Nur Standard-**Python+**.

Zum Beispiel für ein `int`:

```Python
item_id: int
```

oder für ein komplexeres `Item`-Modell:

```Python
item: Item
```

... und mit dieser einen Deklaration erhalten Sie:

* Editor-Unterstützung, einschließlich:
    * Code-Vervollständigung.
    * Typprüfungen.

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

Notice that this means "`one_person` is an **instance** of the class `Person`".

It doesn't mean "`one_person` is the **class** called `Person`".

## Pydantic models { #pydantic-models }

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> is a Python library to perform data validation.

You declare the "shape" of the data as classes with attributes.

# Response Status Code { #response-status-code }

The same way you can specify a response model, you can also declare the HTTP status code used for the response with the parameter `status_code` in any of the *path operations*:

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* etc.

{* ../../docs_src/response_status_code/tutorial001.py hl[6] *}

/// note

qui sont relativement fortement couplées.

/// check | A inspiré **FastAPI** à

Définir des validations supplémentaires pour les types de données utilisant la valeur "par défaut" des attributs du modèle. Ceci améliore le support de l'éditeur, et n'était pas disponible dans Pydantic auparavant.

import org.apache.maven.artifact.resolver.ArtifactResolutionException;
import org.apache.maven.artifact.versioning.InvalidVersionSpecificationException;
import org.apache.maven.execution.MavenSession;
import org.apache.maven.model.Plugin;
import org.apache.maven.plugin.descriptor.PluginDescriptor;
import org.apache.maven.plugin.version.PluginVersionNotFoundException;
import org.apache.maven.plugin.version.PluginVersionResolutionException;

And then you can set headers in that *temporal* response object.

{* ../../docs_src/response_headers/tutorial002.py hl[1, 7:8] *}

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

 ╭────────── FastAPI CLI - Development mode ───────────╮
 │                                                     │
 │  Serving at: http://127.0.0.1:8000                  │
 │                                                     │
 │  API docs: http://127.0.0.1:8000/docs               │
 │                                                     │
 │  Running in development mode, for production use:   │

Although any other parameter declared normally (for example, the body with a Pydantic model) would still be validated, converted, annotated, etc.

But there are specific cases where it's useful to get the `Request` object.

## Use the `Request` object directly { #use-the-request-object-directly }

from pydantic import BaseModel

# Deklarieren Sie eine Variable als ein `str`
# und bekommen Sie Editor-Unterstütung innerhalb der Funktion
def main(user_id: str):
    return user_id


# Ein Pydantic-Modell
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Das kann nun wie folgt verwendet werden:

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

```Python
from datetime import date

from pydantic import BaseModel

# Declareer een variabele als een str
# en krijg editorondersteuning in de functie
def main(user_id: str):
    return user_id


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

Vervolgens kan je het op deze manier gebruiken:

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