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docs/en/docs/advanced/dataclasses.md
## Dataclasses in Nested Data Structures You can also combine `dataclasses` with other type annotations to make nested data structures. In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation. In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:
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docs/em/docs/advanced/dataclasses.md
```Python hl_lines="1 7-12 19-20" {!../../../docs_src/dataclasses/tutorial001.py!} ``` 👉 🐕🦺 👏 **Pydantic**, ⚫️ ✔️ <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">🔗 🐕🦺 `dataclasses`</a>. , ⏮️ 📟 🔛 👈 🚫 ⚙️ Pydantic 🎯, FastAPI ⚙️ Pydantic 🗜 📚 🐩 🎻 Pydantic 👍 🍛 🎻. & ↗️, ⚫️ 🐕🦺 🎏: * 💽 🔬 * 💽 🛠️
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docs/zh/docs/advanced/dataclasses.md
```Python hl_lines="1 7-12 19-20" {!../../../docs_src/dataclasses/tutorial001.py!} ``` 这还是借助于 **Pydantic** 及其<a href="https://pydantic-docs.helpmanual.io/usage/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">内置的 `dataclasses`</a>。 因此,即便上述代码没有显式使用 Pydantic,FastAPI 仍会使用 Pydantic 把标准数据类转换为 Pydantic 数据类(`dataclasses`)。 并且,它仍然支持以下功能: * 数据验证 * 数据序列化 * 数据存档等
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docs/de/docs/advanced/dataclasses.md
```Python hl_lines="1 7-12 19-20" {!../../../docs_src/dataclasses/tutorial001.py!} ``` Das ist dank **Pydantic** ebenfalls möglich, da es <a href="https://pydantic-docs.helpmanual.io/usage/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">`dataclasses` intern unterstützt</a>.
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