```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo",
      "url": "https://errors.pydantic.dev/2.1/v/int_parsing"
    }
  ]
}
```

                "path",
                "item_id"
            ],
            "msg": "value is not a valid integer",
            "type": "type_error.integer"
        }
    ]
}

```

被替换为了以下文本格式的错误信息：

```
1 validation error
path -> item_id
  value is not a valid integer (type=type_error.integer)

```

### `RequestValidationError` vs `ValidationError`

                "path",
                "item_id"
            ],
            "msg": "value is not a valid integer",
            "type": "type_error.integer"
        }
    ]
}
```

👆 🔜 🤚 ✍ ⏬, ⏮️:

```
1 validation error
path -> item_id
  value is not a valid integer (type=type_error.integer)
```

#### `RequestValidationError` 🆚 `ValidationError`

!!! warning

```JSON
{
    "detail": [
        {
            "loc": [
                "path",
                "item_id"
            ],
            "msg": "value is not a valid integer",
            "type": "type_error.integer"
        }
    ]
}
```

这是因为路径参数 `item_id` 的值 （`"foo"`）的类型不是 `int`。

    But this example is still valid and it shows how to interact with the internal components.

We can also use this same approach to access the request body in an exception handler.

All we need to do is handle the request inside a `try`/`except` block:

    ```

=== "Python 3.8+"

    ```Python hl_lines="4  10"
    {!> ../../../docs_src/body_nested_models/tutorial005.py!}
    ```

The string will be checked to be a valid URL, and documented in JSON Schema / OpenAPI as such.

## Attributes with lists of submodels

You can also use Pydantic models as subtypes of `list`, `set`, etc.:

=== "Python 3.10+"

    You can use a closing code from the <a href="https://tools.ietf.org/html/rfc6455#section-7.4.1" class="external-link" target="_blank">valid codes defined in the specification</a>.

### Try the WebSockets with dependencies

If your file is named `main.py`, run your application with:

<div class="termy">

```console
$ fastapi dev main.py

## Response with arbitrary `dict`

You can also declare a response using a plain arbitrary `dict`, declaring just the type of the keys and values, without using a Pydantic model.

This is useful if you don't know the valid field/attribute names (that would be needed for a Pydantic model) beforehand.

In this case, you can use `typing.Dict` (or just `dict` in Python 3.9 and above):

=== "Python 3.9+"

    ```Python hl_lines="6"

```JSON
{
    "detail": [
        {
            "loc": [
                "path",
                "item_id"
            ],
            "msg": "value is not a valid integer",
            "type": "type_error.integer"
        }
    ]
}
```

debido a que el parámetro de path `item_id` tenía el valor `"foo"`, que no es un `int`.

```JSON
{
    "detail": [
        {
            "loc": [
                "path",
                "item_id"
            ],
            "msg": "value is not a valid integer",
            "type": "type_error.integer"
        }
    ]
}
```

devido ao parâmetro da rota `item_id` ter um valor `"foo"`, que não é um `int`.