"operationId": "read_items_items__get",
                    "parameters": [
                        {
                            "description": "Query string for the items to search in the database that have a good match",
                            "required": False,
                            "deprecated": True,
                            "schema": IsDict(
                                {

            bool,
            Doc(
                """
                Configuration passed to Pydantic to define if the response data
                should have all the fields, including the ones that were not set and
                have their default values. This is different from
                `response_model_exclude_defaults` in that if the fields are set,

# Extra Data Types

Up to now, you have been using common data types, like:

* `int`
* `float`
* `str`
* `bool`

But you can also use more complex data types.

And you will still have the same features as seen up to now:

* Great editor support.
* Data conversion from incoming requests.
* Data conversion for response data.
* Data validation.
* Automatic annotation and documentation.

## Other data types

```Python hl_lines="4  11  15-18"
{!../../../docs_src/templates/tutorial001.py!}
```

!!! note
    Antes do FastAPI 0.108.0, Starlette 0.29.0, `name` era o primeiro parâmetro.

    Além disso, em versões anteriores, o objeto `request` era passado como parte dos pares chave-valor no "context" dict para o Jinja2.

            "user": {"username": "Dave"},
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 5,
        "importance": 2,
        "item": {
            "name": "Foo",
            "price": 50.5,
            "description": None,
            "tax": None,
        },
        "user": {"username": "Dave", "full_name": None},
    }

            "user": {"username": "Dave"},
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 5,
        "importance": 2,
        "item": {
            "name": "Foo",
            "price": 50.5,
            "description": None,
            "tax": None,
        },
        "user": {"username": "Dave", "full_name": None},
    }

            "user": {"username": "Dave"},
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 5,
        "importance": 2,
        "item": {
            "name": "Foo",
            "price": 50.5,
            "description": None,
            "tax": None,
        },
        "user": {"username": "Dave", "full_name": None},
    }


@needs_py310

### Check the docs

Now you can start your app and go to <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>.

You will see your docs have the normal *path operations* and now also some **webhooks**:

Quando tem uma operação que exigirá espera antes de dar os resultados e tem suporte para esses recursos Python, você pode escrever assim:

```Python
burgers = await get_burgers(2)
```

{!../../../docs_src/custom_response/tutorial007.py!}
```

#### Using `StreamingResponse` with file-like objects

If you have a file-like object (e.g. the object returned by `open()`), you can create a generator function to iterate over that file-like object.

That way, you don't have to read it all first in memory, and you can pass that generator function to the `StreamingResponse`, and return it.