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

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

## 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

labels.reload_doc_index=Dokumenten-Index neuladen
labels.reload_doc_index_button=Neuladen
labels.plugin_title=Plugin
labels.plugin_list_name=Plugin-Liste
labels.plugin_type=Typ
labels.plugin_name=Name
labels.plugin_version=Version
labels.plugin_delete=Löschen
labels.plugin_install=Installieren
labels.plugin_install_title=Plugin installieren
labels.plugin_jar_file=JAR-Datei
labels.plugin_local_install=Lokal

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

- The scheduler skips the `InterPodAffinity` Score plugin when nothing to do with the Pod.
  It will affect some metrics values related to the InterPodAffinity Score plugin. ([#117794](https://github.com/kubernetes/kubernetes/pull/117794), [@utam0k](https://github.com/utam0k)) [SIG Scheduling]
- The scheduler skips the `PodTopologySpread` Filter plugin if no spread constraints.

  }
  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

/// tip | "豆知識"

<a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a>エディタを使用している場合は、<a href="https://github.com/koxudaxi/pydantic-pycharm-plugin/" class="external-link" target="_blank">Pydantic PyCharm Plugin</a>が使用可能です。

以下のエディターサポートが強化されます:

* 自動補完
* 型チェック
* リファクタリング
* 検索
* インスペクション

///

## モデルの使用

関数内部で、モデルの全ての属性に直接アクセスできます:

	xldap "github.com/minio/minio/internal/config/identity/ldap"
	"github.com/minio/minio/internal/config/identity/openid"
	idplugin "github.com/minio/minio/internal/config/identity/plugin"
	polplugin "github.com/minio/minio/internal/config/policy/plugin"
	"github.com/minio/minio/internal/config/storageclass"
	"github.com/minio/minio/internal/config/subnet"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/mux"

* 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))

      --enable-gnu-indirect-function \
      --enable-gnu-unique-object \
      --enable-initfini-array \
      --enable-languages="c,c++" \
      --enable-linker-build-id \
      --enable-plugin \
      --enable-shared \
      --enable-threads=posix \
      --with-default-libstdcxx-abi=${LIBSTDCXX_ABI} \
      --with-gcc-major-version-only \
      --with-linker-hash-style="gnu" \