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docs/en/docs/advanced/dataclasses.md
!!! info Keep in mind that dataclasses can't do everything Pydantic models can do. So, you might still need to use Pydantic models. But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓 ## Dataclasses in `response_model` You can also use `dataclasses` in the `response_model` parameter: ```Python hl_lines="1 7-13 19"
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docs/de/docs/advanced/dataclasses.md
Daher müssen Sie möglicherweise weiterhin Pydantic-Modelle verwenden. Wenn Sie jedoch eine Menge Datenklassen herumliegen haben, ist dies ein guter Trick, um sie für eine Web-API mithilfe von FastAPI zu verwenden. 🤓 ## Datenklassen als `response_model` Sie können `dataclasses` auch im Parameter `response_model` verwenden: ```Python hl_lines="1 7-13 19"
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docs/en/docs/advanced/path-operation-advanced-configuration.md
Nevertheless, we can declare the expected schema for the request body. ### Custom OpenAPI content type Using this same trick, you could use a Pydantic model to define the JSON Schema that is then included in the custom OpenAPI schema section for the *path operation*. And you could do this even if the data type in the request is not JSON.
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docs/de/docs/advanced/path-operation-advanced-configuration.md
Dennoch können wir das zu erwartende Schema für den Requestbody deklarieren. ### Benutzerdefinierter OpenAPI-Content-Type Mit demselben Trick könnten Sie ein Pydantic-Modell verwenden, um das JSON-Schema zu definieren, das dann im benutzerdefinierten Abschnitt des OpenAPI-Schemas für die *Pfadoperation* enthalten ist.
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docs/en/docs/tutorial/path-params-numeric-validations.md
``` ## Order the parameters as you need, tricks !!! tip This is probably not as important or necessary if you use `Annotated`. Here's a **small trick** that can be handy, but you won't need it often. If you want to: * declare the `q` query parameter without a `Query` nor any default value * declare the path parameter `item_id` using `Path`
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