verschachtelte Modelle definieren, validieren, dokumentieren und verwenden.

## Listen als Felder { #list-fields }

Sie können ein Attribut als Kindtyp definieren, zum Beispiel eine Python-`list`.

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

  "version": "1.0",
  "published": "2025-01-15",
  "tags": ["crawler", "extractor", "json"],
  "content": {
    "summary": "This is a sample JSON document for testing",
    "body": "The extractor should handle nested objects and arrays properly"
  },
  "metadata": {
    "created_at": "2025-01-01T00:00:00Z",
    "updated_at": "2025-01-15T12:00:00Z"
  }

# Cuerpo - Modelos Anidados { #body-nested-models }

Con **FastAPI**, puedes definir, validar, documentar y usar modelos anidados de manera arbitraria (gracias a Pydantic).

## Campos de lista { #list-fields }

Puedes definir un atributo como un subtipo. Por ejemplo, una `list` en Python:

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

Esto hará que `tags` sea una lista, aunque no declare el tipo de los elementos de la lista.

# Corpo - Modelos aninhados { #body-nested-models }

Com o **FastAPI**, você pode definir, validar, documentar e usar modelos arbitrariamente e profundamente aninhados (graças ao Pydantic).

## Campos do tipo Lista { #list-fields }

Você pode definir um atributo como um subtipo. Por exemplo, uma `list` do Python:

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

    }

    @Nested
    @DisplayName("Modification Behavior")
    class ModificationBehaviorTests {

        @Test
        @DisplayName("should not save modifications to disk")
        void shouldNotSaveModificationsToDisk() {
            assertFalse(checkGoal.shouldSaveModifications(), "Check goal should not save modifications to disk");
        }
    }

    @Nested
    @DisplayName("Execution")

    }

    @Nested
    @DisplayName("Modification Behavior")
    class ModificationBehaviorTests {

        @Test
        @DisplayName("should save modifications to disk")
        void shouldSaveModificationsToDisk() {
            assertTrue(applyGoal.shouldSaveModifications(), "Apply goal should save modifications to disk");
        }
    }

    @Nested
    @DisplayName("Execution")