import org.apache.maven.artifact.repository.ArtifactRepositoryFactory;
import org.apache.maven.execution.MavenExecutionRequest;
import org.apache.maven.execution.MavenSession;
import org.apache.maven.plugin.LegacySupport;
import org.apache.maven.repository.MirrorSelector;
import org.apache.maven.settings.Mirror;
import org.apache.maven.settings.Proxy;
import org.apache.maven.settings.Server;

 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.plugin.logging;

/**
 * This interface supplies the API for providing feedback to the user from the <code>Mojo</code>, using standard
 * <code>Maven</code> channels.<br>

    val repoDir = bndDir / "repo"
    fileSystem.createDirectories(repoDir)
    return Workspace(workspaceDir.toFile(), bndDir.name)
      .apply {
        setProperty(
          "${Constants.PLUGIN}.$REPO_NAME",
          LocalIndexedRepo::class.java.getName() +
            "; ${LocalIndexedRepo.PROP_NAME} = '$REPO_NAME'" +
            "; ${LocalIndexedRepo.PROP_LOCAL_DIR} = '$repoDir'",
        )
        refresh()

    }

    public Artifact createPluginArtifact(String groupId, String artifactId, VersionRange versionRange) {
        return createArtifact(groupId, artifactId, versionRange, "maven-plugin", null, Artifact.SCOPE_RUNTIME, null);
    }

    public Artifact createProjectArtifact(String groupId, String artifactId, String version, String scope) {

```console
$ pytest

================ test session starts ================
platform linux -- Python 3.6.9, pytest-5.3.5, py-1.8.1, pluggy-0.13.1
rootdir: /home/user/code/superawesome-cli/app
plugins: forked-1.1.3, xdist-1.31.0, cov-2.8.1
collected 6 items

---> 100%

test_main.py <span style="color: green; white-space: pre;">......                            [100%]</span>

  }
  delete[] shape_list_array;
}

namespace tensorflow {
absl::Status TF_TensorToTensor(const TF_Tensor* src, Tensor* dst);

// Helpers for loadding a TensorFlow PluggableDevice plugin (a .so file).
absl::Status LoadPluggableDeviceLibrary(const char* library_filename,
                                        void** result);
}  // namespace tensorflow

        sampleDoc = new File(docsRoot, "sample.adoc")
        linkErrors = new File(projectDir, "build/reports/dead-internal-links.txt")


        new File(projectDir, "build.gradle") << """
            plugins {
                id 'java'
                id 'checkstyle'
                id 'gradlebuild.documentation'
            }

            gradleDocumentation {
                javadocs {

labels.reload_doc_index=Reload Doc Index
labels.reload_doc_index_button=Reload
labels.plugin_title=Plugin
labels.plugin_list_name=Plugin List
labels.plugin_type=Type
labels.plugin_name=Name
labels.plugin_version=Version
labels.plugin_delete=Delete
labels.plugin_install=Install
labels.plugin_install_title=Install Plugin
labels.plugin_jar_file=Jar File
labels.plugin_local_install=Local

  xml.schemaLocation="http://maven.apache.org/xsd/lifecycle-${version}.xsd">
  <id>lifecycle</id>
  <name>Lifecycle</name>
  <description>
    Configuration of custom lifecycle mappings for the plugin, as generally stored in
    {@code META-INF/maven/lifecycle.xml} in a plugin's jar artifact.
  </description>
  <classes>
    <class rootElement="true" xml.tagName="lifecycles" xsd.compositor="sequence">

Schauen wir uns an, wie wir das machen können.

## pytest.mark.anyio

Wenn wir in unseren Tests asynchrone Funktionen aufrufen möchten, müssen unsere Testfunktionen asynchron sein. AnyIO stellt hierfür ein nettes Plugin zur Verfügung, mit dem wir festlegen können, dass einige Testfunktionen asynchron aufgerufen werden sollen.

## HTTPX