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docs/pt/docs/tutorial/sql-databases.md
Como cada modelo SQLModel também é um modelo Pydantic, você pode usá-lo nas mesmas **anotações de tipo** que usaria para modelos Pydantic. Por exemplo, se você declarar um parâmetro do tipo `Hero`, ele será lido do **corpo JSON**. Da mesma forma, você pode declará-lo como o **tipo de retorno** da função, e então o formato dos dados aparecerá na interface de documentação automática da API.
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sun Oct 27 15:25:29 UTC 2024 - 15.8K bytes - Viewed (0) -
docs/pt/docs/tutorial/response-model.md
Se você tiver verificações de tipo rigorosas em seu editor, mypy, etc, você pode declarar o tipo de retorno da função como `Any`. Dessa forma, você diz ao editor que está retornando qualquer coisa intencionalmente. Mas o FastAPI ainda fará a documentação de dados, validação, filtragem, etc. com o `response_model`. /// ### Prioridade `response_model`
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Tue Nov 26 22:51:05 UTC 2024 - 16.5K bytes - Viewed (0) -
docs/fr/docs/alternatives.md
Le système d'injection de dépendances exige le pré-enregistrement des dépendances et les dépendances sont résolues sur la base des types déclarés. Ainsi, il n'est pas possible de déclarer plus d'un "composant" qui fournit un certain type. Les routes sont déclarées à un seul endroit, en utilisant des fonctions déclarées à d'autres endroits (au lieu d'utiliser des décorateurs qui peuvent être placés juste au-dessus de la fonction qui gère l'endpoint). Cette
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sat Nov 09 16:39:20 UTC 2024 - 27.5K bytes - Viewed (0) -
docs/es/docs/tutorial/security/get-current-user.md
Pero eso aún no es tan útil. Vamos a hacer que nos dé el usuario actual. ## Crear un modelo de usuario Primero, vamos a crear un modelo de usuario con Pydantic. De la misma manera que usamos Pydantic para declarar cuerpos, podemos usarlo en cualquier otra parte: {* ../../docs_src/security/tutorial002_an_py310.py hl[5,12:6] *} ## Crear una dependencia `get_current_user` Vamos a crear una dependencia `get_current_user`.
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Mon Dec 30 18:26:57 UTC 2024 - 4.3K bytes - Viewed (0) -
CHANGELOG/CHANGELOG-1.29.md
- Fixed a situation when, sometimes, the scheduler incorrectly placed a pod in the `unschedulable` queue instead of the `backoff` queue. This happened when some plugin previously declared the pod as `unschedulable` and then in a later attempt encounters some other error. Scheduling of that pod then got delayed by up to five minutes, after which periodic flushing moved the pod back into the `active` queue. ([#120334](https://github.com/kubernetes/kubernetes/pull/120334), [@pohly](https://github.com/pohly))...
Registered: Fri Sep 05 09:05:11 UTC 2025 - Last Modified: Wed Mar 12 00:36:01 UTC 2025 - 429.6K bytes - Viewed (1) -
docs/en/docs/tutorial/body-fields.md
# Body - Fields { #body-fields } The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`. ## Import `Field` { #import-field } First, you have to import it: {* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *} /// warning
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sun Aug 31 09:15:41 UTC 2025 - 2.3K bytes - Viewed (0) -
docs/en/docs/tutorial/body-nested-models.md
This will make `tags` be a list, although it doesn't declare the type of the elements of the list. ## List fields with type parameter { #list-fields-with-type-parameter } But Python has a specific way to declare lists with internal types, or "type parameters": ### Import typing's `List` { #import-typings-list } In Python 3.9 and above you can use the standard `list` to declare these type annotations as we'll see below. 💡
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sun Aug 31 09:15:41 UTC 2025 - 7.3K bytes - Viewed (0) -
docs/pt/docs/tutorial/bigger-applications.md
```Python hl_lines="1 3" title="app/routers/users.py" {!../../docs_src/bigger_applications/app/routers/users.py!} ``` ### *Operações de Rota* com `APIRouter` E então você o utiliza para declarar suas *operações de rota*. Utilize-o da mesma maneira que utilizaria a classe `FastAPI`: ```Python hl_lines="6 11 16" title="app/routers/users.py" {!../../docs_src/bigger_applications/app/routers/users.py!} ```
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sun May 11 13:37:26 UTC 2025 - 19.6K bytes - Viewed (0) -
docs/en/docs/tutorial/cookie-params.md
## Import `Cookie` { #import-cookie } First import `Cookie`: {* ../../docs_src/cookie_params/tutorial001_an_py310.py hl[3] *} ## Declare `Cookie` parameters { #declare-cookie-parameters } Then declare the cookie parameters using the same structure as with `Path` and `Query`. You can define the default value as well as all the extra validation or annotation parameters:
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sun Aug 31 09:15:41 UTC 2025 - 1.1K bytes - Viewed (0) -
docs/en/docs/tutorial/query-params.md
You can declare multiple path parameters and query parameters at the same time, **FastAPI** knows which is which. And you don't have to declare them in any specific order. They will be detected by name: {* ../../docs_src/query_params/tutorial004_py310.py hl[6,8] *} ## Required query parameters { #required-query-parameters }
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