Historically, Gradle has shipped with some Groovy types in very prominent APIs.
This required the Kotlin DSL to add special integration to work with Groovy closures.
This has also forced plugins written in languages other than Groovy to use Groovy types for some APIs.

When the Kotlin DSL was introduced, we made an effort to add non-Groovy equivalents for all APIs.

You can verify it in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/request-form-models/image01.png">
</div>

## Forbid Extra Form Fields { #forbid-extra-form-fields }

In some special use cases (probably not very common), you might want to **restrict** the form fields to only those declared in the Pydantic model. And **forbid** any **extra** fields.

/// note

The **Advanced User Guide** builds on this one, uses the same concepts, and teaches you some extra features.

But you should first read the **Tutorial - User Guide** (what you are reading right now).

   * the discussion in the {@link #addListener} documentation. All its warnings about heavyweight
   * listeners are also applicable to heavyweight functions passed to this method.
   *
   * <p>This method is similar to {@link java.util.concurrent.CompletableFuture#exceptionally}. It
   * can also serve some of the use cases of {@link java.util.concurrent.CompletableFuture#handle}

## Forbid Extra Query Parameters { #forbid-extra-query-parameters }

In some special use cases (probably not very common), you might want to **restrict** the query parameters that you want to receive.

You can use Pydantic's model configuration to `forbid` any `extra` fields:

{* ../../docs_src/query_param_models/tutorial002_an_py310.py hl[10] *}

    response = client.put(
        "/items/123",
        json={"name": "Foo", "price": 50.1, "description": "Some Foo", "tax": 0.3},
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 123,
        "name": "Foo",
        "price": 50.1,
        "description": "Some Foo",
        "tax": 0.3,
    }


def test_put_only_required(client: TestClient):
    response = client.put(

## Code includes with unknown attributes { #code-includes-with-unknown-attributes }

{* ../../docs_src/python_types/tutorial001_py310.py unknown[123] *}

## Some more code includes to test fixing { #some-more-code-includes-to-test-fixing }

{* ../../docs_src/dependencies/tutorial013_an_py310.py ln[19:21] *}

            }
            // Simulate some encoding activity on the buffer
            dst.enc_ndr_long(123);
        }

        @Override
        public void decode(NdrBuffer src) throws NdrException {
            if (throwOnDecode) {
                throw new NdrException("Failed to decode");
            }
            // Simulate some decoding activity on the buffer
            src.dec_ndr_long();

```json
{
    "description": "Some data",
    "data": "aGVsbG8="
}
```

/// tip | Tipp

`aGVsbG8=` ist die base64-Kodierung von `hello`.

///

Anschließend dekodiert Pydantic den base64-String und stellt Ihnen die ursprünglichen Bytes im Feld `data` des Modells bereit.

Sie erhalten eine Response wie:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

       *
       * TODO(b/112550045): Allocating a single, cheaper listener is (I think) only an optimization.
       * If we make some other optimizations, this one will no longer be necessary. The optimization
       * could actually hurt in some cases, as it forces us to keep all inputs in memory until the
       * final input completes.
       */
      @RetainedLocalRef