## 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.

Let's imagine that we want to have a dependency that checks if the query parameter `q` contains some fixed content.

But we want to be able to parameterize that fixed content.

## A "callable" instance

In Python there's a way to make an instance of a class a "callable".

Not the class itself (which is already a callable), but an instance of that class.

To do that, we declare a method `__call__`:

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

### Declare the dependency, in the "dependant"

The same way you use `Body`, `Query`, etc. with your *path operation function* parameters, use `Depends` with a new parameter:

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[13,18] *}

Although you use `Depends` in the parameters of your function the same way you use `Body`, `Query`, etc, `Depends` works a bit differently.

# Body - Fields

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field`

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

"CA","PlateExpiry":"201503","Make":"NISS","BodyStyle":"PA","Color":"BK","Location":"200 WORLD WAY","Route":"2R2","Agency":2,"ViolationCode":"8939","ViolationDescr":"WHITE CURB","Fine":58,"Latitude":6439997.9,"Longitude":1802686.4} {"Ticket":1104820732,"IssueData":"2015-12-26T00:00:00","IssueTime":"1515","RPState":"CA","PlateExpiry":"","Make":"ACUR","BodyStyle":"PA","Color":"WH","Location":"100 WORLD WAY","Route":"2F11","Agency":2,"ViolationCode":"000","ViolationDescr":"17104h","Fine":"","Latitud...

</blockquote>

## Investigation

By using all the previous alternatives I had the chance to learn from all of them, take ideas, and combine them in the best way I could find for myself and the teams of developers I have worked with.

///

/// tip

Here we reuse the same Pydantic model.

But the same way, we could have validated it in some other way.

# MinIO Grid

The MinIO Grid is a package that provides two-way communication between servers.
It uses a single two-way connection to send and receive messages between servers.

It includes built in muxing of concurrent requests as well as congestion handling for streams.

Requests can be "Single Payload" or "Streamed".

Use the MinIO Grid for:

* Small, frequent requests with low latency requirements.

**FastAPI** provides several tools to help you deal with **Security** easily, rapidly, in a standard way, without having to study and learn all the security specifications.

But first, let's check some small concepts.

## In a hurry?