## Классы как зависимости { #classes-as-dependencies_1 }

Вы можете заметить, что для создания экземпляра класса в Python используется тот же синтаксис.

Например:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

В данном случае `fluffy` является экземпляром класса `Cat`.

А чтобы создать `fluffy`, вы «вызываете» `Cat`.

	for _, opt := range opts {
		str := stmt.Quote(opt.DBName)
		if opt.Expression != "" {
			str = opt.Expression
		} else if opt.Length > 0 {
			str += fmt.Sprintf("(%d)", opt.Length)
		}

		if opt.Collate != "" {
			str += " COLLATE " + opt.Collate
		}

		if opt.Sort != "" {
			str += " " + opt.Sort
		}
		results = append(results, clause.Expr{SQL: str})
	}
	return
}

    @Test
    @DisplayName("Should handle mixed CharSequence types")
    void testJoinWithMixedCharSequenceTypes() {
        String str = "string";
        StringBuilder builder = new StringBuilder("builder");
        StringBuffer buffer = new StringBuffer("buffer");
        String result = StringUtil.join(",", str, builder, buffer);
        assertEquals("string,builder,buffer", result);
    }

    @ParameterizedTest

from pydantic import BaseModel

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}")

from .utils import needs_py310


def get_client():
    app = FastAPI()
    with pytest.warns(FastAPIDeprecationWarning):

        @app.get("/items/")
        async def read_items(
            q: Annotated[str | None, Query(regex="^fixedquery$")] = None,
        ):
            if q:
                return f"Hello {q}"
            else:
                return "Hello World"

    client = TestClient(app)
    return client

## 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。

### 使用 `response_model_exclude_unset` 参数

For that, we update the Pydantic model `TokenData` with a new property `scopes`.

By validating the data with Pydantic we can make sure that we have, for example, exactly a `list` of `str` with the scopes and a `str` with the `username`.

Instead of, for example, a `dict`, or something else, as it could break the application at some point later, making it a security risk.

	c.processor.callbacks = append(c.processor.callbacks, c)
	return c.processor.compile()
}

// getRIndex get right index from string slice
func getRIndex(strs []string, str string) int {
	for i := len(strs) - 1; i >= 0; i-- {
		if strs[i] == str {
			return i
		}
	}
	return -1
}

func sortCallbacks(cs []*callback) (fns []func(*DB), err error) {
	var (
		names, sorted []string

            case NUMBER:
                final Number d = (Number) xObj.value();
                return new String[] { d.toString() };
            case STRING:
                final String str = (String) xObj.value();
                return new String[] { str.trim() };
            case NODESET:
                final XPathNodes nodeList = (XPathNodes) xObj.value();
                final List<String> strList = new ArrayList<>();

Puedes notar que para crear una instance de una clase en Python, utilizas esa misma sintaxis.

Por ejemplo:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

En este caso, `fluffy` es una instance de la clase `Cat`.

Y para crear `fluffy`, estás "llamando" a `Cat`.