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docs/zh/docs/tutorial/response-model.md
### `response_model_include` 和 `response_model_exclude` 你还可以使用*路径操作装饰器*的 `response_model_include` 和 `response_model_exclude` 参数。 它们接收一个由属性名称 `str` 组成的 `set` 来包含(忽略其他的)或者排除(包含其他的)这些属性。 如果你只有一个 Pydantic 模型,并且想要从输出中移除一些数据,则可以使用这种快捷方法。 !!! tip 但是依然建议你使用上面提到的主意,使用多个类而不是这些参数。
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docs/ja/docs/tutorial/response-model.md
```Python hl_lines="9 11 16" {!../../../docs_src/response_model/tutorial003.py!} ``` ここでは、*path operation関数*がパスワードを含む同じ入力ユーザーを返しているにもかかわらず: ```Python hl_lines="24" {!../../../docs_src/response_model/tutorial003.py!} ``` ...`response_model`を`UserOut`と宣言したことで、パスワードが含まれていません: ```Python hl_lines="22" {!../../../docs_src/response_model/tutorial003.py!} ```
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docs/ko/docs/tutorial/response-model.md
```Python hl_lines="9 11 16" {!../../../docs_src/response_model/tutorial003.py!} ``` 여기서 *경로 작동 함수*가 비밀번호를 포함하는 동일한 입력 사용자를 반환할지라도: ```Python hl_lines="24" {!../../../docs_src/response_model/tutorial003.py!} ``` ...`response_model`을 `UserOut` 모델로 선언했기 때문에 비밀번호를 포함하지 않습니다: ```Python hl_lines="22" {!../../../docs_src/response_model/tutorial003.py!} ```
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docs/en/docs/tutorial/security/get-current-user.md
But you are not restricted to using some specific data model, class or type. Do you want to have an `id` and `email` and not have any `username` in your model? Sure. You can use these same tools. Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.
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docs/en/docs/advanced/dataclasses.md
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" {!../../../docs_src/dataclasses/tutorial002.py!} ``` The dataclass will be automatically converted to a Pydantic dataclass.
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docs/fr/docs/advanced/additional-responses.md
## Réponse supplémentaire avec `model` Vous pouvez ajouter à votre décorateur de *paramètre de chemin* un paramètre `responses`. Il prend comme valeur un `dict` dont les clés sont des codes HTTP pour chaque réponse, comme `200`, et la valeur de ces clés sont d'autres `dict` avec des informations pour chacun d'eux. Chacun de ces `dict` de réponse peut avoir une clé `model`, contenant un modèle Pydantic, tout comme `response_model`.
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docs/em/docs/advanced/response-change-status-code.md
{!../../../docs_src/response_change_status_code/tutorial001.py!} ``` & ⤴️ 👆 💪 📨 🙆 🎚 👆 💪, 👆 🛎 🔜 ( `dict`, 💽 🏷, ♒️). & 🚥 👆 📣 `response_model`, ⚫️ 🔜 ⚙️ ⛽ & 🗜 🎚 👆 📨. **FastAPI** 🔜 ⚙️ 👈 *🔀* 📨 ⚗ 👔 📟 (🍪 & 🎚), & 🔜 🚮 👫 🏁 📨 👈 🔌 💲 👆 📨, ⛽ 🙆 `response_model`.
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docs/en/docs/tutorial/body-fields.md
``` !!! warning Notice that `Field` is imported directly from `pydantic`, not from `fastapi` as are all the rest (`Query`, `Path`, `Body`, etc). ## Declare model attributes You can then use `Field` with model attributes: === "Python 3.10+" ```Python hl_lines="11-14" {!> ../../../docs_src/body_fields/tutorial001_an_py310.py!} ``` === "Python 3.9+"
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docs/em/docs/advanced/response-cookies.md
{!../../../docs_src/response_cookies/tutorial002.py!} ``` & ⤴️ 👆 💪 📨 🙆 🎚 👆 💪, 👆 🛎 🔜 ( `dict`, 💽 🏷, ♒️). & 🚥 👆 📣 `response_model`, ⚫️ 🔜 ⚙️ ⛽ & 🗜 🎚 👆 📨. **FastAPI** 🔜 ⚙️ 👈 *🔀* 📨 ⚗ 🍪 (🎚 & 👔 📟), & 🔜 🚮 👫 🏁 📨 👈 🔌 💲 👆 📨, ⛽ 🙆 `response_model`. 👆 💪 📣 `Response` 🔢 🔗, & ⚒ 🍪 (& 🎚) 👫. ## 📨 `Response` 🔗 👆 💪 ✍ 🍪 🕐❔ 🛬 `Response` 🔗 👆 📟.
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docs/en/docs/tutorial/path-params.md
!!! tip If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>. ### Declare a *path parameter* Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`): ```Python hl_lines="16"
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