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

=== "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)):

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

=== "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)):

			name:           "Correct-Decom-Pool-Removed",
			expectedErr:    false,
			expectedUpdate: true,
		},
		{
			meta:           poolMeta{}, // no-pool info available fresh setup.
			pools:          pools,
			name:           "Correct-Fresh-Setup",
			expectedErr:    false,
			expectedUpdate: true,
		},
		{
			meta:           nmeta2,
			pools:          orderChangePools,

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"

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

## 🌃

↖️ ⚪️➡️ 🌐 🎀 🔤 ⚙️ 📥, **🔗 💉** ⚙️ 🙅.

🔢 👈 👀 🎏 *➡ 🛠️ 🔢*.

✋️, ⚫️ 📶 🏋️, & ✔ 👆 📣 🎲 🙇 🐦 🔗 "📊" (🌲).

!!! tip

By the time I started creating **FastAPI** itself, most of the pieces were already in place, the design was defined, the requirements and tools were ready, and the knowledge about the standards and specifications was clear and fresh.

## Future

By this point, it's already clear that **FastAPI** with its ideas is being useful for many people.

It is being chosen over previous alternatives for suiting many use cases better.

        .minFresh(3.seconds)
        .onlyIfCached()
        .noTransform()
        .immutable()
        .build()
    assertThat(cacheControl.toString()).isEqualTo(
      "no-cache, no-store, max-age=1, max-stale=2, min-fresh=3, only-if-cached, no-transform, immutable",
    )
    assertThat(cacheControl.noCache).isTrue()
    assertThat(cacheControl.noStore).isTrue()
    assertThat(cacheControl.maxAgeSeconds).isEqualTo(1)

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。

*path operation関数*と同じように見えるただの関数です。

しかし、それでも非常に強力で、任意の深くネストされた依存関係「グラフ」（ツリー）を宣言することができます。

var errSkipFile = errors.New("skip this file")

var errIgnoreFileContrib = errors.New("ignore this file's contribution toward data-usage")

// errXLBackend XL drive mode requires fresh deployment.
var errXLBackend = errors.New("XL backend requires fresh drive")

// StorageErr represents error generated by xlStorage call.
type StorageErr string

func (h StorageErr) Error() string {
	return string(h)
}

        .onlyIfCached()
        .noTransform()
        .immutable()
        .build()
    assertThat(cacheControl.toString()).isEqualTo(
      "no-cache, no-store, max-age=1, max-stale=2, min-fresh=3, only-if-cached, " +
        "no-transform, immutable",
    )
    assertThat(cacheControl.noCache).isTrue()
    assertThat(cacheControl.noStore).isTrue()
    assertThat(cacheControl.maxAgeSeconds).isEqualTo(1)