#### `RequestValidationError` 🆚 `ValidationError`

/// warning

👫 📡 ℹ 👈 👆 💪 🚶 🚥 ⚫️ 🚫 ⚠ 👆 🔜.

///

`RequestValidationError` 🎧-🎓 Pydantic <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>.

**FastAPI** ⚙️ ⚫️ 👈, 🚥 👆 ⚙️ Pydantic 🏷 `response_model`, &amp; 👆 💽 ✔️ ❌, 👆 🔜 👀 ❌ 👆 🕹.

/// warning | Увага

Це технічні деталі, які Ви можете пропустити, якщо вони зараз не важливі для Вас.

///

`RequestValidationError` є підкласом Pydantic <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>.

  public static final String SEC_CH_UA_ARCH = "Sec-CH-UA-Arch";

  /**
   * The HTTP <a href="https://wicg.github.io/ua-client-hints/#sec-ch-ua-model">{@code
   * Sec-CH-UA-Model}</a> header field name.
   *
   * @since 30.0
   */
  public static final String SEC_CH_UA_MODEL = "Sec-CH-UA-Model";

  /**
   * The HTTP <a href="https://wicg.github.io/ua-client-hints/#sec-ch-ua-platform">{@code

<img src="/img/python-types/image06.png">

Lưu ý rằng, điều này có nghĩa rằng "`one_person`" là một **thực thể** của lớp `Person`.

Nó không có nghĩa "`one_person`" là một **lớp** gọi là `Person`.

## Pydantic models

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> là một thư viện Python để validate dữ liệu hiệu năng cao.

### Memory per Process { #memory-per-process }

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

 * `MODERN_TLS` is a secure configuration that connects to modern HTTPS servers.
 * `COMPATIBLE_TLS` is a secure configuration that connects to secure–but not current–HTTPS servers.
 * `CLEARTEXT` is an insecure configuration that is used for `http://` URLs.

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

👈 💪 ⤴️ ⚙️ 💖:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {

Temporarily adopting this point of view (of the *external developer*) can help you feel like it's more obvious where to put the parameters, the Pydantic model for the body, for the response, etc. for that *external API*.

///

### Create a callback `APIRouter` { #create-a-callback-apirouter }

First create a new `APIRouter` that will contain one or more callbacks.

Ayrıca, Pydantic modelleri de döndürebilirsiniz (bu konu ileriki aşamalarda irdelenecektir).

Otomatik olarak JSON'a dönüştürülecek (ORM'ler vb. dahil) başka birçok nesne ve model vardır. En beğendiklerinizi kullanmayı deneyin, yüksek ihtimalle destekleniyordur.

## Özet

* `FastAPI`'yı projemize dahil ettik.
* Bir `app` örneği oluşturduk.

### Memória por Processo

Agora, quando o programa carrega coisas na memória, por exemplo, um modelo de aprendizado de máquina em uma variável, ou o conteúdo de um arquivo grande em uma variável, tudo isso **consome um pouco da memória (RAM)** do servidor.