Variadic<TFTensorType>:$results
  );

  let assemblyFormat = "attr-dict `:` type($results)";
}

def AwaitOp: TensorflowMlrt_Op<"await", [Pure]> {
  let summary = "Await a tensor from a !mlrt.future";

  let description = [{
    Await a tensor from a !mlrt.future.

    $future: A value of type !mlrt.future. The underlying value must be a tensorflow tensor.

    $result: a tensorflow tensor.

    **FastAPI** provides the same `WebSocket` directly just as a convenience for you, the developer. But it comes directly from Starlette.

## Await for messages and send messages

In your WebSocket route you can `await` for messages and send messages.

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

You can receive and send binary, text, and JSON data.

                functionBlocking.await();
                return immediateFuture(null);
              }
            });

    ExecutorService executor = Executors.newSingleThreadExecutor();
    try {
      ListenableFuture<?> output =
          Futures.transformAsync(immediateFuture(null), function, executor);
      functionCalled.await();
      assertThat(output.toString()).contains(function.toString());

                functionBlocking.await();
                return immediateFuture(null);
              }
            });

    ExecutorService executor = Executors.newSingleThreadExecutor();
    try {
      ListenableFuture<?> output =
          Futures.transformAsync(immediateFuture(null), function, executor);
      functionCalled.await();
      assertThat(output.toString()).contains(function.toString());

// used during parallelization and has no runtime implementation.
def TFAwaitOp: TensorflowMlrt_Op<"tf_await", [Pure, TFRT_CostFunctionInterface, TFRT_FixedCost<1>]> {
  let summary = "Await a tensor from a !mlrt.future";

  let description = [{
    Await a tensor from a !mlrt.future.

    $future: A value of type !mlrt.future. The underlying value must be a tensorflow tensor.

    $result: a tensorflow tensor.
  }];

        val problem = Any()
        val results = Collections.synchronizedList(mutableListOf<Boolean>())

        fun doTest() {
            reporting.enterDynamicCall(this)
            latch.countDown()
            latch.await()
            results += reporting.unreportedProblemInCurrentCall(problem)
        }

        (1..3).map { thread { doTest() } }.forEach(Thread::join)
        assertEquals(listOf(true, true, true), results)
    }

  // Space for returned values.
  llvm::SmallVector<RCReference<AsyncValue>> results(compute->num_results());

  compute->Execute(*exec_ctx_, exec_arguments, results);

  // Wait for the function execution to finish, as well as the side-effects.
  host_context_->Await(results);

  // Check that all results are available.
  llvm::SmallVector<Tensor> ret_values;
  for (unsigned i = 1; i < results.size(); ++i) {

    dependencies { testImplementation 'junit:junit:4.13' }

    test {
        doFirst {
            println path + " waiting for other tests..."
            latch.countDown()
            latch.await()
            println path + " go"
        }

        executable = "$java"
    }
}
"""
        subprojects.each { subproject ->
            settingsFile << "include '$subproject'\n"

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

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

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

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

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

!!! info "说明"

    `open()` 函数中，`mode="a"` 指的是**追加**。因此这行文本会添加在文件已有内容之后，不会覆盖之前的内容。

!!! tip "提示"

    注意，本例使用 Python `open()` 标准函数与文件交互。

    这个函数执行 I/O（输入/输出）操作，需要等待内容写进磁盘。

    但 `open()` 函数不支持使用 `async` 与 `await`。

    因此，声明事件处理函数要使用 `def`，不能使用 `asnyc def`。

!!! info "说明"