under the License.
-->

<!--
 | This is the toolchains file for Maven. It can be specified at two levels:
 |
 |  1. User Level. This toolchains.xml file provides configuration for a single user,
 |                 and is normally provided in ${user.home}/.m2/toolchains.xml.
 |
 |                 NOTE: This location can be overridden with the CLI option:
 |
 |                 -t /path/to/user/toolchains.xml
 |

}
```

## Recap

You can add multiple body parameters to your *path operation function*, even though a request can only have a single body.

But **FastAPI** will handle it, give you the correct data in your function, and validate and document the correct schema in the *path operation*.

You can also declare singular values to be received as part of the body.

  scheme: http
  static_configs:
  - targets: ['localhost:9000']
```

##### Node (optional)

Optionally you can also collect per node metrics. This needs to be done on a per server instance.
The scrape configurations should use all the servers under `targets` so that graphing systems like
grafana can visualize them for all the nodes

```yaml
scrape_configs:
- job_name: minio-job
  metrics_path: /minio/v2/metrics/node

    }

    public static String key(String groupId, String artifactId, String version) {
        notBlank(groupId, "groupId can neither be null, empty nor blank");
        notBlank(artifactId, "artifactId can neither be null, empty nor blank");
        notBlank(version, "version can neither be null, empty nor blank");

        return groupId + ":" + artifactId + ":" + version;
    }

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Several of these are explored in the next chapters of the tutorial.

## Order matters

When creating *path operations*, you can find situations where you have a fixed path.

# Declare Request Example Data

You can declare examples of the data your app can receive.

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

//// tab | Python 3.10+ Pydantic v2

```Python hl_lines="13-24"
{!> ../../docs_src/schema_extra_example/tutorial001_py310.py!}
```

////

```

////

The files and form fields will be uploaded as form data and you will receive the files and form fields.

And you can declare some of the files as `bytes` and some as `UploadFile`.

/// warning

    /**
     * Gets the decrypted proxies.
     *
     * @return The decrypted proxy, can be empty but never {@code null}.
     */
    List<Proxy> getProxies();

    /**
     * Gets the problems that were encountered during the settings decryption.
     *
     * @return The problems that were encountered during the decryption, can be empty but never {@code null}.
     */
    List<SettingsProblem> getProblems();

`@lru_cache` is part of `functools` which is part of Python's standard library, you can read more about it in the <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python docs for `@lru_cache`</a>.

## Recap

- we need to deal with plugins as core application logic which can also interact with plugins

* Along with this comes the testing strategies that make this work
* The repository model where plugins can be stored and cataloged
* Bridging this into an OSGi system: if this could be done then we can basically take over p2

TODO