In that case, it could be better to have only 2 servers and use a higher percentage of their resources (CPU, memory, disk, network bandwidth, etc).

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

* the data from the client to be sent through the network
* the data sent by your program to be received by the client through the network
* the contents of a file in the disk to be read by the system and given to your program
* the contents your program gave to the system to be written to disk
* a remote API operation
* a database operation to finish
* a database query to return the results
* etc.

* You don't have to use `File()` in the default value of the parameter.
* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.

framework'den geliyorsanız ve küçük bir performans kazancı (yaklaşık 100 nanosaniye) için  "def" ile *path fonksiyonu* tanımlamaya alışkınsanız, **FastAPI**'de tam tersi olacağını unutmayın. Bu durumlarda, *path fonksiyonu* <abbr title="Input/Output: disk okuma veya yazma, ağ iletişimleri.">G/Ç</abbr> engelleyen durum oluşturmadıkça "async def" kullanmak daha iyidir.

Yine de, her iki durumda da, **FastAPI**'nin önceki frameworkden [hala daha hızlı](index.md#performans){.internal-link target=_blank}...

    * Normally, a token is set to expire after some time.
        * So, the user will have to log in again at some point later.
        * And if the token is stolen, the risk is less. It is not like a permanent key that will work forever (in most of the cases).
* The frontend stores that token temporarily somewhere.
* The user clicks in the frontend to go to another section of the frontend web app.

Here we define the config `env_file` inside of your Pydantic `Settings` class, and set the value to the filename with the dotenv file we want to use.

### Creating the `Settings` only once with `lru_cache`

Reading a file from disk is normally a costly (slow) operation, so you probably want to do it only once and then re-use the same settings object, instead of reading it for each request.

But every time we do:

```Python
Settings()
```

(aproximadamente 100 nanosegundos), ten en cuenta que en **FastAPI** el efecto sería bastante opuesto. En estos casos, es mejor usar `async def` a menos que tus *path operation functions* usen un código que realice el bloqueo <abbr title="Input/Output: disk reading or writing, network communications.">I/O</abbr>.

Aún así, en ambas situaciones, es probable que **FastAPI** sea [aún más rápido](index.md#rendimiento){.Internal-link target=_blank} que (o al menos comparable) a tu framework anterior....

🚥 👆 👟 ⚪️➡️ ➕1️⃣ 🔁 🛠️ 👈 🔨 🚫 👷 🌌 🔬 🔛 &amp; 👆 ⚙️ ⚖ 🙃 📊-🕴 *➡ 🛠️ 🔢* ⏮️ ✅ `def` 🤪 🎭 📈 (🔃 1️⃣0️⃣0️⃣ 💓), 🙏 🗒 👈 **FastAPI** ⭐ 🔜 🔄. 👫 💼, ⚫️ 👻 ⚙️ `async def` 🚥 👆 *➡ 🛠️ 🔢* ⚙️ 📟 👈 🎭 🚧 <abbr title="Input/Output: disk reading or writing, network communications.">👤/🅾</abbr>.

, 👯‍♂️ ⚠, 🤞 👈 **FastAPI** 🔜 [⏩](index.md#_15){.internal-link target=_blank} 🌘 (⚖️ 🌘 ⭐) 👆 ⏮️ 🛠️.

### 🔗

A container image is comparable to the **program** file and contents, e.g. `python` and some file `main.py`.