```Python hl_lines="1  4"
{!> ../../docs_src/python_types/tutorial008b.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.

│   └── main.py
```

In the file `main.py` you have your **FastAPI** app:


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

### Testing file { #testing-file }

Then you could have a file `test_main.py` with your tests. It could live on the same Python package (the same directory with a `__init__.py` file):

``` hl_lines="5"
.
├── app
│   ├── __init__.py
│   ├── main.py
│   └── test_main.py
```

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 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 <a href="https://en.wikipedia.org/wiki/ISO_8601" class="external-link" target="_blank">ISO format</a>.

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.

             to quit<b>)</b>
```

</div>

That would work for most of the cases. 😎

You could use that command for example to start your **FastAPI** app in a container, in a server, etc.

## ASGI Servers { #asgi-servers }

Let's go a little deeper into the details.

        "needy"
      ],
      "msg": "Field required",
      "input": null
    }
  ]
}
```

As `needy` is a required parameter, you would need to set it in the URL:

```
http://127.0.0.1:8000/items/foo-item?needy=sooooneedy
```

...this would work:

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

```Python
{"id": id}
```

For example, with an ID of `42`, this would render:

```html
Item ID: 42
```

### Template `url_for` Arguments { #template-url-for-arguments }

You can also use `url_for()` inside of the template, it takes as arguments the same arguments that would be used by your *path operation function*.

So, the section with:

{% raw %}

```jinja

It's possible to upload several files at the same time.

They would be associated to the same "form field" sent using "form data".

To use that, declare a list of `bytes` or `UploadFile`:

{* ../../docs_src/request_files/tutorial002_an_py39.py hl[10,15] *}

You will receive, as declared, a `list` of `bytes` or `UploadFile`s.

/// note | Technical Details

You could also use `from starlette.responses import HTMLResponse`.

In the next chapter about [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank} I'll explain some strategies you could use to handle the other **deployment concepts**.

I'll show you how to **build your own image from scratch** to run a single Uvicorn process. It is a simple process and is probably what you would want to do when using a distributed container management system like **Kubernetes**.

## Recap { #recap }

We can do better...

## What makes a dependency { #what-makes-a-dependency }

Up to now you have seen dependencies declared as functions.

But that's not the only way to declare dependencies (although it would probably be the more common).

The key factor is that a dependency should be a "callable".

A "**callable**" in Python is anything that Python can "call" like a function.