| <<<pom>>>             |               | <= type>   | none      |                       |                       |
*-----------------------+---------------+------------+-----------+-----------------------+-----------------------+
| <<<bom>>> *           |               | <<<pom>>>  | none      |                       |                       |

    client = TestClient(mod.app)
    return client


@pytest.mark.parametrize(
    "path,headers,expected_status,expected_response",
    [
        ("/items", None, 200, {"X-Token values": None}),
        ("/items", {"x-token": "foo"}, 200, {"X-Token values": ["foo"]}),
        (
            "/items",
            [("x-token", "foo"), ("x-token", "bar")],
            200,

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package csv

import (
	"encoding/xml"
	"errors"
	"fmt"
	"io"
	"strings"
	"unicode/utf8"
)

const (
	none   = "none"
	use    = "use"
	ignore = "ignore"

	defaultRecordDelimiter      = "\n"
	defaultFieldDelimiter       = ","
	defaultQuoteCharacter       = `"`
	defaultQuoteEscapeCharacter = `"`

<img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image02.png">

## 响应模型编码参数

你的响应模型可以具有默认值，例如：

{* ../../docs_src/response_model/tutorial004.py hl[11,13:14] *}

* `description: Union[str, None] = None` 具有默认值 `None`。
* `tax: float = 10.5` 具有默认值 `10.5`.
* `tags: List[str] = []` 具有一个空列表作为默认值： `[]`.

但如果它们并没有存储实际的值，你可能想从结果中忽略它们的默认值。

举个例子，当你在 NoSQL 数据库中保存了具有许多可选属性的模型，但你又不想发送充满默认值的很长的 JSON 响应。

app = FastAPI()


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


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")
def update_item(item_id: int, item: Item):

    assert response.json() == {
        "name": "Special Offer",
        "description": None,
        "price": 38.6,
        "items": [
            {
                "name": "Foo",
                "description": None,
                "price": 35.4,
                "tax": None,
                "tags": [],
                "images": [
                    {

public class CIDetectorHelperTest {
    private static final Set<String> ALL =
            Set.of("CIRCLECI", "CI", "WORKSPACE", "GITHUB_ACTIONS", "TEAMCITY_VERSION", "TRAVIS");

    @Test
    void none() throws Exception {
        assertEquals("NONE;", runner(Map.of()));
    }

    @Test
    void generic() throws Exception {
        assertEquals(GenericCIDetector.NAME + ";", runner(Map.of("CI", "true")));
    }

    @Test

Your response model could have default values, like:

{* ../../docs_src/response_model/tutorial004_py310.py hl[9,11:12] *}

* `description: Union[str, None] = None` (or `str | None = None` in Python 3.10) has a default of `None`.
* `tax: float = 10.5` has a default of `10.5`.
* `tags: List[str] = []` has a default of an empty list: `[]`.

Seu modelo de resposta pode ter valores padrão, como:

{* ../../docs_src/response_model/tutorial004_py310.py hl[9,11:12] *}

* `description: Union[str, None] = None` (ou `str | None = None` no Python 3.10) tem um padrão de `None`.
* `tax: float = 10.5` tem um padrão de `10.5`.
* `tags: List[str] = []` tem um padrão de uma lista vazia: `[]`.

        "detail": [
            {
                "type": "missing",
                "loc": ["header", "p_alias"],
                "msg": "Field required",
                "input": IsOneOf(None, IsPartialDict({"p": ["hello", "world"]})),
            }
        ]
    }


@pytest.mark.parametrize(
    "path",
    [
        "/required-list-alias",
        "/model-required-list-alias",