second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info "情報"
    `**second_user_data` は以下を意味します：

    `second_user_data`辞書のキーと値を直接、キーと値の引数として渡します。これは、`User(id=4, name="Mary", joined="2018-11-30")`と同等です。

### エディタのサポート

すべてのフレームワークは使いやすく直感的に使用できるように設計されており、すべての決定は開発を開始する前でも複数のエディターでテストされ、最高の開発体験が保証されます。

# General - How To - Recipes

Here are several pointers to other places in the docs, for general or frequent questions.

## Filter Data - Security

To ensure that you don't return more data than you should, read the docs for [Tutorial - Response Model - Return Type](../tutorial/response-model.md){.internal-link target=_blank}.

## Documentation Tags - OpenAPI

The files and form fields will be uploaded as form data and you will receive the files and form fields.

And you can declare some of the files as `bytes` and some as `UploadFile`.

!!! warning
    You can declare multiple `File` and `Form` parameters in a *path operation*, but you can't also declare `Body` fields that you expect to receive as JSON, as the request will have the body encoded using `multipart/form-data` instead of `application/json`.

# Using the Request Directly

Up to now, you have been declaring the parts of the request that you need with their types.

Taking data from:

* The path as parameters.
* Headers.
* Cookies.
* etc.

And by doing so, **FastAPI** is validating that data, converting it and generating documentation for your API automatically.

But there are situations where you might need to access the `Request` object directly.

# WebSockets

When defining WebSockets, you normally declare a parameter of type `WebSocket` and with it you can read data from the client and send data to it.

It is provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi import WebSocket
```

!!! tip

`UploadFile` имеет следующие методы `async`. Все они вызывают соответствующие файловые методы (используя внутренний SpooledTemporaryFile).

* `write(data)`: Записать данные `data` (`str` или `bytes`) в файл.
* `read(size)`: Прочитать количество `size` (`int`) байт/символов из файла.
* `seek(offset)`: Перейти к байту на позиции `offset` (`int`) в файле.

It will perform the validation of the compound data, and will document it like that for the OpenAPI schema and automatic docs.

## Singular values in body

The same way there is a `Query` and `Path` to define extra data for query and path parameters, **FastAPI** provides an equivalent `Body`.

`UploadFile` 支持以下 `async` 方法，（使用内部 `SpooledTemporaryFile`）可调用相应的文件方法。

* `write(data)`：把 `data` （`str` 或 `bytes`）写入文件；
* `read(size)`：按指定数量的字节或字符（`size` (`int`)）读取文件内容；
* `seek(offset)`：移动至文件 `offset` （`int`）字节处的位置；
    * 例如，`await myfile.seek(0) ` 移动到文件开头；
    * 执行 `await myfile.read()` 后，需再次读取已读取内容时，这种方法特别好用；

* Notes to be created (`NoteIn`).
* Notes to be returned (`Note`).

```Python hl_lines="31-33  36-39"
{!../../../docs_src/async_sql_databases/tutorial001.py!}
```

By creating these Pydantic models, the input data will be validated, serialized (converted), and annotated (documented).

So, you will be able to see it all in the interactive API docs.

## Connect and disconnect

* Create your `FastAPI` application.

You declare the "shape" of the data as classes with attributes.

And each attribute has a type.

Then you create an instance of that class with some values and it will validate the values, convert them to the appropriate type (if that's the case) and give you an object with all the data.

And you get all the editor support with that resulting object.