# Security Tools

When you need to declare dependencies with OAuth2 scopes you use `Security()`.

But you still need to define what is the dependable, the callable that you pass as a parameter to `Depends()` or `Security()`.

There are multiple tools that you can use to create those dependables, and they get integrated into OpenAPI so they are shown in the automatic docs UI, they can be used by automatically generated clients and SDKs, etc.

# Parâmetros de Cabeçalho

Você pode definir parâmetros de Cabeçalho da mesma maneira que define paramêtros com `Query`, `Path` e `Cookie`.

## importe `Header`

Primeiro importe `Header`:

=== "Python 3.10+"

    ```Python hl_lines="1"
    {!> ../../../docs_src/header_params/tutorial001_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="3"
    {!> ../../../docs_src/header_params/tutorial001.py!}
    ```

#### "Schema"

Un "schema" es una definición o descripción de algo. No es el código que la implementa, sino solo una descripción abstracta.

#### "Schema" de la API

En este caso, <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank">OpenAPI</a> es una especificación que dicta como se debe definir el schema de tu API.

=== "Python 3.8+ non-Annotated"

    !!! tip
        Prefer to use the `Annotated` version if possible.

    ```Python hl_lines="1"
    {!> ../../../docs_src/request_forms/tutorial001.py!}
    ```

## Define `Form` parameters

Create form parameters the same way you would for `Body` or `Query`:

=== "Python 3.9+"

    ```Python hl_lines="9"
    {!> ../../../docs_src/request_forms/tutorial001_an_py39.py!}
    ```

!!! tip
    To avoid confusion between the Peewee *models* and the Pydantic *models*, we will have the file `models.py` with the Peewee models, and the file `schemas.py` with the Pydantic models.

    These Pydantic models define more or less a "schema" (a valid data shape).

    So this will help us avoiding confusion while using both.

### Create the Pydantic *models* / schemas

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`

!!! tip
    To avoid confusion between the SQLAlchemy *models* and the Pydantic *models*, we will have the file `models.py` with the SQLAlchemy models, and the file `schemas.py` with the Pydantic models.

    These Pydantic models define more or less a "schema" (a valid data shape).

    So this will help us avoiding confusion while using both.

### Create initial Pydantic *models* / schemas

    You can use a closing code from the <a href="https://tools.ietf.org/html/rfc6455#section-7.4.1" class="external-link" target="_blank">valid codes defined in the specification</a>.

### Try the WebSockets with dependencies

If your file is named `main.py`, run your application with:

<div class="termy">

```console
$ fastapi dev main.py

    ```

## `Union` or `anyOf`

You can declare a response to be the `Union` of two types, that means, that the response would be any of the two.

It will be defined in OpenAPI with `anyOf`.

To do that, use the standard Python type hint <a href="https://docs.python.org/3/library/typing.html#typing.Union" class="external-link" target="_blank">`typing.Union`</a>:

!!! note

* Valida **estructuras complejas**:
    * Usa modelos jerárquicos de modelos de Pydantic, `typing` de Python,  `List` y `Dict`, etc.