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

#### `RequestValidationError` или `ValidationError`

!!! warning "Внимание"
    Это технические детали, которые можно пропустить, если они не важны для вас сейчас.

以下のようなテキスト版を取得します:

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

#### `RequestValidationError`と`ValidationError`

!!! warning "注意"
    これらは今のあなたにとって重要でない場合は省略しても良い技術的な詳細です。

`RequestValidationError`はPydanticの<a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>のサブクラスです。

```Python hl_lines="2  14-16"
{!../../../docs_src/handling_errors/tutorial004.py!}
```

Wenn Sie nun `/items/foo` besuchen, erhalten Sie statt des Default-JSON-Errors:

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

Os status codes na faixa dos 400 significam que houve um erro por parte do cliente.

Você se lembra de todos aqueles erros (e piadas) a respeito do "**404 Not Found**"?

## Use o `HTTPException`

Para retornar ao cliente *responses* HTTP com erros, use o `HTTPException`.

### Import `HTTPException`

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

This also means that if something changed it will be **reflected** on the client code automatically. And if you **build** the client it will error out if you have any **mismatch** in the data used.

### Small Errors Automatically Handled

When building web APIs with FastAPI, if there's an error in our code, FastAPI will normally contain it to the single request that triggered the error. 🛡

The client will get a **500 Internal Server Error** for that request, but the application will continue working for the next requests instead of just crashing completely.

        logging.error(
            f"Response was not 200, after: {after}, category_id: {category_id}"
        )
        logging.error(response.text)
        raise RuntimeError(response.text)
    data = response.json()
    if "errors" in data:
        logging.error(f"Errors in response, after: {after}, category_id: {category_id}")
        logging.error(data["errors"])
        logging.error(response.text)

            v_, errors_ = field.validate(value, values, loc=loc)

            if isinstance(errors_, list):
                errors.extend(errors_)
            elif errors_:
                errors.append(errors_)
            else:
                values[field.name] = v_
    return values, errors

```Python hl_lines="1  4"
{!../../../docs_src/python_types/tutorial009.py!}
```

Using `Optional[str]` instead of just `str` will let the editor help you detecting errors where you could be assuming that a value is always a `str`, when it could actually be `None` too.

`Optional[Something]` is actually a shortcut for `Union[Something, None]`, they are equivalent.

      "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"
    }
  ]
}
```

Der Pfad-Parameter `item_id` hatte den Wert `"foo"`, was kein `int` ist.