'input_tensor': np.random.uniform(low=-1.0, high=1.0, size=(1, 4))
        }

    repr_ds = data_gen()
    self.assertIsNone(repr_dataset.get_num_samples(repr_ds))

    # Make sure that the __next__() is never called during the
    # get_num_samples call.
    self.assertLen(list(repr_ds), num_samples)

  def test_get_num_samples_returns_none_when_len_raises_error(self):
    class LenRaisingError:

     * Wait for the interrupting thread to set DONE. (See interruptTask().) We want to wait so that
     * the interrupting thread doesn't interrupt the _next_ thing to run on this thread.
     *
     * Note: We don't reset the interrupted bit, just wait for it to be set. If this is a thread
     * pool thread, the thread pool will reset it for us. Otherwise, the interrupted bit may have

     * Wait for the interrupting thread to set DONE. (See interruptTask().) We want to wait so that
     * the interrupting thread doesn't interrupt the _next_ thing to run on this thread.
     *
     * Note: We don't reset the interrupted bit, just wait for it to be set. If this is a thread
     * pool thread, the thread pool will reset it for us. Otherwise, the interrupted bit may have

In Python können Sie Kontextmanager erstellen, indem Sie <a href="https://docs.python.org/3/reference/datamodel.html#context-managers" class="external-link" target="_blank">eine Klasse mit zwei Methoden erzeugen: `__enter__()` und `__exit__()`</a>.

Sie können solche auch innerhalb von **FastAPI**-Abhängigkeiten mit `yield` verwenden, indem Sie `with`- oder `async with`-Anweisungen innerhalb der Abhängigkeits-Funktion verwenden:

```Python hl_lines="1-9  13"

В Python для создания менеджеров контекста можно <a href="https://docs.python.org/3/reference/datamodel.html#context-managers" class="external-link" target="_blank">создать класс с двумя методами: `__enter__()` и `__exit__()`</a>.

Вы также можете использовать их внутри зависимостей **FastAPI** с `yield`, используя операторы
`with` или `async with` внутри функции зависимости:

```Python hl_lines="1-9  13"

In Python, you can create Context Managers by <a href="https://docs.python.org/3/reference/datamodel.html#context-managers" class="external-link" target="_blank">creating a class with two methods: `__enter__()` and `__exit__()`</a>.

You can also use them inside of **FastAPI** dependencies with `yield` by using
`with` or `async with` statements inside of the dependency function:

```Python hl_lines="1-9  13"

!!! warning
    这是一个更为“高级”的想法。

    如果您刚开始使用**FastAPI**，您可能暂时可以跳过它。

在Python中，你可以通过<a href="https://docs.python.org/3/reference/datamodel.html#context-managers" class="external-link" target="_blank">创建一个带有`__enter__()`和`__exit__()`方法的类</a>来创建上下文管理器。

你也可以在**FastAPI**的依赖项中使用带有`yield`的`with`或`async with`语句，通过在依赖函数内部使用它们。

```Python hl_lines="1-9  13"
{!../../../docs_src/dependencies/tutorial010.py!}
```

!!! tip

    **FastAPI** を使い始めたばかりの方は、とりあえずスキップした方がよいかもしれません。

Pythonでは、<a href="https://docs.python.org/3/reference/datamodel.html#context-managers" class="external-link" target="_blank">以下の２つのメソッドを持つクラスを作成する: `__enter__()`と`__exit__()`</a>ことでコンテキストマネージャを作成することができます。

また、依存関数の中で`with`や`async with`文を使用することによって`yield`を持つ **FastAPI** の依存関係の中でそれらを使用することができます:

```Python hl_lines="1 2 3 4 5 6 7 8 9 13"
{!../../../docs_src/dependencies/tutorial010.py!}

   * done in the meantime instead of waiting idly.
   *
   * This has important consequences: it means that the RateLimiter doesn't remember the time of the
   * _last_ request, but it remembers the (expected) time of the _next_ request. This also enables
   * us to tell immediately (see tryAcquire(timeout)) whether a particular timeout is enough to get
   * us to the point of the next scheduling time, since we always maintain that. And what we mean by

   * done in the meantime instead of waiting idly.
   *
   * This has important consequences: it means that the RateLimiter doesn't remember the time of the
   * _last_ request, but it remembers the (expected) time of the _next_ request. This also enables
   * us to tell immediately (see tryAcquire(timeout)) whether a particular timeout is enough to get
   * us to the point of the next scheduling time, since we always maintain that. And what we mean by