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`

!!! warning "警告"

    如果您觉得现在还用不到以下技术细节，可以先跳过下面的内容。


`RequestValidationError` 是 Pydantic 的 <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a> 的子类。

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

#### `RequestValidationError` 🆚 `ValidationError`

!!! warning
    👫 📡 ℹ 👈 👆 💪 🚶 🚥 ⚫️ 🚫 ⚠ 👆 🔜.

`RequestValidationError` 🎧-🎓 Pydantic <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>.

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。

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.

```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"
    }
  ]
}
```

│   └── test_main.py
```

Let's say that now the file `main.py` with your **FastAPI** app has some other **path operations**.

It has a `GET` operation that could return an error.

It has a `POST` operation that could return several errors.

Both *path operations* require an `X-Token` header.

=== "Python 3.10+"

    ```Python
    {!> ../../../docs_src/app_testing/app_b_an_py310/main.py!}
    ```

* **Veloce da programmare**: Velocizza il lavoro consentendo il rilascio di nuove funzionalità tra il 200% e il 300% più rapidamente. *
* **Meno bug**: Riduce di circa il 40% gli errori che commettono gli sviluppatori durante la scrittura del codice. *

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

app = SomeASGIApp()

new_app = UnicornMiddleware(app, some_config="rainbow")
```

But FastAPI (actually Starlette) provides a simpler way to do it that makes sure that the internal middlewares to handle server errors and custom exception handlers work properly.

For that, you use `app.add_middleware()` (as in the example for CORS).

```Python
from fastapi import FastAPI
from unicorn import UnicornMiddleware

app = FastAPI()

                    "schema": {
                        "$ref": "#/components/schemas/Item"
                    }
                }
            }
        },
        "422": {
            "description": "Validation Error",
            "content": {
                "application/json": {
                    "schema": {
                        "$ref": "#/components/schemas/HTTPValidationError"
                    }
                }