* REST-Backend-Tests basierend auf **Pytest**, integriert in Docker, sodass Sie die vollständige API-Interaktion unabhängig von der Datenbank testen können. Da es in Docker ausgeführt wird, kann jedes Mal ein neuer Datenspeicher von Grund auf erstellt werden (Sie können also ElasticSearch, MongoDB, CouchDB oder was auch immer Sie möchten verwenden und einfach testen, ob die API funktioniert).

    !!! tip
        Prefer to use the `Annotated` version if possible.

    ```Python
    {!> ../../../docs_src/app_testing/app_b/main.py!}
    ```

### Extended testing file

You could then update `test_main.py` with the extended tests:

```Python
{!> ../../../docs_src/app_testing/app_b/test_main.py!}
```

Konkret geht es darum, Uvicorn, Starlette und FastAPI miteinander zu vergleichen (neben vielen anderen Tools).

Je einfacher das Problem, welches durch das Tool gelöst wird, desto besser ist die Performanz. Und die meisten Benchmarks testen nicht die zusätzlichen Funktionen, welche das Tool bietet.

Die Hierarchie ist wie folgt:

* **Uvicorn**: ein ASGI-Server
    * **Starlette**: (verwendet Uvicorn) ein Web-Mikroframework

You could want to set up a different database for testing, rollback the data after the tests, pre-fill it with some testing data, etc.

The main idea is exactly the same you saw in that previous chapter.

## Add tests for the SQL app

# 测试事件：启动 - 关闭

使用 `TestClient` 和 `with` 语句，在测试中运行事件处理器（`startup` 与 `shutdown`）。

```Python hl_lines="9-12  20-24"
{!../../../docs_src/app_testing/tutorial003.py!}

      - name: Install Dependencies
        if: steps.cache.outputs.cache-hit != 'true'
        run: pip install -r requirements-tests.txt
      - name: Install Pydantic v2
        run: pip install "pydantic>=2.0.2,<3.0.0"
      - name: Lint
        run: bash scripts/lint.sh

  test:
    runs-on: ubuntu-latest
    strategy:

from docs_src.additional_responses.tutorial002 import app

client = TestClient(app)


def test_path_operation():
    response = client.get("/items/foo")
    assert response.status_code == 200, response.text
    assert response.json() == {"id": "foo", "value": "there goes my hero"}


def test_path_operation_img():
    shutil.copy("./docs/en/docs/img/favicon.png", "./image.png")

from docs_src.additional_responses.tutorial003 import app

client = TestClient(app)


def test_path_operation():
    response = client.get("/items/foo")
    assert response.status_code == 200, response.text
    assert response.json() == {"id": "foo", "value": "there goes my hero"}


def test_path_operation_not_found():
    response = client.get("/items/bar")
    assert response.status_code == 404, response.text

        ("/elements/", 200, [{"item_id": "Foo"}]),
    ],
)
def test_query_params_str_validations(path, expected_status, expected_response):
    response = client.get(path)
    assert response.status_code == expected_status
    assert response.json() == expected_response


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

            200,
            {"X-Token values": ["foo", "bar"]},
        ),
    ],
)
def test(path, headers, expected_status, expected_response):
    response = client.get(path, headers=headers)
    assert response.status_code == expected_status
    assert response.json() == expected_response


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200