}
                }),
            executor);

    // Pause in step 2.
    step2Waiter.awaitStarted();

    // Everything should still be open.
    assertStillOpen(closeable1, closeable2, closeable3, closeable4);

    // Cancel step 3, resume step 2, and pause in step 4.
    assertWithMessage("step3.cancel()").that(step3.cancel(false)).isTrue();
    step2Waiter.awaitReturned();

                  }
                }),
            executor);

    // Pause in step 2.
    step2Waiter.awaitStarted();

    // Everything should still be open.
    assertStillOpen(closeable1, closeable2, closeable3, closeable4);

    // Cancel step 3, resume step 2, and pause in step 4.
    assertWithMessage("step3.cancel()").that(step3.cancel(false)).isTrue();
    step2Waiter.awaitReturned();

 * is by declaring that step to be the last step of the pipeline. Nevertheless, we refer to the
 * "value" of a successful step or the "result" (value or exception) of any step.
 *
 * <ol>
 *   <li>A pipeline starts at its leaf step (or steps), which is created from either a callable
 *       block or a {@link ListenableFuture}.

          "expr": "round(sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_service=~\"$service\"}[5m])), 0.001)",
          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A",
          "step": 4
        }
      ],
      "title": "Client Request Volume",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },

          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A",
          "step": 4
        }
      ],
      "title": "Incoming Request Volume",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },

          "format": "time_series",
          "hide": false,
          "intervalFactor": 2,
          "legendFormat": "Total (k8s)",
          "refId": "A",
          "step": 2
        }
      ],
      "title": "Memory",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },

You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.

## Recap, step by step

### Step 1: import `FastAPI`

```Python hl_lines="1"
{!../../../docs_src/first_steps/tutorial001.py!}
```

`FastAPI` is a Python class that provides all the functionality for your API.

        Doc(
            """
            'Whitelist' validation step. The parameter field will be the single one
            allowed by the alias or set of aliases defined.
            """
        ),
    ] = None,
    serialization_alias: Annotated[
        Union[str, None],
        Doc(
            """
            'Blacklist' validation step. The vanilla parameter field will be the

    The `--upgrade` option tells `pip` to upgrade the packages if they are already installed.

    Because the previous step copying the file could be detected by the **Docker cache**, this step will also **use the Docker cache** when available.

## ステップ毎の要約

### Step 1: `FastAPI`をインポート

```Python hl_lines="1"
{!../../../docs_src/first_steps/tutorial001.py!}
```

`FastAPI`は、APIのすべての機能を提供するPythonクラスです。

!!! note "技術詳細"
    `FastAPI`は`Starlette`を直接継承するクラスです。

    `FastAPI`でも<a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a>のすべての機能を利用可能です。

### Step 2: `FastAPI`の「インスタンス」を生成