async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
    return {"fresh_value": fresh_value}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip

Prefer to use the `Annotated` version if possible.

///

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}
```

app = FastAPI()


@dataclass
class Item:
    name: str
    price: Optional[float] = None
    owner_ids: Optional[List[int]] = None


@app.get("/items/invalid", response_model=Item)
def get_invalid():
    return {"name": "invalid", "price": "foo"}


@app.get("/items/innerinvalid", response_model=Item)
def get_innerinvalid():
    return {"name": "double invalid", "price": "foo", "owner_ids": ["foo", "bar"]}

app = FastAPI()


class Item(BaseModel):
    name: str
    price: Optional[float] = None
    owner_ids: Optional[List[int]] = None


@app.get("/items/invalid", response_model=Item)
def get_invalid():
    return {"name": "invalid", "price": "foo"}


@app.get("/items/invalidnone", response_model=Item)
def get_invalid_none():
    return None

async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
    return {"fresh_value": fresh_value}
```

////

//// tab | Python 3.6+ без Annotated

/// tip | "Подсказка"

Предпочтительнее использовать версию с аннотацией, если это возможно.

///

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):

async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
    return {"fresh_value": fresh_value}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip | "Dica"

Utilize a versão com `Annotated` se possível.

///

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}
```

async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
    return {"fresh_value": fresh_value}
```

////

//// tab | Python 3.8+ nicht annotiert

/// tip | "Tipp"

Bevorzugen Sie die `Annotated`-Version, falls möglich.

///

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}

🏧 😐 🌐❔ 👆 💭 👆 💪 🔗 🤙 🔠 🔁 (🎲 💗 🕰) 🎏 📨 ↩️ ⚙️ "💾" 💲, 👆 💪 ⚒ 🔢 `use_cache=False` 🕐❔ ⚙️ `Depends`:

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}
```

## 🌃

↖️ ⚪️➡️ 🌐 🎀 🔤 ⚙️ 📥, **🔗 💉** ⚙️ 🙅.

🔢 👈 👀 🎏 *➡ 🛠️ 🔢*.

✋️, ⚫️ 📶 🏋️, & ✔ 👆 📣 🎲 🙇 🐦 🔗 "📊" (🌲).

在高级使用场景中，如果不想使用「缓存」值，而是为需要在同一请求的每一步操作（多次）中都实际调用依赖项，可以把 `Depends` 的参数 `use_cache` 的值设置为 `False` :

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):
    return {"fresh_value": fresh_value}
```

## 小结

千万别被本章里这些花里胡哨的词藻吓倒了，其实**依赖注入**系统非常简单。

依赖注入无非是与*路径操作函数*一样的函数罢了。

但它依然非常强大，能够声明任意嵌套深度的「图」或树状的依赖结构。

/// tip | "提示"

	TrustDomain string `json:"trust_domain"`
	SecretMeta
}

// SecretMeta holds selected fields which can be extracted from parsed x509 cert
type SecretMeta struct {
	Valid        bool   `json:"cert_valid"`
	SerialNumber string `json:"serial_number"`
	NotAfter     string `json:"not_after"`
	NotBefore    string `json:"not_before"`
	Type         string `json:"type"`
	TrustDomain  string `json:"trust_domain"`
}

		wantValid: false,
	}, {
		in: []sparseEntry{{1, 3}, {2, 2}}, size: 10,
		wantValid: false,
	}}

	for i, v := range vectors {
		gotValid := validateSparseEntries(v.in, v.size)
		if gotValid != v.wantValid {
			t.Errorf("test %d, validateSparseEntries() = %v, want %v", i, gotValid, v.wantValid)
		}
		if !v.wantValid {
			continue
		}
		gotAligned := alignSparseEntries(append([]sparseEntry{}, v.in...), v.size)