///

An environment variable (also known as "**env var**") is a variable that lives **outside** of the Python code, in the **operating system**, and could be read by your Python code (or by other programs as well).

Environment variables could be useful for handling application **settings**, as part of the **installation** of Python, etc.

## Create and Use Env Vars

     * @return The deserialized metadata, never {@code null}.
     * @throws IOException If the metadata could not be deserialized.
     * @throws MetadataParseException If the input format could not be parsed.
     */
    Metadata read(File input, Map<String, ?> options) throws IOException, MetadataParseException;

    /**

     * @return The deserialized settings, never {@code null}.
     * @throws IOException If the settings could not be deserialized.
     * @throws SettingsParseException If the input format could not be parsed.
     */
    Settings read(File input, Map<String, ?> options) throws IOException, SettingsParseException;

    /**

     * @return The deserialized toolchains, never {@code null}.
     * @throws IOException If the toolchains could not be deserialized.
     * @throws ToolchainsParseException If the input format could not be parsed.
     */
    PersistedToolchains read(File input, Map<String, ?> options) throws IOException, ToolchainsParseException;

    /**

Now, let's see how you could use that to return a custom response.

Let's say that you want to return an <a href="https://en.wikipedia.org/wiki/XML" class="external-link" target="_blank">XML</a> response.

# OpenAPI Callbacks

You could create an API with a *path operation* that could trigger a request to an *external API* created by someone else (probably the same developer that would be *using* your API).

This client could be a browser with a frontend, a code from someone else, an IoT device, etc.

You could need to tell the client that:

* The client doesn't have enough privileges for that operation.
* The client doesn't have access to that resource.
* The item the client was trying to access doesn't exist.
* etc.

If you use a `requirements.txt` file you could specify the version with:

```txt
fastapi[standard]==0.112.0
```

that would mean that you would use exactly the version `0.112.0`.

Or you could also pin it with:

```txt
fastapi[standard]>=0.112.0,<0.113.0
```

│   └── main.py
```

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


```Python
{!../../docs_src/app_testing/main.py!}
```

### 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`:

```Python hl_lines="19-36  39-40"