#!/usr/bin/env bash

echo "script failed" >resiliency-verify-healing.log # assume initial state

# Extract arguments from json object ...
FILE=$(echo $1 | jq -r '.args.file')
DIR=$(echo $1 | jq -r '.args.dir')
DEEP=$(echo $1 | jq -r '.args.deep')
WANT=$(echo $1 | jq 'del(.args)') # ... and remove args from wanted result

ALIAS_NAME=myminio
BUCKET="test-bucket"

* cross origin: cross origin (do not translate to "origem cruzada")
* Cross-Origin Resource Sharing: Cross-Origin Resource Sharing (do not translate to "Compartilhamento de Recursos de Origem Cruzada")
* Deep Learning: Deep Learning (do not translate to "Aprendizado Profundo")
* dependable: dependable
* dependencies: dependências
* deprecated: descontinuado
* docs: documentação
* FastAPI app: aplicação FastAPI

 */
@Deprecated(since = "4.0.0")
public interface ProfileInjector {

    /**
     * Merges values from the specified profile into the given model. Implementations are expected to keep the profile
     * and model completely decoupled by injecting deep copies rather than the original objects from the profile.
     *
     * @param model The model into which to merge the values defined by the profile, must not be <code>null</code>.

* back and forth: de un lado a otro
* I/O (as in "input and output"): I/O (do not translate to "E/S")
* Machine Learning: Machine Learning (do not translate to "Aprendizaje Automático")
* Deep Learning: Deep Learning (do not translate to "Aprendizaje Profundo")
* callback hell: callback hell (do not translate to "infierno de callbacks")
* tip: Consejo (do not translate to "tip")

        assertEquals(p.getRepositories().size(), clone.getRepositories().size());
        // TODO deep compare the lists
        assertEquals(
                p.getPluginRepositories().size(), clone.getPluginRepositories().size());
        // TODO deep compare the lists
    }

    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":
        return {"model_name": model_name, "message": "LeCNN all the images"}

		Recursive: true,                  // recursively heal all objects at 'prefix'
		Remove:    true,                  // remove content that has lost quorum and not recoverable
		ScanMode:  madmin.HealNormalScan, // by default do not do 'deep' scanning
	}

	start, _, err := madmClnt.Heal(context.Background(), "healing-rewrite-bucket", "", opts, "", false, false)
	if err != nil {
		log.Fatalln(err)
	}
	fmt.Println("Healstart sequence ===")

client = TestClient(app)


def test_get_enums_alexnet():
    response = client.get("/models/alexnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}


def test_get_enums_lenet():
    response = client.get("/models/lenet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "lenet", "message": "LeCNN all the images"}

@Deprecated(since = "4.0.0")
public interface InheritanceAssembler {

    /**
     * Merges values from the specified parent model into the given child model. Implementations are expected to keep
     * parent and child completely decoupled by injecting deep copies of objects into the child rather than the original
     * objects from the parent.
     *

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):