It would also mean that if you get data from the `Request` object directly (for example, read the body) it won't be validated, converted or documented (with OpenAPI, for the automatic API user interface) by FastAPI.

Although any other parameter declared normally (for example, the body with a Pydantic model) would still be validated, converted, annotated, etc.

But there are specific cases where it's useful to get the `Request` object.

a `response_class` with a JSON media type (`application/json`), like is the case with the `JSONResponse`, the data you return will be automatically converted (and filtered) with any Pydantic `response_model` that you declared in the *path operation decorator*. But the data won't be serialized to JSON bytes with Pydantic, instead it will be converted with the `jsonable_encoder` and then passed to the `JSONResponse` class, which will serialize it to bytes using the standard JSON library in Python....

You couldn't get this kind of editor support if you were working directly with `dict` instead of Pydantic models.

But you don't have to worry about them either, incoming dicts are converted automatically and your output is converted automatically to JSON too.

## Bodies of arbitrary `dict`s { #bodies-of-arbitrary-dicts }

You can also declare a body as a `dict` with keys of some type and values of some other type.

For example, you cannot put a Pydantic model in a `JSONResponse` without first converting it to a `dict` with all the data types (like `datetime`, `UUID`, etc) converted to JSON-compatible types.

For those cases, you can use the `jsonable_encoder` to convert your data before passing it to a response:

{* ../../docs_src/response_directly/tutorial001_py310.py hl[5:6,20:21] *}

/// note | Technical Details

* `skip`: with a value of `0`
* `limit`: with a value of `10`

As they are part of the URL, they are "naturally" strings.

But when you declare them with Python types (in the example above, as `int`), they are converted to that type and validated against it.

All the same process that applied for path parameters also applies for query parameters:

* Editor support (obviously)

For example, it doesn't receive `datetime` objects, as those are not compatible with JSON.

So, a `datetime` object would have to be converted to a `str` containing the data in [ISO format](https://en.wikipedia.org/wiki/ISO_8601).

The same way, this database wouldn't receive a Pydantic model (an object with attributes), only a `dict`.

You can use `jsonable_encoder` for that.

* `frozenset`:
    * In requests and responses, treated the same as a `set`:
        * In requests, a list will be read, eliminating duplicates and converting it to a `set`.
        * In responses, the `set` will be converted to a `list`.
        * The generated schema will specify that the `set` values are unique (using JSON Schema's `uniqueItems`).
* `bytes`:
    * Standard Python `bytes`.
    * In requests and responses will be treated as `str`.

        List<Object> resultList = (List<Object>) result;
        assertEquals(3, resultList.size());

        // First element should be converted to Map since it's an Entity
        assertTrue(resultList.get(0) instanceof Map);
        // All elements are converted by BeanUtil.copyBeanToNewMap when first element is Entity
        assertTrue(resultList.get(1) instanceof Map);
        assertTrue(resultList.get(2) instanceof Map);

 * lookups.
 *
 * <p>During construction, names are normalized in two ways:
 *
 * <ol>
 *   <li>ASCII uppercase characters are converted to lowercase.
 *   <li>Unicode dot separators other than the ASCII period ({@code '.'}) are converted to the ASCII
 *       period.
 * </ol>
 *
 * <p>The normalized values will be returned from {@link #toString()} and {@link #parts()}, and will

You can also use `dataclasses` in the `response_model` parameter:

{* ../../docs_src/dataclasses_/tutorial002_py310.py hl[1,6:12,18] *}

The dataclass will be automatically converted to a Pydantic dataclass.

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">