"content": {"application/json": {"schema": {}}},
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

                            "content": {"application/json": {"schema": {}}},
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

from starlette.exceptions import HTTPException as StarletteHTTPException

app = FastAPI()


@app.exception_handler(StarletteHTTPException)
async def custom_http_exception_handler(request, exc):
    print(f"OMG! An HTTP error!: {repr(exc)}")
    return await http_exception_handler(request, exc)


@app.exception_handler(RequestValidationError)
async def validation_exception_handler(request, exc):

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"
                    }
                }

之后，所有处理逻辑都一样。

但因为改变了 `GzipRequest.body`，**FastAPI** 加载请求体时会自动解压。

## 在异常处理器中访问请求体

!!! tip "提示"

    为了解决同样的问题，在 `RequestValidationError` 的自定义处理器使用 `body`  （[处理错误](../tutorial/handling-errors.md#use-the-requestvalidationerror-body){.internal-link target=_blank}）可能会更容易。

    但本例仍然可行，而且本例展示了如何与内部组件进行交互。

同样也可以在异常处理器中访问请求体。

此时要做的只是处理 `try`/`except` 中的请求：

```Python hl_lines="13  15"

                                }
                            },
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

FastAPI will use this return type to:

* **Validate** the returned data.
    * If the data is invalid (e.g. you are missing a field), it means that *your* app code is broken, not returning what it should, and it will return a server error instead of returning incorrect data. This way you and your clients can be certain that they will receive the data and the data shape expected.
* Add a **JSON Schema** for the response, in the OpenAPI *path operation*.

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

из-за того, что параметр пути `item_id` имеет значение `"foo"`, которое не является типом  `int`.