from fastapi import FastAPI, Request

app = FastAPI()


@app.get("/items/{item_id}")
def read_root(item_id: str, request: Request):
    client_host = request.client.host

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/{item_id}")
async def read_item(item_id: int):

Теперь измените файл `main.py`, чтобы получить тело ответа из `PUT` запроса.

Объявите тело, используя стандартную типизацию Python, спасибо Pydantic.

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

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")

### Multi destination replication

Replication from a source bucket to multiple destination buckets is supported. For each of the targets, repeat the steps to configure a remote target ARN and add replication rules to the source bucket's replication config.

    *   Rebase your pull request onto a recent pull from
        [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch.

2.  If you are changing the code and the docstring of a class/function/method,
    then you will need to
    [build TensorFlow from source](https://www.tensorflow.org/install/source).
    Once you are setup to build from source, you can run the tests:

    ```bash

   * iterated are the individual lists created, and these are not retained after iteration.
   *
   * @param sets the sets to choose elements from, in the order that the elements chosen from those
   *     sets should appear in the resulting lists
   * @param <B> any common base class shared by all axes (often just {@link Object})

		}
	}

	return r
}

// Maximum 4KiB size per object lock config.
const maxObjectLockConfigSize = 1 << 12

// ParseObjectLockConfig parses ObjectLockConfig from xml
func ParseObjectLockConfig(reader io.Reader) (*Config, error) {
	config := Config{}
	if err := xml.NewDecoder(io.LimitReader(reader, maxObjectLockConfigSize)).Decode(&config); err != nil {
		return nil, err
	}

	ChecksumCRC32
	// ChecksumCRC32C indicates a CRC32 checksum with Castagnoli table.
	ChecksumCRC32C
	// ChecksumInvalid indicates an invalid checksum.
	ChecksumInvalid
	// ChecksumMultipart indicates the checksum is from a multipart upload.
	ChecksumMultipart
	// ChecksumIncludesMultipart indicates the checksum also contains part checksums.
	ChecksumIncludesMultipart

	// ChecksumNone indicates no checksum.
	ChecksumNone ChecksumType = 0

from fastapi import FastAPI, Response

app = FastAPI()


@app.post("/cookie-and-object/")
def create_cookie(response: Response):
    response.set_cookie(key="fakesession", value="fake-cookie-session-value")

所以你需要确保你响应数据类型的正确性，如：你可以使用`JSONResponse`来兼容JSON的场景。

同时，你也应当仅反馈通过`response_model`过滤过的数据。

///

### 更多信息

/// note | "技术细节"

你也可以使用`from starlette.responses import Response` 或者 `from starlette.responses import JSONResponse`。

为了方便开发者，**FastAPI** 封装了相同数据类型，如`starlette.responses` 和 `fastapi.responses`。不过大部分response对象都是直接引用自Starlette。