String arg0 = "plugin-name";
        FessMessages result = messages.addSuccessInstallPlugin(property, arg0);
        assertNotNull(result);
        assertSame(messages, result);
        assertTrue(messages.hasMessageOf(property));
    }

    public void test_addSuccessDeletePlugin() {
        String property = "testProperty";
        String arg0 = "plugin-name";

  }
  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

  xml.schemaLocation="https://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">

Let's look at how we can make that work.

## pytest.mark.anyio { #pytest-mark-anyio }

If we want to call asynchronous functions in our tests, our test functions have to be asynchronous. AnyIO provides a neat plugin for this, that allows us to specify that some test functions are to be called asynchronously.

## HTTPX { #httpx }

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

* Fix issue where on re-registration of device plugin, `allocatable` was not getting updated. This issue makes devices invisible to the Kubelet if device plugin restarts. Only work-around, if this fix is not there, is to restart the kubelet and then start device plugin. ([#63118](https://github.com/kubernetes/kubernetes/pull/63118), [@vikaschoudhary16](https://github.com/vikaschoudhary16))

		}
		// In Kubernetes environment, try to fetch the Operator, VSPHERE plugin version
		opVersion := env.Get("MINIO_OPERATOR_VERSION", "")
		if opVersion != "" {
			uaAppend(" operator-", opVersion)
		}
		vsphereVersion := env.Get("MINIO_VSPHERE_PLUGIN_VERSION", "")
		if vsphereVersion != "" {
			uaAppend(" vsphere-plugin-", vsphereVersion)
		}
	}

	if IsPCFTile() {

- Scheduler: Add DefaultBinder plugin ([#87430](https://github.com/kubernetes/kubernetes/pull/87430), [@alculquicondor](https://github.com/alculquicondor)) [SIG Scheduling and Testing]

<img src="/img/tutorial/body/image05.png">

/// tip

🚥 👆 ⚙️ <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">🗒</a> 👆 👨‍🎨, 👆 💪 ⚙️ <a href="https://github.com/koxudaxi/pydantic-pycharm-plugin/" class="external-link" target="_blank">Pydantic 🗒 📁</a>.

⚫️ 📉 👨‍🎨 🐕‍🦺 Pydantic 🏷, ⏮️:

* 🚘-🛠️
* 🆎 ✅
* 🛠️
* 🔎
* 🔬

///

## ⚙️ 🏷

_current_module.__path__ = [_module_dir] + _current_module.__path__


# Enable TF2 behaviors
from tensorflow.python.compat import v2_compat as _compat
_compat.enable_v2_behavior()
_major_api_version = 2


# Load all plugin libraries from site-packages/tensorflow-plugins if we are
# running under pip.
# TODO(gunan): Find a better location for this code snippet.
from tensorflow.python.framework import load_library as _ll