In many cases your application could need some external settings or configurations, for example secret keys, database credentials, credentials for email services, etc.

Most of these settings are variable (can change), like database URLs. And many could be sensitive, like secrets.

For this reason it's common to provide them in environment variables that are read by the application.

## Environment Variables

!!! tip

### Project file structure

Let's say your project file structure looks like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
```

Now create a directory to store those static files.

Your new file structure could look like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
└── static/
```

### Download the files

You can easily adapt it to any database supported by SQLAlchemy, like:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is.

Later, for your production application, you might want to use a database server like **PostgreSQL**.

!!! tip

ledTemporaryFile" class="external-link" target="_blank">`SpooledTemporaryFile`</a> (ein <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a> Objekt). Das ist das tatsächliche Python-Objekt, das Sie direkt anderen Funktionen oder Bibliotheken übergeben können, welche ein „file-like“-Objekt erwarten.

`UploadFile` hat die folgenden `async`hronen Methoden. Sie alle rufen die entsprechenden Methoden des darunterliegenden...

    ```Python hl_lines="9"
    {!> ../../../docs_src/header_params/tutorial003.py!}
    ```

If you communicate with that *path operation* sending two HTTP headers like:

```
X-Token: foo
X-Token: bar
```

The response would be like:

```JSON
{
    "X-Token values": [
        "bar",
        "foo"
    ]
}
```

## Recap

# `Response` class

You can declare a parameter in a *path operation function* or dependency to be of type `Response` and then you can set data for the response like headers or cookies.

You can also use it directly to create an instance of it and return it from your *path operations*.

You can import it directly from `fastapi`:

```python
from fastapi import Response
```

But for those additional responses you have to make sure you return a `Response` like `JSONResponse` directly, with your status code and content.

## Additional Response with `model`

You can pass to your *path operation decorators* a parameter `responses`.

It receives a `dict`, the keys are status codes for each response, like `200`, and the values are other `dict`s with the information for each of them.

Let's start with an example and then see it in detail.

We create an async function `lifespan()` with `yield` like this:

```Python hl_lines="16  19"
{!../../../docs_src/events/tutorial003.py!}
```

Let's see how that works and how to change it if you need to do that.

## Pydantic Models for Input and Output

Let's say you have a Pydantic model with default values, like this one:

=== "Python 3.10+"

    ```Python hl_lines="7"
    {!> ../../../docs_src/separate_openapi_schemas/tutorial001_py310.py[ln:1-7]!}

    # Code below omitted 👇
    ```

    <details>

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

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

So, if you have an object `something` (that might _not_ be a function) and you can "call" it (execute it) like:

```Python
something()
```

or

```Python
something(some_argument, some_keyword_argument="foo")
```

then it is a "callable".