### Eine Engine erstellen { #create-an-engine }

Eine SQLModel-`engine` (darunter ist es tatsächlich eine SQLAlchemy-`engine`) ist das, was die **Verbindungen** zur Datenbank hält.

Sie hätten **ein einziges `engine`-Objekt** für Ihren gesamten Code, um sich mit derselben Datenbank zu verbinden.

  api(libs.square.kotlin.poet)
  testImplementation(libs.assertk)
  testImplementation(libs.junit.jupiter.api)
  testImplementation(libs.junit.jupiter.params)

  testImplementation(rootProject.libs.junit.jupiter.engine)
}

animalsniffer {
  isIgnoreFailures = true

### Crear un Engine { #create-an-engine }

Un `engine` de SQLModel (en el fondo, realmente es un `engine` de SQLAlchemy) es lo que **mantiene las conexiones** a la base de datos.

Tendrías **un solo objeto `engine`** para todo tu código para conectar a la misma base de datos.

jetbrains-annotations = { module = "org.jetbrains:annotations", version.ref = "jetbrains-annotations" }
junit-jupiter-api = { module = "org.junit.jupiter:junit-jupiter-api", version.ref = "org-junit-jupiter" }
junit-jupiter-engine = { module = "org.junit.jupiter:junit-jupiter-engine", version.ref = "org-junit-jupiter" }
junit-jupiter-params = { module = "org.junit.jupiter:junit-jupiter-params", version.ref = "org-junit-jupiter" }

    public void close() {
        scriptCache.invalidateAll();
        scriptCache.cleanUp();
    }

    /**
     * Returns the name identifier for this script engine.
     *
     * @return "groovy" - the identifier used to register and retrieve this engine
     */
    @Override
    protected String getName() {
        return "groovy";
    }

    /**

dependencies {
  "friendsApi"(projects.okhttp)
  api(projects.mockwebserver3)
  api(libs.junit.jupiter.api)
  compileOnly(libs.animalsniffer.annotations)

  testRuntimeOnly(libs.junit.jupiter.engine)
  testImplementation(libs.kotlin.junit5)
  testImplementation(projects.okhttpTestingSupport)
  testImplementation(libs.assertk)

    /** The expression used to match documents for boosting */
    private String matchExpression;

    /** The script engine type used for expression evaluation */
    private final String scriptType;

    /**
     * Default constructor that creates a DocBoostMatcher with default script type.
     * Uses the default script engine as defined in Constants.DEFAULT_SCRIPT.
     */
    public DocBoostMatcher() {

    SQLModel 会知道声明为 `str` 的内容将是类型为 `TEXT`（或 `VARCHAR`，具体取决于数据库）的 SQL 列。

### 创建引擎（Engine） { #create-an-engine }

SQLModel 的 `engine`（实际上它是一个 SQLAlchemy 的 `engine`）是用来与数据库**保持连接**的。

你只需构建**一个 `engine` 对象**，让你的所有代码连接到同一个数据库。

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[14:18] hl[14:15,17:18] *}

        return childUrlSet.isEmpty() ? null : childUrlSet;
    }

    /**
     * Retrieves child URLs for a given document ID from the search engine index.
     * This method queries the search engine for child documents and extracts their URLs.
     *
     * @param searchEngineClient the search engine client to query
     * @param id the parent document ID to find children for

project.applyJavaModules("mockwebserver3.junit4")

dependencies {
  api(projects.okhttp)
  api(projects.mockwebserver3)
  api(libs.junit)

  testImplementation(libs.assertk)
  testImplementation(libs.junit.vintage.engine)