```bash
helm get values my-release > old_values.yaml
```

Then change the field `image.tag` in `old_values.yaml` file with MinIO image tag you want to use. Now update the chart using

```bash
helm upgrade -f old_values.yaml my-release minio/minio
```

Default upgrade strategies are specified in the `values.yaml` file. Update these fields if you'd like to use a different strategy.

### Configuration

	}{
		{
			config:      "testdata/config/1.yaml",
			expectedErr: false,
			hash:        "hash:02bf70285dc71f76",
		},
		{
			config:      "testdata/config/2.yaml",
			expectedErr: false,
			hash:        "hash:676d2da00f71f205",
		},
		{
			config:      "testdata/config/invalid.yaml",
			expectedErr: true,
		},
		{
			config:      "testdata/config/invalid-types.yaml",
			expectedErr: true,
		},
		{

    delay: 500ms # least amount of delay between each retry
`
	var job BatchJobRequest
	err := yaml.Unmarshal([]byte(expireYaml), &job)
	if err != nil {
		t.Fatal("Failed to parse batch-job-expire yaml", err)
	}
	if !slices.Equal(job.Expire.Prefix.F(), []string{"myprefix"}) {
		t.Fatal("Failed to parse batch-job-expire yaml")
	}

	multiPrefixExpireYaml := `
expire: # Expire objects that match a condition
  apiVersion: v1

        x - x-men
        x - x-avengers
        """
    response = client.post("/items/", content=yaml_data)
    assert response.status_code == 422, response.text
    assert response.json() == {"detail": "Invalid YAML"}


def test_post_invalid(client: TestClient):
    yaml_data = """
        name: Deadpoolio
        tags:
        - x-force
        - x-men
        - x-avengers
        - sneaky: object
        """

Luego usamos el request directamente, y extraemos el cuerpo como `bytes`. Esto significa que FastAPI ni siquiera intentará parsear la carga útil del request como JSON.

Y luego en nuestro código, parseamos ese contenido YAML directamente, y nuevamente estamos usando el mismo modelo Pydantic para validar el contenido YAML:

//// tab | Pydantic v2

Então utilizamos a requisição diretamente, e extraímos o corpo como `bytes`. Isso significa que o FastAPI não vai sequer tentar analisar o corpo da requisição como JSON.

E então no nosso código, nós analisamos o conteúdo YAML diretamente, e estamos utilizando o mesmo modelo Pydantic para validar o conteúdo YAML:

//// tab | Pydantic v2

{* ../../docs_src/path_operation_advanced_configuration/tutorial007_py39.py hl[15:20, 22] *}

Obwohl wir nicht die standardmäßig integrierte Funktionalität verwenden, verwenden wir dennoch ein Pydantic-Modell, um das JSON-Schema für die Daten, die wir in YAML empfangen möchten, manuell zu generieren.

{* ../../docs_src/path_operation_advanced_configuration/tutorial007.py hl[17:22,24] *}

Néanmoins, bien que nous n'utilisions pas la fonctionnalité par défaut, nous utilisons toujours un modèle Pydantic pour générer manuellement le schéma JSON pour les données que nous souhaitons recevoir en YAML.

## 2. Run Distributed MinIO on Docker Compose

import logging
import secrets
import subprocess
from pathlib import Path

import yaml
from github import Github
from pydantic import BaseModel, SecretStr
from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    github_repository: str
    github_token: SecretStr


class Repo(BaseModel):
    name: str
    html_url: str
    stars: int
    owner_login: str
    owner_html_url: str