def test_depends_repr():
    assert repr(Depends()) == "Depends(NoneType)"
    assert repr(Depends(get_user)) == "Depends(get_user)"
    assert repr(Depends(use_cache=False)) == "Depends(NoneType, use_cache=False)"
    assert (
        repr(Depends(get_user, use_cache=False)) == "Depends(get_user, use_cache=False)"

//// tab | Python 3.8+

```Python hl_lines="1"
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

//// tab | Python 3.6+

```Python hl_lines="1"
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

//// tab | Python 3.8+

```Python hl_lines="1"
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"

🏧 😐 🌐❔ 👆 💭 👆 💪 🔗 🤙 🔠 🔁 (🎲 💗 🕰) 🎏 📨 ↩️ ⚙️ "💾" 💲, 👆 💪 ⚒ 🔢 `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}
```

## 🌃

↖️ ⚪️➡️ 🌐 🎀 🔤 ⚙️ 📥, **🔗 💉** ⚙️ 🙅.

🔢 👈 👀 🎏 *➡ 🛠️ 🔢*.

//// tab | Python 3.8+

```Python hl_lines="1"
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

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。

    response_param_name: Optional[str] = None
    background_tasks_param_name: Optional[str] = None
    security_scopes_param_name: Optional[str] = None
    security_scopes: Optional[List[str]] = None
    use_cache: bool = True
    path: Optional[str] = None
    cache_key: Tuple[Optional[Callable[..., Any]], Tuple[str, ...]] = field(init=False)

    def __post_init__(self) -> None:

):
    return {"counter": count, "subcounter": subcount}


@app.get("/sub-counter-no-cache/")
async def get_sub_counter_no_cache(
    subcount: int = Depends(super_dep),
    count: int = Depends(dep_counter, use_cache=False),
):
    return {"counter": count, "subcounter": subcount}


@app.get("/scope-counter")
async def get_scope_counter(
    count: int = Security(dep_counter),

高度なシナリオでは、「キャッシュされた」値を使うのではなく、同じリクエストの各ステップ（おそらく複数回）で依存関係を呼び出す必要があることがわかっている場合、`Depens`を使用する際に、`use_cache=False`というパラメータを設定することができます。

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

## まとめ

ここで使われている派手な言葉は別にして、**依存性注入** システムは非常にシンプルです。