```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info
    `**second_user_data` means:

    Pass the keys and values of the `second_user_data` dict directly as key-value arguments, equivalent to: `User(id=4, name="Mary", joined="2018-11-30")`

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.
    * Query parameters.

#### Data "schema"

The term "schema" might also refer to the shape of some data, like a JSON content.

In that case, it would mean the JSON attributes, and data types they have, etc.

#### OpenAPI and JSON Schema

# OpenAPI Webhooks

There are cases where you want to tell your API **users** that your app could call *their* app (sending a request) with some data, normally to **notify** of some type of **event**.

This means that instead of the normal process of your users sending requests to your API, it's **your API** (or your app) that could **send requests to their system** (to their API, their app).

This is normally called a **webhook**.

## Webhooks steps

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.
    * Query parameters.

    # Uvicorn with uvloop
    "uvicorn[standard] >=0.12.0",
    # TODO: this should be part of some pydantic optional extra dependencies
    # # Settings management
    # "pydantic-settings >=2.0.0",
    # # Extra Pydantic data types
    # "pydantic-extra-types >=2.0.0",
]

all = [
    "fastapi-cli >=0.0.2",
    # # For the test client
    "httpx >=0.23.0",
    # For templates
    "jinja2 >=2.11.2",

In your WebSocket route you can `await` for messages and send messages.

```Python hl_lines="48-52"
{!../../../docs_src/websockets/tutorial001.py!}
```

You can receive and send binary, text, and JSON data.

## Try it

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

<div class="termy">

```console
$ fastapi dev main.py

```

But possibly the most important part of the callback is making sure that your API user (the external developer) implements the *external API* correctly, according to the data that *your API* is going to send in the request body of the callback, etc.

So, what we will do next is add the code to document how that *external API* should look like to receive the callback from *your API*.

| `minio_cluster_iam_since_last_sync_millis`                      | `counter` | Time (in milliseconds) since last successful IAM data sync                                                               |        |
| `minio_cluster_iam_sync_failures`                               | `counter` | Number of failed IAM data syncs since server start                                                                       |        |

Next it will convert and validate the data. So, when you use that `settings` object, you will have data of the types you declared (e.g. `items_per_user` will be an `int`).

### Use the `settings`

Then you can use the new `settings` object in your application:

```Python hl_lines="18-20"