* `Decimal`:
    * Standard Python `Decimal`.
    * In requests and responses, handled the same as a `float`.
* You can check all the valid Pydantic data types here: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Example

Here's an example *path operation* with parameters using some of the above types.

//// tab | Python 3.10+

{!> ../../docs_src/extra_models/tutorial001_py310.py!}
```

////

### 🔃 `**user_in.dict()`

#### Pydantic `.dict()`

`user_in` Pydantic 🏷 🎓 `UserIn`.

Pydantic 🏷 ✔️ `.dict()` 👩‍🔬 👈 📨 `dict` ⏮️ 🏷 💽.

, 🚥 👥 ✍ Pydantic 🎚 `user_in` 💖:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

& ⤴️ 👥 🤙:

* 100% test coverage.
* 100% type annotated codebase.

## Pydantic features

**FastAPI** is fully compatible with (and based on) <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>. So, any additional Pydantic code you have, will also work.

* 100% pokrycie testami.
* 100% adnotacji typów.

## Cechy Pydantic

**FastAPI** jest w pełni kompatybilny z (oraz bazuje na) <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>. Tak więc każdy dodatkowy kod Pydantic, który posiadasz, również będzie działał.

* `Decimal`:
    * Standard-Python-`Decimal`.
    * In Requests und Responses wird es wie ein `float` behandelt.
* Sie können alle gültigen Pydantic-Datentypen hier überprüfen: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Beispiel

Hier ist ein Beispiel für eine *Pfadoperation* mit Parametern, die einige der oben genannten Typen verwenden.

                    "msg": "Field required",
                    "input": None,
                },
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "item"],
                    "msg": "field required",
                    "type": "value_error.missing",
                },

{!> ../../docs_src/extra_models/tutorial001.py!}
```

////

### Про `**user_in.dict()`

#### `.dict()` из Pydantic

`user_in` - это Pydantic-модель класса `UserIn`.

У Pydantic-моделей есть метод `.dict()`, который возвращает `dict` с данными модели.

Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

{!> ../../docs_src/extra_models/tutorial001_py310.py!}
```

////

### Sobre `**user_in.dict()`

#### O `.dict()` do Pydantic

`user_in` é um modelo Pydantic da classe `UserIn`.

Os modelos Pydantic possuem um método `.dict()` que retorna um `dict` com os dados do modelo.

Então, se criarmos um objeto Pydantic `user_in` como:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

            Any,
            Doc(
                """
                The type to use for the response.

                It could be any valid Pydantic *field* type. So, it doesn't have to
                be a Pydantic model, it could be other things, like a `list`, `dict`,
                etc.

                It will be used for:

So, you can just let **FastAPI** use the correct Starlette version.

## About Pydantic

Pydantic includes the tests for **FastAPI** with its own tests, so new versions of Pydantic (above `1.0.0`) are always compatible with FastAPI.

You can pin Pydantic to any version above `1.0.0` that works for you.

For example:

```txt
pydantic>=2.7.0,<3.0.0