{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Create your data model { #create-your-data-model }

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

Et ces modèles partagent beaucoup de données et dupliquent des noms et types d'attributs.

Nous pouvons faire mieux.

name: Publish

on:
  release:
    types:
      - created

jobs:
  publish:
    runs-on: ubuntu-latest
    permissions:
      id-token: write
      contents: read
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v6
      - name: Set up Python
        uses: actions/setup-python@v6
        with:

    /**
     * Returns the element type of an array with parameterized types.
     * <p>
     * If <code>type</code> is not an array of parameterized types, <code>null</code> is returned.
     * </p>
     *
     * @param type
     *            the type to analyze
     * @return the element type of the array, or null if not an array of parameterized types
     */
    public static Type getElementTypeOfArray(final Type type) {

 *
 * <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 PredecessorsFunction}. It will also work
 * with any other implementation of this interface.
 *

 *
 * <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 =