![ReDoc](https://fastapi.tiangolo.com/img/index/index-02-redoc-simple.png)

## Példa frissítése

Módosítsuk a `main.py` fájlt, hogy `PUT` kérések esetén tudjon body-t fogadni.

Deklaráld a body-t standard Python típusokkal, a Pydantic-nak köszönhetően.

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and validated.

!!! check "Inspired **FastAPI** to"
    Use Python types to have great editor support.

                        "token_type": {"title": "Token Type", "type": "string"},
                    },
                },
                "Body_login_for_access_token_token_post": {
                    "title": "Body_login_for_access_token_token_post",
                    "required": ["username", "password"],
                    "type": "object",
                    "properties": {

<img src="/img/tutorial/generate-clients/image08.png">

## Benefits

When using the automatically generated clients you would get **autocompletion** for:

* Methods.
* Request payloads in the body, query parameters, etc.
* Response payloads.

You would also have **inline errors** for everything.

* Tự động tài liệu hóa data model theo <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (OpenAPI bản thân nó được dựa trên JSON Schema).

    client = TestClient(app)
    return client


def test_post_form_no_body(client: TestClient):
    response = client.post("/files/")
    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "missing",
                    "loc": ["body", "file"],
                    "msg": "Field required",

    ```Python hl_lines="1"
    {!> ../../../docs_src/request_files/tutorial001.py!}
    ```

## Определите параметры `File`

Создайте параметры `File` так же, как вы это делаете для `Body` или `Form`:

=== "Python 3.9+"

    ```Python hl_lines="9"
    {!> ../../../docs_src/request_files/tutorial001_an_py39.py!}
    ```

=== "Python 3.6+"

    ```Python hl_lines="8"

    {!> ../../../docs_src/dependencies/tutorial001.py!}
    ```

### Deklarieren der Abhängigkeit im <abbr title="Das Abhängige, der Verwender der Abhängigkeit">„Dependant“</abbr>

So wie auch `Body`, `Query`, usw., verwenden Sie `Depends` mit den Parametern Ihrer *Pfadoperation-Funktion*:

=== "Python 3.10+"

    ```Python hl_lines="13  18"
    {!> ../../../docs_src/dependencies/tutorial001_an_py310.py!}

            "detail": [
                {
                    "type": "missing",
                    "loc": ["body", "grant_type"],
                    "msg": "Field required",
                    "input": None,
                },
                {
                    "type": "missing",
                    "loc": ["body", "username"],
                    "msg": "Field required",
                    "input": None,
                },

    ```

!!! note
    Notice that `response_model` is a parameter of the "decorator" method (`get`, `post`, etc). Not of your *path operation function*, like all the parameters and body.

`response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`.