package cmd

import (
	"slices"
	"testing"

	"gopkg.in/yaml.v3"
)

func TestBatchJobPrefix_UnmarshalYAML(t *testing.T) {
	type args struct {
		yamlStr string
	}
	type PrefixTemp struct {
		Prefix BatchJobPrefix `yaml:"prefix"`
	}
	tests := []struct {
		name    string
		b       PrefixTemp
		args    args
		want    []string
		wantErr bool

          black-list-labels:
            - '>test-mute'
    axes:
      - axis:
          type: slave
          name: nodes
          values:
            - "general-purpose"
      - axis:
          type: yaml
          filename: ".ci/bwcVersions"
          name: "BWC_VERSION"
    builders:
      - inject:
          properties-file: '.ci/java-versions.properties'
          properties-content: |

{* ../../docs_src/path_operation_advanced_configuration/tutorial007_py310.py hl[15:20, 22] *}

それでも、デフォルトの統合機能を使っていないにもかかわらず、YAMLで受け取りたいデータのために、Pydanticモデルを使って手動でJSON Schemaを生成しています。

そしてリクエストを直接使い、ボディを `bytes` として抽出します。これは、FastAPIがリクエストペイロードをJSONとしてパースしようとすらしないことを意味します。

その後、コード内でそのYAMLコンテンツを直接パースし、さらに同じPydanticモデルを使ってYAMLコンテンツを検証しています。

---
jjbb-template: matrix-gradle-unix.yml
vars:
  - job-name: elastic+elasticsearch+%BRANCH%+periodic+java-fips-matrix
  - job-display-name: "elastic / elasticsearch # %BRANCH% - java fips compatibility matrix"
  - job-description: "Testing of the Elasticsearch %BRANCH% branch java FIPS compatibility matrix.\n"
  - matrix-yaml-file: ".ci/matrix-runtime-javas-fips.yml"
  - matrix-variable: ES_RUNTIME_JAVA

themselves can be written in either Java or with a YAML based DSL.

YAML based REST tests should be preferred since these are shared between all
the elasticsearch official clients. The YAML based tests describe the
operations to be executed and the obtained results that need to be tested.

例如，在这个应用中我们不使用 FastAPI 集成的从 Pydantic 模型提取 JSON Schema 的功能，也不使用对 JSON 的自动校验。实际上，我们将请求的内容类型声明为 YAML，而不是 JSON：

{* ../../docs_src/path_operation_advanced_configuration/tutorial007_py310.py hl[15:20, 22] *}

尽管我们没有使用默认的集成功能，我们仍然使用 Pydantic 模型手动生成我们想以 YAML 接收的数据的 JSON Schema。

然后我们直接使用请求并将请求体提取为 `bytes`。这意味着 FastAPI 甚至不会尝试将请求负载解析为 JSON。

接着在我们的代码中，我们直接解析该 YAML 内容，然后再次使用同一个 Pydantic 模型来验证该 YAML 内容：

        OutputStream jsonOutput = SearchEngineUtil.getXContentBuilderOutputStream(callback, XContentType.JSON);
        assertNotNull(jsonOutput);

        // Test with YAML
        OutputStream yamlOutput = SearchEngineUtil.getXContentBuilderOutputStream(callback, XContentType.YAML);
        assertNotNull(yamlOutput);
    }

    @Test
    public void test_getXContentOutputStream_success() {
        ToXContent xContent = new ToXContent() {

        )
    data = [repo.model_dump() for repo in final_repos]

    # Local development
    # repos_path = Path("../docs/en/data/topic_repos.yml")
    repos_path = Path("./docs/en/data/topic_repos.yml")
    repos_old_content = repos_path.read_text(encoding="utf-8")
    new_repos_content = yaml.dump(data, sort_keys=False, width=200, allow_unicode=True)
    if repos_old_content == new_repos_content:

import static org.elasticsearch.gradle.internal.test.rest.RestTestUtil.registerTestTask;
import static org.elasticsearch.gradle.internal.test.rest.RestTestUtil.setupTestDependenciesDefaults;

/**
 * Apply this plugin to run the YAML based REST tests.
 */
public class InternalYamlRestTestPlugin implements Plugin<Project> {

    public static final String SOURCE_SET_NAME = "yamlRestTest";

    @Override
    public void apply(Project project) {

    }
    yamlRestCompatTest {
      id = 'elasticsearch.yaml-rest-compat-test'
      implementationClass = 'org.elasticsearch.gradle.internal.rest.compat.YamlRestCompatTestPlugin'
    }
    yamlRestTest {
      id = 'elasticsearch.internal-yaml-rest-test'
      implementationClass = 'org.elasticsearch.gradle.internal.test.rest.InternalYamlRestTestPlugin'
    }
  }
}