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docs/es/docs/deployment/versions.md
## Acerca de las versiones Siguiendo las convenciones de *Semantic Versioning*, cualquier versión por debajo de `1.0.0` puede potencialmente tener <abbr title="cambios que rompen funcionalidades o compatibilidad">*breaking changes*</abbr>.
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CONTRIBUTING.md
file). 3. Files should be formatted according to Google's [Java style guide][]. 4. Please squash all commits for a change into a single commit (this can be done using `git rebase -i`). Do your best to have a [well-formed commit message][] for the change. [Java style guide]: https://google.github.io/styleguide/javaguide.html
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docs/es/docs/features.md
### Simplemente Python moderno Todo está basado en las declaraciones de tipo de **Python 3.8** estándar (gracias a Pydantic). No necesitas aprender una sintaxis nueva, solo Python moderno. Si necesitas un repaso de 2 minutos de cómo usar los tipos de Python (así no uses FastAPI) prueba el tutorial corto: [Python Types](python-types.md){.internal-link target=_blank}. Escribes Python estándar con tipos así: ```Python
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docs/es/docs/tutorial/first-steps.md
Lo pones encima de una función. Es como un lindo sombrero decorado (creo que de ahí salió el concepto). Un "decorador" toma la función que tiene debajo y hace algo con ella. En nuestro caso, este decorador le dice a **FastAPI** que la función que está debajo corresponde al **path** `/` con una **operación** `get`. Es el "**decorador de operaciones de path**". También puedes usar las otras operaciones:
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CONTRIBUTING.md
you're running the same code that you're testing: * Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/) `pip install -U tf-nightly` * Rebase your pull request onto a recent pull from [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch. 2. If you are changing the code and the docstring of a class/function/method,
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docs/pt/docs/tutorial/path-params.md
!!! check "Verifique" Então, com a mesma declaração de tipo do Python, o **FastAPI** dá pra você validação de dados. Observe que o erro também mostra claramente o ponto exato onde a validação não passou. Isso é incrivelmente útil enquanto se desenvolve e debuga o código que interage com a sua API. ## Documentação
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docs/en/docs/async.md
### Concurrency and Burgers This idea of **asynchronous** code described above is also sometimes called **"concurrency"**. It is different from **"parallelism"**. **Concurrency** and **parallelism** both relate to "different things happening more or less at the same time". But the details between *concurrency* and *parallelism* are quite different. To see the difference, imagine the following story about burgers:
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docs/es/docs/tutorial/path-params.md
Podrías necesitar que el parámetro contenga `/home/johndoe/myfile.txt` con un slash inicial (`/`). En este caso la URL sería `/files//home/johndoe/myfile.txt` con un slash doble (`//`) entre `files` y `home`. ## Repaso Con **FastAPI**, usando declaraciones de tipo de Python intuitivas y estándares, obtienes: * Soporte en el editor: chequeo de errores, auto-completado, etc.
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common-protos/k8s.io/apimachinery/pkg/apis/meta/v1/generated.proto
// FieldManager is required for apply requests. // ApplyOptions is equivalent to PatchOptions. It is provided as a convenience with documentation // that speaks specifically to how the options fields relate to apply. message ApplyOptions { // When present, indicates that modifications should not be // persisted. An invalid or unrecognized dryRun directive will // result in an error response and no further processing of the
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RELEASE.md
which drops erroneous elements from `Dataset`s. * Added [`tf.data.Dataset.rebatch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset#rebatch), a new API for rebatching the elements of a dataset. * `tf.distribute`: * Added
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