///

## Write the callback documentation code { #write-the-callback-documentation-code }

This code won't be executed in your app, we only need it to *document* how that *external API* should look like.

```

</div>

In the output, there's a line with something like:

```hl_lines="4"
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

That line shows the URL where your app is being served, in your local machine.

### Check it { #check-it }

    }
}
```

In this example, the "Proxy" could be something like **Traefik**. And the server would be something like FastAPI CLI with **Uvicorn**, running your FastAPI application.

### Providing the `root_path` { #providing-the-root-path }

To achieve this, you can use the command line option `--root-path` like:

<div class="termy">

```console

When we don't need to declare more validations or metadata, we can make the `q` query parameter required just by not declaring a default value, like:

```Python
q: str
```

instead of:

```Python
q: str | None = None
```

But we are now declaring it with `Query`, for example like:

//// tab | Annotated

```Python
q: Annotated[str | None, Query(min_length=3)] = None
```

////

But that file doesn't exist, our dependencies are in a file at `app/dependencies.py`.

Remember how our app/file structure looks like:

<img src="/img/tutorial/bigger-applications/package.drawio.svg">

---

The two dots `..`, like in:

```Python
from ..dependencies import get_token_header
```

mean:

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

* `datetime.date`:
    * Python `datetime.date`.
    * In requests and responses will be represented as a `str` in ISO 8601 format, like: `2008-09-15`.
* `datetime.time`:
    * A Python `datetime.time`.
    * In requests and responses will be represented as a `str` in ISO 8601 format, like: `14:23:55.003`.
* `datetime.timedelta`:

For example, you could use it to read and verify passwords generated by another system (like Django) but hash any new passwords with a different algorithm like Bcrypt.

And be compatible with all of them at the same time.

///

Create a utility function to hash a password coming from the user.

* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.
* It has a <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a> `async` interface.

---

This would be the parallel equivalent story for burgers. 🍔

For a more "real life" example of this, imagine a bank.

Up to recently, most of the banks had multiple cashiers 👨‍💼👨‍💼👨‍💼👨‍💼 and a big line 🕙🕙🕙🕙🕙🕙🕙🕙.

All of the cashiers doing all the work with one client after the other 👨‍💼⏯.

And you have to wait 🕙 in the line for a long time or you lose your turn.