Instead, use the actual default value of the function parameter. Otherwise, it would be inconsistent.

For example, this is not allowed:

```Python
q: Annotated[str, Query(default="rick")] = "morty"
```

...because it's not clear if the default value should be `"rick"` or `"morty"`.

So, you would use (preferably):

```Python
q: Annotated[str, Query()] = "rick"
```

> Requests is one of the most downloaded Python packages of all time

The way you use it is very simple. For example, to do a `GET` request, you would write:

```Python
response = requests.get("http://example.com/some/url")
```

The FastAPI counterpart API *path operation* could look like:

```Python hl_lines="1"
@app.get("/some/url")
def read_url():
    return {"message": "Hello World"}
```

So, you could add additional data to the automatically generated schema.

For example, you could decide to read and validate the request with your own code, without using the automatic features of FastAPI with Pydantic, but you could still want to define the request in the OpenAPI schema.

You could do that with `openapi_extra`:

    # For coverage
    # TODO: in theory this would allow declaring types that could be lists of bytes
    # to be read from files and other types, but I'm not even sure it's a good idea
    # to support it as a first class "feature"
    assert is_bytes_sequence_annotation(Union[list[str], list[bytes]])


def test_is_uploadfile_sequence_annotation():
    # For coverage

 * }
 * }
 *
 * @author Ben Yu
 * @since 12.0
 */
/*
 * A nullable bound would let users create a TypeParameter instance for a parameter with a nullable
 * bound. However, it would also let them create `new TypeParameter<@Nullable T>() {}`, which
 * wouldn't behave as users might expect. Additionally, it's not clear how the TypeToken API could
 * support even a "normal" `TypeParameter<T>` when `<T>` has a nullable bound. (See the discussion

It has a `GET` operation that could return an error.

It has a `POST` operation that could return several errors.

Both *path operations* require an `X-Token` header.

{* ../../docs_src/app_testing/app_b_an_py310/main.py *}

### Extended testing file { #extended-testing-file }

You could then update `test_main.py` with the extended tests:

            # as is just because it's an instance of a subclass of a more limited class
            # e.g. UserInDB (containing hashed_password) could be a subclass of User
            # that doesn't have the hashed_password. But because it's a subclass, it
            # would pass the validation and be returned as is.
            # By being a new field, no inheritance will be passed as is. A new model
            # will always be created.

Depending on your use case, you might prefer to use a different library, but if you asked me, I would probably suggest you try **Strawberry**.

Here's a small preview of how you could integrate Strawberry with FastAPI:

{* ../../docs_src/graphql_/tutorial001_py39.py hl[3,22,25] *}

For example, you could want to **return a dictionary** or a database object, but **declare it as a Pydantic model**. This way the Pydantic model would do all the data documentation, validation, etc. for the object that you returned (e.g. a dictionary or database object).

```Python hl_lines="1  4"
{!> ../../docs_src/python_types/tutorial008b_py39.py!}
```

////

In both cases this means that `item` could be an `int` or a `str`.

#### Possibly `None` { #possibly-none }

You can declare that a value could have a type, like `str`, but that it could also be `None`.

In Python 3.6 and above (including Python 3.10) you can declare it by importing and using `Optional` from the `typing` module.