This is normally called a **webhook**.

## Webhooks steps

The process normally is that **you define** in your code what is the message that you will send, the **body of the request**.

You also define in some way at which **moments** your app will send those requests or events.

And **your users** define in some way (for example in a web dashboard somewhere) the **URL** where your app should send those requests.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip
    When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

            if it should exclude from the output the fields that had the same default
            value, even when they were explicitly set.
            """
        ),
    ] = False,
    exclude_none: Annotated[
        bool,
        Doc(
            """
            Pydantic's `exclude_none` parameter, passed to Pydantic models to define

# `HTTPConnection` class

When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

You can import it from `fastapi.requests`:

```python
from fastapi.requests import HTTPConnection
```

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.

* API usage monitoring systems
* response data injection systems
* etc.

## Simple and Powerful

Although the hierarchical dependency injection system is very simple to define and use, it's still very powerful.

You can define dependencies that in turn can define dependencies themselves.

#### "*Schema*"

Um "*schema*" é uma definição ou descrição de algo. Não o código que o implementa, mas apenas uma descrição abstrata.

#### API "*schema*"

Nesse caso, <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank">OpenAPI</a> é uma especificação que determina como definir um *schema* da sua API.

It is provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi import WebSocket
```

!!! tip
    When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

::: fastapi.WebSocket
    options:
        members:
            - scope
            - app

So, you could add additional data to the automatically generated schema.

For example, you could decide to read and validate the request with your own code, without using the automatic features of FastAPI with Pydantic, but you could still want to define the request in the OpenAPI schema.

You could do that with `openapi_extra`:

```Python hl_lines="20-37  39-40"

# 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.