When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

You can import it from `fastapi.requests`:

```python
from fastapi.requests import HTTPConnection
```

from fastapi.testclient import TestClient

from docs_src.response_cookies.tutorial002 import app

client = TestClient(app)


def test_path_operation():
    response = client.post("/cookie-and-object/")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Come to the dark side, we have cookies"}

	}
	if vals := strings.Split(key.Name, "."); len(vals) == 2 {
		key.Extension = "." + vals[1]
		key.Name = strings.TrimSuffix(key.Name, key.Extension)
	}
	return
}

// replayItems - Reads the items from the store and replays.
func replayItems[I any](store Store[I], doneCh <-chan struct{}, log logger, id string) <-chan Key {
	keyCh := make(chan Key)

	go func() {
		defer xioutil.SafeClose(keyCh)

from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Cookies(BaseModel):
    session_id: str
    fatebook_tracker: str | None = None
    googall_tracker: str | None = None


@app.get("/items/")
async def read_items(cookies: Cookies = Cookie()):

from fastapi.testclient import TestClient

from docs_src.events.tutorial003 import (
    app,
    fake_answer_to_everything_ml_model,
    ml_models,
)


def test_events():
    assert not ml_models, "ml_models should be empty"
    with TestClient(app) as client:
        assert ml_models["answer_to_everything"] == fake_answer_to_everything_ml_model
        response = client.get("/predict", params={"x": 2})

from fastapi.testclient import TestClient

from docs_src.response_model.tutorial003_02 import app

client = TestClient(app)


def test_get_portal():
    response = client.get("/portal")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Here's your interdimensional portal."}


def test_get_redirect():
    response = client.get("/portal", params={"teleport": True}, follow_redirects=False)

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item):
    item_dict = item.dict()
    if item.tax:
        price_with_tax = item.price + item.tax
        item_dict.update({"price_with_tax": price_with_tax})

from typing import Union

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: int = Path(title="The ID of the item to get"),
    q: Union[str, None] = Query(default=None, alias="item-query"),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

## Import `Field`

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

Notice that `Field` is imported directly from `pydantic`, not from `fastapi` as are all the rest (`Query`, `Path`, `Body`, etc).

///

## Declare model attributes

You can then use `Field` with model attributes:

import typing

from fastapi import Body, FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()

media_type = "application/vnd.api+json"


# NOTE: These are not valid JSON:API resources
# but they are fine for testing requestBody with custom media_type
class Product(BaseModel):
    name: str
    price: float


class Shop(BaseModel):
    name: str


@app.post("/products")