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docs/fr/docs/tutorial/body.md
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 27 17:34:41 UTC 2024 - 7.6K bytes - Viewed (0) -
docs/en/docs/advanced/events.md
## Use Case Let's start with an example **use case** and then see how to solve it with this. Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖 The same models are shared among requests, so, it's not one model per request, or one per user or something similar.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Mon Oct 28 10:36:22 UTC 2024 - 7.6K bytes - Viewed (0) -
compat/maven-model-builder/src/main/java/org/apache/maven/model/normalization/ModelNormalizer.java
*/ void injectDefaultValues(Model model, ModelBuildingRequest request, ModelProblemCollector problems); org.apache.maven.api.model.Model mergeDuplicates( org.apache.maven.api.model.Model model, ModelBuildingRequest request, ModelProblemCollector problems); org.apache.maven.api.model.Model injectDefaultValues( org.apache.maven.api.model.Model model, ModelBuildingRequest request, ModelProblemCollector problems);
Registered: Sun Nov 03 03:35:11 UTC 2024 - Last Modified: Fri Oct 25 12:31:46 UTC 2024 - 2.8K bytes - Viewed (0) -
compat/maven-model-builder/src/main/java/org/apache/maven/model/superpom/SuperPomProvider.java
*/ package org.apache.maven.model.superpom; import org.apache.maven.model.Model; /** * Provides the super POM that all models implicitly inherit from. * * @deprecated use {@link org.apache.maven.api.services.ModelBuilder} instead */ @Deprecated(since = "4.0.0") public interface SuperPomProvider { /**
Registered: Sun Nov 03 03:35:11 UTC 2024 - Last Modified: Fri Oct 25 12:31:46 UTC 2024 - 1.6K bytes - Viewed (0) -
docs/zh/docs/tutorial/response-model.md
## 在文档中查看 当你查看自动化文档时,你可以检查输入模型和输出模型是否都具有自己的 JSON Schema: <img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image01.png"> 并且两种模型都将在交互式 API 文档中使用: <img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image02.png"> ## 响应模型编码参数 你的响应模型可以具有默认值,例如: ```Python hl_lines="11 13-14" {!../../docs_src/response_model/tutorial004.py!} ```
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 7.8K bytes - Viewed (0) -
docs/pt/docs/tutorial/encoder.md
Da mesma forma, este banco de dados não receberia um modelo Pydantic (um objeto com atributos), apenas um `dict`. Você pode usar a função `jsonable_encoder` para resolver isso. A função recebe um objeto, como um modelo Pydantic e retorna uma versão compatível com JSON: //// tab | Python 3.10+ ```Python hl_lines="4 21"
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api/maven-api-settings/pom.xml
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compat/maven-repository-metadata/pom.xml
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api/maven-api-core/src/main/java/org/apache/maven/api/services/SuperPomProvider.java
import org.apache.maven.api.annotations.Nonnull; import org.apache.maven.api.model.Model; /** * Provides the super POM that all models implicitly inherit from. * * @since 4.0.0 */ @Experimental public interface SuperPomProvider extends Service { /** * Gets the super POM for the specified model version. * * @param version The model version to retrieve the super POM for (e.g. "4.0.0"), must not be {@code null}.
Registered: Sun Nov 03 03:35:11 UTC 2024 - Last Modified: Wed Feb 28 23:54:53 UTC 2024 - 1.5K bytes - Viewed (0) -
api/maven-api-spi/src/main/java/org/apache/maven/api/spi/ModelTransformer.java
* @return the transformed model, or the input model if no transformation is needed * @throws ModelTransformerException */ @Nonnull default Model transformFileModel(@Nonnull Model model) throws ModelTransformerException { return model; } /** * Apply a transformation on the raw models. * * This method will be called on each raw model being loaded,
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