### Injection de dépendances

FastAPI contient un système simple mais extrêmement puissant d'<abbr title='aussi connus sous le nom de "composants", "ressources", "services", "providers"'><strong>Injection de Dépendances</strong></abbr>.

* Même les dépendances peuvent avoir des dépendances, créant une hiérarchie ou un **"graph" de dépendances**
* Tout est **automatiquement géré** par le framework

              <goal>build-bom</goal>
            </goals>
            <configuration>
              <bomClassifier>fat</bomClassifier>
              <bomName>Maven Dependencies Fat BOM</bomName>
              <bomDescription>Bill Of Materials for Apache Maven - All dependencies</bomDescription>
              <outputFilename>maven-fat-bom.xml</outputFilename>
              <reactorDependencies>REACTOR</reactorDependencies>

        "org.gradle.jvm.version": "8",
        "org.gradle.jvm.environment": "${variant.jvmEnvironment}",
        "org.gradle.libraryelements": "jar",
        "org.gradle.usage": "java-api"
      },
      "dependencies": [
        {
          "group": "com.google.guava",
          "module": "failureaccess",
          "version": {
            "requires": "1.0.3"
          }
        },
        {

      failWithoutSignatures = false
    }
  }

  dependencies {
    // No dependency requirements for testing-support.
    if (project.name == "okhttp-testing-support") return@dependencies

    // okhttp configured specifically.
    if (project.name == "okhttp") return@dependencies

    if (project.name == "mockwebserver3-junit5") {

                // It should have never found its way into Maven 2.x repository, but it did.
                dependencies = Collections.emptyList();
            } else {
                dependencies = rel.project.getModel().getDependencies();

                DependencyManagement depMgmt = rel.project.getModel().getDependencyManagement();

previous build will be preserved and reused for the subsequent builds.

### Specifying Python dependencies

During bazel build all TensorFlow's Python dependencies are pinned to their
specific versions. This is necessary to ensure reproducibility of the build.
The pinned versions of the full transitive closure of TensorFlow's dependencies
together with their corresponding hashes are specified in

    <syntax>project.artifacts</syntax>
    <configuration>
      <![CDATA[
<dependencies>
  ...
</dependencies>
    ]]></configuration>
    <description>
      <![CDATA[
      This is a set of Artifact instances resolved from the set of dependencies for
      the current project.

      NOTE: This will likely contain much more than the direct dependencies of the

 Plugins should avoid these classes and be updated to use only Maven3 dependencies (and require Maven3): see
 {{{https://cwiki.apache.org/confluence/display/MAVEN/Plugin+migration+to+Maven3+dependencies} Plugin migration to Maven3 dependencies}}

/**
 * Verifies scope inheritance of direct and transitive dependencies.
 *
 * Should show three behaviors:
 *
 * 1. dependencyManagement should override the scope of transitive dependencies.
 * 2. Direct dependencies should override the scope of dependencyManagement.
 * 3. Direct dependencies should inherit scope from dependencyManagement when
 *    they do not explicitly state a scope.
 *
 */

     */
    enum Type {
        PROJECT,
        DEPENDENCIES,
        CHILDREN
    }

    /**
     * The phase name.
     */
    String phase();

    /**
     * The type of this pointer.
     */
    Type type();

    /**
     * The scope for dependencies, only if {@code type() == Type.Dependencies}.
     */
    String scope() default "";