last_edge = discussion_edges[-1]
        discussion_edges = get_graphql_question_discussion_edges(
            settings=settings, after=last_edge.cursor
        )
    return discussion_nodes


def get_discussions_experts(
    discussion_nodes: List[DiscussionsNode],
) -> DiscussionExpertsResults:
    commenters = Counter()
    last_month_commenters = Counter()

{% if people %}
<div class="user-list user-list-center">
{% for user in people.last_month_experts[:10] %}

<div class="user"><a href="{{ user.url }}" target="_blank"><div class="avatar-wrapper"><img src="{{ user.avatarUrl }}"/></div><div class="title">@{{ user.login }}</div></a> <div class="count">Questions replied: {{ user.count }}</div></div>
{% endfor %}

!!! note
    Notice that as we communicate with the database using `await`, the *path operation function* is declared with `async`.

### Notice the `response_model=List[Note]`

It uses `typing.List`.

That documents (and validates, serializes, filters) the output data, as a `list` of `Note`s.

## Create notes

Create the *path operation function* to create notes:

```Python hl_lines="61-65"

def get_full_name(first_name, last_name):
    full_name = first_name.title() + " " + last_name.title()
    return full_name

app = FastAPI()


def query_extractor(q: Union[str, None] = None):
    return q


def query_or_cookie_extractor(
    q: Annotated[str, Depends(query_extractor)],
    last_query: Annotated[Union[str, None], Cookie()] = None,
):
    if not q:
        return last_query
    return q


@app.get("/items/")
async def read_query(
    query_or_default: Annotated[str, Depends(query_or_cookie_extractor)],
):

):
    comment_nodes: List[Comment] = []
    discussion_edges = get_graphql_translation_discussion_comments_edges(
        settings=settings, discussion_number=discussion_number
    )

    while discussion_edges:
        for discussion_edge in discussion_edges:
            comment_nodes.append(discussion_edge.node)
        last_edge = discussion_edges[-1]

```Python hl_lines="55-58"
{!../../../docs_src/async_sql_databases/tutorial001.py!}
```

!!! Note "笔记"

    注意，本例与数据库通信时使用 `await`，因此*路径操作函数*要声明为异步函数（`asnyc`）。

### 注意 `response_model=List[Note]`

`response_model=List[Note]` 使用的是 `typing.List`。

它以笔记（`Note`）列表的形式存档（及验证、序列化、筛选）输出的数据。

## 创建笔记

创建新建笔记的*路径操作函数*：

```Python hl_lines="61-65"
{!../../../docs_src/async_sql_databases/tutorial001.py!}
```

    In this case, `str` is the type parameter passed to `List` (or `list` in Python 3.9 and above).

That means: "the variable `items` is a `list`, and each of the items in this list is a `str`".

!!! tip
    If you use Python 3.9 or above, you don't have to import `List` from `typing`, you can use the same regular `list` type instead.

"dict", "list", "set" ve "tuple" gibi diğer değerleri içerebilen bazı veri yapıları vardır. Ve dahili değerlerinin de tip belirtecleri olabilir.

Bu tipleri ve dahili tpileri bildirmek için standart Python modülünü "typing" kullanabilirsiniz.

Bu tür tip belirteçlerini desteklemek için özel olarak mevcuttur.

#### `List`

Örneğin `str` değerlerden oluşan bir `list` tanımlayalım.

```Python
    first_name, last_name
```

para:

```Python
    first_name: str, last_name: str
```

É isso aí.

Esses são os "type hints":

```Python hl_lines="1"
{!../../../docs_src/python_types/tutorial002.py!}
```

Isso não é o mesmo que declarar valores padrão como seria com:

```Python
    first_name="john", last_name="doe"
```

É uma coisa diferente.