*
 * <p>If you have an instance of one of the primary {@code common.graph} types ({@link Graph},
 * {@link ValueGraph}, and {@link Network}):
 *
 * {@snippet :
 * someGraphAlgorithm(startNode, graph);
 * }
 *
 * This works because those types each implement {@code SuccessorsFunction}. It will also work with
 * any other implementation of this interface.
 *

# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

name: PR Automation
on:
  pull_request_target:
    types:
      - closed

jobs:
  pr-automation:
    name: PR Automation

 * case of (say) {@link HashSet}, which is an <i>implementation</i>, with semantics that were
 * largely defined by its supertype.
 *
 * <p>For field types and method return types, you should generally use the immutable type (such as
 * {@link ImmutableList}) instead of the general collection interface type (such as {@link List}).

Il en serait de même si vous aviez quelque chose comme une <dfn title="Une union entre plusieurs types signifie « n'importe lequel de ces types ».">union</dfn> entre différents types dont un ou plusieurs ne sont pas des types Pydantic valides, par exemple ceci échouerait 💥 :

{* ../../docs_src/response_model/tutorial003_04_py310.py hl[8] *}

    TypeVariable<?> k = (TypeVariable<?>) paramType.getActualTypeArguments()[0];
    TypeVariable<?> v = (TypeVariable<?>) paramType.getActualTypeArguments()[1];
    assertEquals(Types.newParameterizedType(List.class, v), k.getBounds()[0]);
    assertEquals(Types.newParameterizedType(List.class, k), v.getBounds()[0]);
  }

  public void testWithGenericLowerBoundInWildcard() throws Exception {
    WildcardType wildcardType =

    TypeVariable<?> k = (TypeVariable<?>) paramType.getActualTypeArguments()[0];
    TypeVariable<?> v = (TypeVariable<?>) paramType.getActualTypeArguments()[1];
    assertEquals(Types.newParameterizedType(List.class, v), k.getBounds()[0]);
    assertEquals(Types.newParameterizedType(List.class, k), v.getBounds()[0]);
  }

  public void testWithGenericLowerBoundInWildcard() throws Exception {
    WildcardType wildcardType =

* Автоматическую документацию

## Особые типы и валидация { #special-types-and-validation }

Помимо обычных простых типов, таких как `str`, `int`, `float` и т.д., вы можете использовать более сложные простые типы, которые наследуются от `str`.

Чтобы увидеть все варианты, которые у вас есть, ознакомьтесь с [обзором типов Pydantic](https://docs.pydantic.dev/latest/concepts/types/). Вы увидите некоторые примеры в следующей главе.

    return containsKey(key) ? unfiltered.removeAll(key) : unmodifiableEmptyCollection();
  }

  @SuppressWarnings("EmptyList") // ImmutableList doesn't support nullable element types
  Collection<V> unmodifiableEmptyCollection() {
    if (unfiltered instanceof SetMultimap) {
      return emptySet();
    } else {
      return emptyList();
    }
  }

  @Override
  public void clear() {

    return containsKey(key) ? unfiltered.removeAll(key) : unmodifiableEmptyCollection();
  }

  @SuppressWarnings("EmptyList") // ImmutableList doesn't support nullable element types
  Collection<V> unmodifiableEmptyCollection() {
    if (unfiltered instanceof SetMultimap) {
      return emptySet();
    } else {
      return emptyList();
    }
  }

  @Override
  public void clear() {

http://127.0.0.1:8000/items/?skip=0&limit=10
```

... die Query-Parameter:

* `skip`: mit dem Wert `0`
* `limit`: mit dem Wert `10`

Da sie Teil der URL sind, sind sie „naturgemäß“ Strings.

Aber wenn Sie sie mit Python-Typen deklarieren (im obigen Beispiel als `int`), werden sie zu diesem Typ konvertiert und gegen diesen validiert.

Die gleichen Prozesse, die für Pfad-Parameter gelten, werden auch auf Query-Parameter angewendet: