.matching(new PatternSet().include("**/*.yml", "**/*.yaml"));

        final Provider<ValidateYamlAgainstSchemaTask> validateChangelogsAgainstYamlTask = project.getTasks()
            .register("validateChangelogsAgainstSchema", ValidateYamlAgainstSchemaTask.class, task -> {
                task.setGroup("Documentation");
                task.setDescription("Validate that the changelog YAML files comply with the changelog schema");

        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() {

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

儘管沒有使用預設的內建功能，我們仍透過 Pydantic 模型手動產生想以 YAML 接收之資料的 JSON Schema。

接著我們直接使用請求，並將本文擷取為 `bytes`。這表示 FastAPI 甚至不會嘗試把請求負載解析為 JSON。

然後在程式中直接解析該 YAML 內容，並再次使用相同的 Pydantic 模型來驗證該 YAML 內容：

 * spec and YAML based rest tests.
 * </p>
 * <strong>Rest API specification:</strong> <br>
 * When the {@link RestResourcesPlugin} has been applied the {@link CopyRestApiTask} will automatically copy the core Rest API specification
 * if there are any Rest YAML tests present in source, or copied from {@link CopyRestTestsTask} output. X-pack specs must be explicitly

import com.fasterxml.jackson.databind.ObjectMapper
import com.fasterxml.jackson.databind.SequenceWriter
import com.fasterxml.jackson.databind.node.ObjectNode
import com.fasterxml.jackson.dataformat.yaml.YAMLFactory
import org.elasticsearch.gradle.Version
import org.elasticsearch.gradle.fixtures.AbstractRestResourcesFuncTest
import org.elasticsearch.gradle.VersionProperties
import org.gradle.testkit.runner.TaskOutcome

{* ../../docs_src/path_operation_advanced_configuration/tutorial007_py310.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.

    def "yamlRestTest does nothing when there are no tests"() {
        given:
        buildFile << """
        plugins {
          id 'elasticsearch.internal-yaml-rest-test'
        }
        """

        when:
        def result = gradleRunner("yamlRestTest").build()

        then:
        result.task(':yamlRestTest').outcome == TaskOutcome.NO_SOURCE

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

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

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

Попри те, що ми не використовуємо типову вбудовану функціональність, ми все одно використовуємо модель Pydantic, щоб вручну згенерувати Схему JSON для даних, які хочемо отримати у форматі YAML.

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