We also saw that HTTPS is normally provided by a component **external** to your application server, a **TLS Termination Proxy**.

And there has to be something in charge of **renewing the HTTPS certificates**, it could be the same component or it could be something different.

### Example Tools for HTTPS

Some of the tools you could use as a TLS Termination Proxy are:

* Traefik

#
# Windows-specific utilities.
#

# Docker on Windows has difficulty using volumes other than C:\, when it comes
# to setting up up volume mappings.
# Thus, the drive letter is replaced with C:\, in case it's
# something else (ex. T:), which is frequently the case inside Kokoro jobs.
function replace_drive_letter_with_c () {
  sed -E "s|^[a-zA-Z]:|C:|g" <<< $1

    assertEquals(
        "text/plain; something=\"cr@zy\"; something-else=\"crazy with spaces\";"
            + " and-another-thing=\"\"; normal-thing=foo",
        MediaType.create("text", "plain")
            .withParameter("something", "cr@zy")
            .withParameter("something-else", "crazy with spaces")
            .withParameter("and-another-thing", "")

A "**callable**" in Python is anything that Python can "call" like a function.

So, if you have an object `something` (that might _not_ be a function) and you can "call" it (execute it) like:

```Python
something()
```

or

```Python
something(some_argument, some_keyword_argument="foo")
```

then it is a "callable".

## Classes as dependencies

到目前为止，您看到的依赖项都被声明为函数。

但这并不是声明依赖项的唯一方法(尽管它可能是更常见的方法)。

关键因素是依赖项应该是 "可调用对象"。

Python 中的 "**可调用对象**" 是指任何 Python 可以像函数一样 "调用" 的对象。

所以，如果你有一个对象 `something` (可能*不是*一个函数)，你可以 "调用" 它(执行它)，就像：

```Python
something()
```

或者

```Python
something(some_argument, some_keyword_argument="foo")
```

这就是 "可调用对象"。

## 类作为依赖项

您可能会注意到，要创建一个 Python 类的实例，您可以使用相同的语法。

举个例子:

```Python

def test_get_exception():
    response = client.get("/unicorns/yolo")
    assert response.status_code == 418, response.text
    assert response.json() == {
        "message": "Oops! yolo did something. There goes a rainbow..."
    }


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

   * String.class}, then {@code new TypeResolver().where(formal, actual)} will {@linkplain
   * #resolveType resolve} {@code ParameterizedType List<T>} to {@code List<String>}, and resolve
   * {@code Map<T, Something>} to {@code Map<String, Something>} etc. Similarly, {@code formal} and
   * {@code actual} can be {@code Map<K, V>} and {@code Map<String, Integer>} respectively, or they

## Return Type and Data Filtering

Let's continue from the previous example. We wanted to **annotate the function with one type**, but we wanted to be able to return from the function something that actually includes **more data**.

@app.exception_handler(UnicornException)
async def unicorn_exception_handler(request: Request, exc: UnicornException):
    return JSONResponse(
        status_code=418,
        content={"message": f"Oops! {exc.name} did something. There goes a rainbow..."},
    )


@app.get("/unicorns/{name}")
async def read_unicorn(name: str):
    if name == "yolo":
        raise UnicornException(name=name)

  private static final String STRING = ASCII + I18N;
  private static final String LINES = "foo\nbar\r\nbaz\rsomething";
  private static final ImmutableList<String> SPLIT_LINES =
      ImmutableList.of("foo", "bar", "baz", "something");

  private TestCharSource source;

  @Override
  public void setUp() {
    source = new TestCharSource(STRING);
  }

  public void testOpenBufferedStream() throws IOException {