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tests/test_filter_pydantic_sub_model_pv2.py
return name async def get_model_c() -> ModelC: return ModelC(username="test-user", password="test-password") @app.get("/model/{name}", response_model=ModelA) async def get_model_a(name: str, model_c=Depends(get_model_c)): return {"name": name, "description": "model-a-desc", "foo": model_c} client = TestClient(app) return client @needs_pydanticv2
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:40:57 UTC 2024 - 6.3K bytes - Viewed (0) -
platforms/core-configuration/configuration-cache/src/integTest/groovy/org/gradle/internal/cc/impl/isolated/IsolatedProjectsToolingApiPhasedBuildActionIntegrationTest.groovy
def model2 = models2.right model2.size() == 2 model2[0].message == "It works from project :" model2[1].message == "It works from project :a" and: fixture.assertStateLoaded() outputDoesNotContain("creating model") } def "caches execution of phased BuildAction that queries custom tooling model and that runs tasks"() { given:
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Sat Jun 08 11:29:25 UTC 2024 - 10.4K bytes - Viewed (0) -
docs/de/docs/tutorial/extra-models.md
# Extramodelle Fahren wir beim letzten Beispiel fort. Es gibt normalerweise mehrere zusammengehörende Modelle. Insbesondere Benutzermodelle, denn: * Das **hereinkommende Modell** sollte ein Passwort haben können. * Das **herausgehende Modell** sollte kein Passwort haben.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sat Mar 30 20:26:47 UTC 2024 - 8.7K bytes - Viewed (0) -
platforms/core-configuration/configuration-cache/src/integTest/groovy/org/gradle/internal/cc/impl/isolated/IsolatedProjectsToolingApiCompositeBuildsIntegrationTest.groovy
modelsCreated(":", ":a") } when: executer.withArguments(ENABLE_CLI) def model2 = runBuildAction(new FetchCustomModelForEachProjectInTree()) then: model2.size() == 2 model2[0].message == "It works from project :" model2[1].message == "It works from project :a" and: fixture.assertStateLoaded() when:
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Sat Jun 08 11:29:25 UTC 2024 - 6.9K bytes - Viewed (0) -
docs/pt/docs/tutorial/body-nested-models.md
## Modelos aninhados Cada atributo de um modelo Pydantic tem um tipo. Mas esse tipo pode ser outro modelo Pydantic. Portanto, você pode declarar "objects" JSON profundamente aninhados com nomes, tipos e validações de atributos específicos. Tudo isso, aninhado arbitrariamente. ### Defina um sub-modelo Por exemplo, nós podemos definir um modelo `Image`: ```Python hl_lines="9-11"
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 7.4K bytes - Viewed (0) -
docs/de/docs/reference/openapi/models.md
# OpenAPI-`models` OpenAPI Pydantic-Modelle, werden zum Generieren und Validieren der generierten OpenAPI verwendet.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sat Mar 30 18:15:17 UTC 2024 - 146 bytes - Viewed (0) -
docs/en/docs/tutorial/extra-models.md
# Extra Models Continuing with the previous example, it will be common to have more than one related model. This is especially the case for user models, because: * The **input model** needs to be able to have a password. * The **output model** should not have a password. * The **database model** would probably need to have a hashed password. !!! danger Never store user's plaintext passwords. Always store a "secure hash" that you can then verify.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 7.7K bytes - Viewed (0) -
docs/de/docs/tutorial/body-nested-models.md
Und es wird entsprechend annotiert/dokumentiert. ## Verschachtelte Modelle Jedes Attribut eines Pydantic-Modells hat einen Typ. Aber dieser Typ kann selbst ein anderes Pydantic-Modell sein. Sie können also tief verschachtelte JSON-„Objekte“ deklarieren, mit spezifischen Attributnamen, -typen, und -validierungen.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Mar 22 01:42:11 UTC 2024 - 10.4K bytes - Viewed (0) -
docs/en/docs/tutorial/body-nested-models.md
## Nested Models Each attribute of a Pydantic model has a type. But that type can itself be another Pydantic model. So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations. All that, arbitrarily nested. ### Define a submodel For example, we can define an `Image` model: === "Python 3.10+"
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Mar 22 01:42:11 UTC 2024 - 9.5K bytes - Viewed (0) -
maven-core/src/test/projects/lifecycle-executor/project-with-multiple-executions/src/main/mdo/supplemental-model.mdo
KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> <model> <id>supplementalModel</id> <name>SupplementalDataModel</name> <description>Provides access to supplemental POM data models.</description> <defaults> <default> <key>package</key> <value>org.apache.maven.plugin.resources.remote</value> </default>
Registered: Wed Jun 12 09:55:16 UTC 2024 - Last Modified: Thu May 21 12:56:07 UTC 2009 - 2.1K bytes - Viewed (0)