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.

### Just Modern Python

It's all based on standard **Python type** declarations (thanks to Pydantic). No new syntax to learn. Just standard modern Python.

If you need a 2 minute refresher of how to use Python types (even if you don't use FastAPI), check the short tutorial: [Python Types](python-types.md){.internal-link target=_blank}.

You write standard Python with types:

```Python
from datetime import date

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

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。

Next, it 🤖 takes the first task to finish (let's say, our "slow-file" 📝) and continues whatever it had to do with it.

That "wait for something else" normally refers to <abbr title="Input and Output">I/O</abbr> operations that are relatively "slow" (compared to the speed of the processor and the RAM memory), like waiting for:

* the data from the client to be sent through the network

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"

# CORS (Cross-Origin Resource Sharing)

<a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS" class="external-link" target="_blank">CORS or "Cross-Origin Resource Sharing"</a> refers to the situations when a frontend running in a browser has JavaScript code that communicates with a backend, and the backend is in a different "origin" than the frontend.

## Origin

<img src="https://fastapi.tiangolo.com/img/async/parallel-burgers/parallel-burgers-04.png" alt="illustration">

Luego, el cajero / cocinero 👨‍🍳 finalmente regresa con tus hamburguesas 🍔, después de mucho tiempo esperando 🕙 frente al mostrador.

<img src="https://fastapi.tiangolo.com/img/async/parallel-burgers/parallel-burgers-05.png" alt="illustration">

In contrast to a "**container image**" that is the stored static contents, a "**container**" normally refers to the running instance, the thing that is being **executed**.