Profile p = Profile.newBuilder().activation(a).build();

        return p;
    }

    private Properties newProperties(String osName, String osVersion, String osArch) {
        Properties props = new Properties();
        props.setProperty("os.name", osName);
        props.setProperty("os.version", osVersion);
        props.setProperty("os.arch", osArch);
        return props;
    }

    @Test

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

You actually don't have users that log in to your application but robots, bots, or other systems, that have just an access token? Again, it all works the same.

///

## Declare model attributes

You can then use `Field` with model attributes:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` works the same way as `Query`, `Path` and `Body`, it has all the same parameters, etc.

/// note | "Technical Details"

```

### Testing file

Then you could have a file `test_main.py` with your tests. It could live on the same Python package (the same directory with a `__init__.py` file):

``` hl_lines="5"
.
├── app
│   ├── __init__.py
│   ├── main.py
│   └── test_main.py
```

Because this file is in the same package, you can use relative imports to import the object `app` from the `main` module (`main.py`):

```Python hl_lines="3"

#### Fix it with `secrets.compare_digest()`

But in our code we are actually using `secrets.compare_digest()`.

In short, it will take the same time to compare `stanleyjobsox` to `stanleyjobson` than it takes to compare `johndoe` to `stanleyjobson`. And the same for the password.

That way, using `secrets.compare_digest()` in your application code, it will be safe against this whole range of security attacks.

After that, all of the processing logic is the same.

But because of our changes in `GzipRequest.body`, the request body will be automatically decompressed when it is loaded by **FastAPI** when needed.

## Accessing the request body in an exception handler

/// tip

### Same Schema for Input and Output Models in Docs

And now there will be one single schema for input and output for the model, only `Item`, and it will have `description` as **not required**:

<div class="screenshot">
<img src="/img/tutorial/separate-openapi-schemas/image05.png">
</div>

 * supplied object is the root. Expressions like 'child.name' will translate into
 * 'rootObject.getChild().getName()' for non-boolean properties, and
 * 'rootObject.getChild().isName()' for boolean properties.
 *
 * @deprecated use {@link org.apache.maven.api.services.ModelBuilder} instead
 */
@Deprecated(since = "4.0.0")
public class ObjectBasedValueSource extends AbstractValueSource {

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.

# Cookie Parameters

You can define Cookie parameters the same way you define `Query` and `Path` parameters.

## Import `Cookie`

First import `Cookie`:

//// tab | Python 3.10+

```Python hl_lines="3"
{!> ../../docs_src/cookie_params/tutorial001_an_py310.py!}
```

////

//// tab | Python 3.9+

```Python hl_lines="3"
{!> ../../docs_src/cookie_params/tutorial001_an_py39.py!}
```

////