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docs/es/docs/advanced/response-directly.md
## Usando el `jsonable_encoder` en una `Response` Como **FastAPI** no realiza ningún cambio en la `Response` que devuelves, debes asegurarte de que el contenido está listo. Por ejemplo, no puedes poner un modelo Pydantic en una `JSONResponse` sin primero convertirlo a un `dict` con todos los tipos de datos (como `datetime`, `UUID`, etc) convertidos a tipos compatibles con JSON.
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docs/es/docs/index.md
</p> <p align="center"> FastAPI framework, alto desempeño, fácil de aprender, rápido de programar, listo para producción </p> <p align="center"> <a href="https://github.com/tiangolo/fastapi/actions?query=workflow%3ATest" target="_blank"> <img src="https://github.com/tiangolo/fastapi/workflows/Test/badge.svg" alt="Test">
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docs/fr/docs/tutorial/query-params-str-validations.md
] } ``` #### Utiliser `list` Il est aussi possible d'utiliser directement `list` plutôt que `List[str]` : ```Python hl_lines="7" {!../../../docs_src/query_params_str_validations/tutorial013.py!} ``` !!! note Dans ce cas-là, **FastAPI** ne vérifiera pas le contenu de la liste.
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docs/de/docs/tutorial/body-nested-models.md
```Python my_list: list[str] ``` Und in Python-Versionen vor 3.9: ```Python from typing import List my_list: List[str] ``` Das ist alles Standard-Python-Syntax für Typdeklarationen. Verwenden Sie dieselbe Standardsyntax für Modellattribute mit inneren Typen. In unserem Beispiel können wir also bewirken, dass `tags` spezifisch eine „Liste von Strings“ ist: === "Python 3.10+" ```Python hl_lines="12"
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tests/test_compat.py
# to be read from files and other types, but I'm not even sure it's a good idea # to support it as a first class "feature" assert is_bytes_sequence_annotation(Union[List[str], List[bytes]]) def test_is_uploadfile_sequence_annotation(): # For coverage # TODO: in theory this would allow declaring types that could be lists of UploadFile
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docs/em/docs/advanced/nosql-databases.md
📥 👥 🔜 👀 🖼 ⚙️ **<a href="https://www.couchbase.com/" class="external-link" target="_blank">🗄</a>**, <abbr title="Document here refers to a JSON object (a dict), with keys and values, and those values can also be other JSON objects, arrays (lists), numbers, strings, booleans, etc.">📄</abbr> 🧢 ☁ 💽. 👆 💪 🛠️ ⚫️ 🙆 🎏 ☁ 💽 💖: * **✳** * **👸** * **✳** * **🇸🇲** * **✳**, ♒️. !!! tip
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docs/en/docs/tutorial/response-model.md
`response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`. FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration. !!! tip
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docs/fr/docs/external-links.md
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docs/pt/docs/tutorial/query-params-str-validations.md
"bar" ] } ``` #### Usando `list` Você também pode utilizar o tipo `list` diretamente em vez de `List[str]`: ```Python hl_lines="7" {!../../../docs_src/query_params_str_validations/tutorial013.py!} ``` !!! note "Observação" Tenha em mente que neste caso, o FastAPI não irá validar os conteúdos da lista.
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docs/de/docs/tutorial/query-params-str-validations.md
``` !!! note "Hinweis" Beachten Sie, dass FastAPI in diesem Fall den Inhalt der Liste nicht überprüft. Zum Beispiel würde `List[int]` überprüfen (und dokumentieren) dass die Liste Ganzzahlen enthält. `list` alleine macht das nicht. ## Deklarieren von mehr Metadaten Sie können mehr Informationen zum Parameter hinzufügen.
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