// SequentialExecutor by the time the barrier is satisfied
      barrier.await(1, SECONDS);
      executor.execute(barrierTask);
      // timeout means the second task wasn't even tried
      barrier.await(1, SECONDS);
    } finally {
      service.shutdown();
    }
  }

  public void testRejectedExecutionThrownWithMultipleCalls() throws Exception {

```Python
with open("file.txt") as file:
    file.read()
```

⏮️ ⏬ 🐍, 📤 **🔁 🔑 👨‍💼**. 👆 🔜 ⚙️ ⚫️ ⏮️ `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

🕐❔ 👆 ✍ 🔑 👨‍💼 ⚖️ 🔁 🔑 👨‍💼 💖 🔛, ⚫️❔ ⚫️ 🔨 👈, ⏭ 🛬 `with` 🍫, ⚫️ 🔜 🛠️ 📟 ⏭ `yield`, & ⏮️ ❎ `with` 🍫, ⚫️ 🔜 🛠️ 📟 ⏮️ `yield`.

👆 📟 🖼 🔛, 👥 🚫 ⚙️ ⚫️ 🔗, ✋️ 👥 🚶‍♀️ ⚫️ FastAPI ⚫️ ⚙️ ⚫️.

            })
        .start();

    // wait for the computingEntry to be created
    computationStarted.await();
    cache.invalidateAll();
    // let the computation proceed
    computingLatch.countDown();
    // don't check cache.size() until we know the get("b") call is complete
    computationComplete.await();

    // At this point, the listener should be holding the seed value (a -> a), and the map should

    legacy_request_state_context_var.reset(contextvar_token)


@app.middleware("http")
async def custom_middleware(
    request: Request, call_next: Callable[[Request], Awaitable[Response]]
):
    response = await call_next(request)
    response.headers["custom"] = "foo"
    return response


@app.get("/user", dependencies=[Depends(set_up_request_state_dependency)])
def get_user():

        .build()
    }
    val request =
      Request.Builder()
        .url(server.url("/"))
        .build()
    client.newCall(request).enqueue(callback)
    callback.await(request.url)
      .assertCode(200)
      .assertHeader("OkHttp-Intercepted", "yep")
  }

  @Test
  fun applicationInterceptorsCanMakeMultipleRequestsToServer() {

```

/// note | "技术细节"

您也可以使用 `from starlette.websockets import WebSocket`。

**FastAPI** 直接提供了相同的 `WebSocket`，只是为了方便开发人员。但它直接来自 Starlette。

///

## 等待消息并发送消息

在您的 WebSocket 路由中，您可以使用 `await` 等待消息并发送消息。

```Python hl_lines="48-52"
{!../../docs_src/websockets/tutorial001.py!}
```

您可以接收和发送二进制、文本和 JSON 数据。

## 尝试一下

如果您的文件名为 `main.py`，请使用以下命令运行应用程序：

```console

    (this as Object).notifyAll()
  }

  /**
   * Returns the recorded response triggered by `request`. Throws if the response isn't
   * enqueued before the timeout.
   */
  @Synchronized
  fun await(url: HttpUrl): RecordedResponse {
    val timeoutMillis = TimeUnit.NANOSECONDS.toMillis(System.nanoTime()) + TIMEOUT_MILLIS
    while (true) {
      val i = responses.iterator()
      while (i.hasNext()) {

with open("file.txt") as file:
    file.read()
```

Nas versões mais recentes de Python, há também um **gerenciador de contexto assíncrono**. Você o usaria com `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

```Python
with open("file.txt") as file:
    file.read()
```

In recent versions of Python, there's also an **async context manager**. You would use it with `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

///

/// tip | "팁"

이 예제에서는 파일과 상호작용 하기 위해 파이썬 표준 함수인 `open()`을 사용하고 있습니다.

따라서 디스크에 데이터를 쓰기 위해 "대기"가 필요한 I/O (입력/출력) 작업을 수행합니다.

그러나 `open()`은 `async`와 `await`을 사용하지 않기 때문에 이벤트 핸들러 함수는 `async def`가 아닌 표준 `def`로 선언하고 있습니다.

///

/// info | "정보"

이벤트 핸들러에 관한 내용은 <a href="https://www.starlette.io/events/" class="external-link" target="_blank">Starlette 이벤트 문서</a>에서 추가로 확인할 수 있습니다.