systems is data "<abbr title="also called marshalling, conversion">serialization</abbr>" which is taking data from the code (Python) and converting it into something that can be sent through the network. For example, converting an object containing data from a database into a JSON object. Converting `datetime` objects into strings, etc.

Another big feature needed by APIs is data validation, making sure that the data is valid, given certain parameters. For example, that some field is an `int`,...

## Parameterized dependencies { #parameterized-dependencies }

All the dependencies we have seen are a fixed function or class.

But there could be cases where you want to be able to set parameters on the dependency, without having to declare many different functions or classes.

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.

<img src="/img/tutorial/dependencies/image02.png">

## Shortcut { #shortcut }

But you see that we are having some code repetition here, writing `CommonQueryParams` twice:

//// tab | Python 3.9+

```Python
commons: Annotated[CommonQueryParams, Depends(CommonQueryParams)]
```

////

But you can still document it as described in [Additional Responses in OpenAPI](additional-responses.md){.internal-link target=_blank}.

It also re-declares `id: int`. By doing this, we are making a **contract** with the API clients, so that they can always expect the `id` to be there and to be an `int` (it will never be `None`).

/// tip

Having the return model ensure that a value is always available and always `int` (not `None`) is very useful for the API clients, they can write much simpler code having this certainty.

/// note

FastAPI will know that the value of `q` is not required because of the default value `= None`.

Having `str | None` will allow your editor to give you better support and detect errors.

///

## Additional validation { #additional-validation }

}

func (c chainG[T]) Group(name string) ChainInterface[T] {
	return c.with(func(db *DB) *DB {
		return db.Group(name)
	})
}

func (c chainG[T]) Having(query interface{}, args ...interface{}) ChainInterface[T] {
	return c.with(func(db *DB) *DB {
		return db.Having(query, args...)
	})
}

func (c chainG[T]) Order(value interface{}) ChainInterface[T] {
	return c.with(func(db *DB) *DB {
		return db.Order(value)
	})

            attributes.attribute(minified, java.lang.Boolean.FALSE)
        }
        /*
         * It would perhaps be better to do this more selectively instead of applying this transform so broadly and having
         * it just no-op in most cases.
         */
        registerTransform(Minify::class) {
            from.attribute(minified, false).attribute(artifactType, "jar")

```

...this would work:

```JSON
{
    "item_id": "foo-item",
    "needy": "sooooneedy"
}
```

And of course, you can define some parameters as required, some as having a default value, and some entirely optional:

{* ../../docs_src/query_params/tutorial006_py310.py hl[8] *}

In this case, there are 3 query parameters:

* `needy`, a required `str`.

                logStrategyResult(context, strategy, strategyResult);

            } catch (Exception e) {
                context.failure("Strategy failed: " + e.getMessage());
                // Mark all POMs as having errors for this strategy
                UpgradeResult errorResult = new UpgradeResult(pomMap.keySet(), java.util.Set.of(), pomMap.keySet());
                overallResult = overallResult.merge(errorResult);
            } finally {