fields `username` and `password`.

    All the initialization parameters are extracted from the request.

    The only difference between `OAuth2PasswordRequestFormStrict` and
    `OAuth2PasswordRequestForm` is that `OAuth2PasswordRequestFormStrict` requires the
    client to send the form field `grant_type` with the value `"password"`, which

                    "msg": "Field required",
                    "input": {"name": "Foo"},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "price"],
                    "msg": "field required",
                    "type": "value_error.missing",

                    "msg": "Field required",
                    "input": {"name": "Foo"},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "price"],
                    "msg": "field required",
                    "type": "value_error.missing",

### Type Annotations and Tooling

First let's see how editors, mypy and other tools would see this.

`BaseUser` has the base fields. Then `UserIn` inherits from `BaseUser` and adds the `password` field, so, it will include all the fields from both models.

We annotate the function return type as `BaseUser`, but we are actually returning a `UserIn` instance.

    Например, вы можете использовать это для добавления дополнительной информации для пользовательского интерфейса в вашем веб-приложении и т.д.

## Дополнительные аргументы поля `Field`

При использовании `Field()` с моделями Pydantic, вы также можете объявлять дополнительную информацию для **JSON Schema**, передавая любые другие произвольные аргументы в функцию.

!!! tip
    Pydantic, ❔ ⚫️❔ 🏋️ 🌐 💽 🔬 &amp; 🛠️ FastAPI, ✔️ 🎁 🎭 🕐❔ 👆 ⚙️ `Optional` ⚖️ `Union[Something, None]` 🍵 🔢 💲, 👆 💪 ✍ 🌅 🔃 ⚫️ Pydantic 🩺 🔃 <a href="https://docs.pydantic.dev/latest/concepts/models/#required-optional-fields" class="external-link" target="_blank">✔ 📦 🏑</a>.

### ⚙️ Pydantic `Required` ↩️ ❕ (`...`)

🚥 👆 💭 😬 ⚙️ `...`, 👆 💪 🗄 &amp; ⚙️ `Required` ⚪️➡️ Pydantic:

```Python hl_lines="2  8"

import warnings
from enum import Enum
from typing import Any, Callable, Dict, List, Optional, Sequence, Union

from fastapi.openapi.models import Example
from pydantic.fields import FieldInfo
from typing_extensions import Annotated, deprecated

from ._compat import PYDANTIC_V2, PYDANTIC_VERSION, Undefined

_Unset: Any = Undefined


class ParamTypes(Enum):
    query = "query"
    header = "header"
    path = "path"

**Spoiler alert**: il tutorial - Guida Utente include:

* Dichiarazione di **parameters** da altri posti diversi come: **headers**, **cookies**, **form fields** e **files**.
* Come stabilire **vincoli di validazione** come `maximum_length` o `regex`.

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and validated.

!!! check "Inspired **FastAPI** to"
    Use Python types to have great editor support.

            field.field_info.annotation
        ) and not isinstance(field.field_info, params.Body)

    def is_sequence_field(field: ModelField) -> bool:
        return field_annotation_is_sequence(field.field_info.annotation)

    def is_scalar_sequence_field(field: ModelField) -> bool:
        return field_annotation_is_scalar_sequence(field.field_info.annotation)