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docs/zh/docs/tutorial/body-nested-models.md
=== "Python 3.10+" ```Python hl_lines="12" {!> ../../../docs_src/body_nested_models/tutorial002_py310.py!} ``` === "Python 3.9+" ```Python hl_lines="14" {!> ../../../docs_src/body_nested_models/tutorial002_py39.py!} ``` === "Python 3.8+" ```Python hl_lines="14" {!> ../../../docs_src/body_nested_models/tutorial002.py!} ``` ## Set 类型 但是随后我们考虑了一下,意识到标签不应该重复,它们很大可能会是唯一的字符串。
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docs/em/docs/tutorial/body-nested-models.md
```Python hl_lines="14" {!> ../../../docs_src/body_nested_models/tutorial002.py!} ``` === "🐍 3️⃣.9️⃣ & 🔛" ```Python hl_lines="14" {!> ../../../docs_src/body_nested_models/tutorial002_py39.py!} ``` === "🐍 3️⃣.1️⃣0️⃣ & 🔛" ```Python hl_lines="12" {!> ../../../docs_src/body_nested_models/tutorial002_py310.py!} ``` ## ⚒ 🆎
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docs/de/docs/tutorial/body-updates.md
Wenn Sie Teil-Aktualisierungen entgegennehmen, ist der `exclude_unset`-Parameter in der `.model_dump()`-Methode von Pydantic-Modellen sehr nützlich. Wie in `item.model_dump(exclude_unset=True)`. !!! info In Pydantic v1 hieß diese Methode `.dict()`, in Pydantic v2 wurde sie deprecated (aber immer noch unterstützt) und in `.model_dump()` umbenannt.
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docs/ja/docs/tutorial/body-nested-models.md
```Python hl_lines="12" {!../../../docs_src/body_nested_models/tutorial001.py!} ``` これにより、各項目の型は宣言されていませんが、`tags`はある項目のリストになります。 ## タイプパラメータを持つリストのフィールド しかし、Pythonには型や「タイプパラメータ」を使ってリストを宣言する方法があります: ### typingの`List`をインポート まず、Pythonの標準の`typing`モジュールから`List`をインポートします: ```Python hl_lines="1" {!../../../docs_src/body_nested_models/tutorial002.py!} ``` ### タイプパラメータを持つ`List`の宣言
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architecture/build-state-model.md
# Build state model The Gradle daemon tracks state for various elements. These are arranged in a hierarchy: ```mermaid graph TD process["build process"] session["build session"] process --> session build_tree["build tree"] session --> build_tree build1["root build"] build_tree --> build1 project1["root project"] build1 --> project1 project2["project"] build1 --> project2
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api/maven-api-plugin/pom.xml
<velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir> <version>2.0.0</version> <models> <model>src/main/mdo/plugin.mdo</model> </models> <templates> <template>model.vm</template> </templates> <params> <param>packageModelV4=org.apache.maven.api.plugin.descriptor</param>
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docs/en/docs/tutorial/sql-databases.md
## Create the Pydantic models Now let's check the file `sql_app/schemas.py`. !!! tip To avoid confusion between the SQLAlchemy *models* and the Pydantic *models*, we will have the file `models.py` with the SQLAlchemy models, and the file `schemas.py` with the Pydantic models. These Pydantic models define more or less a "schema" (a valid data shape).
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maven-api-impl/pom.xml
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api/maven-api-metadata/pom.xml
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api/maven-api-settings/pom.xml
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