**Déployer** une application signifie effectuer les étapes nécessaires pour la rendre **disponible pour les
utilisateurs**.

Pour une **API Web**, cela implique normalement de la placer sur une **machine distante**, avec un **programme serveur**
qui offre de bonnes performances, une bonne stabilité, _etc._, afin que vos **utilisateurs** puissent **accéder** à
l'application efficacement et sans interruption ni problème.

Eso, más el simple hecho de que Python es el lenguaje principal para **Data Science**, Machine Learning y especialmente Deep Learning, hacen de FastAPI una muy buena opción para APIs web de Data Science / Machine Learning y aplicaciones (entre muchas otras).

Para ver cómo lograr este paralelismo en producción, consulta la sección sobre [Despliegue](deployment/index.md).

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)

* API key: API key (do not translate to "clave API")
* 100% test coverage: cobertura de tests del 100%
* back and forth: de un lado a otro
* I/O (as in "input and output"): I/O (do not translate to "E/S")
* Machine Learning: Machine Learning (do not translate to "Aprendizaje Automático")
* Deep Learning: Deep Learning (do not translate to "Aprendizaje Profundo")
* callback hell: callback hell (do not translate to "infierno de callbacks")

 |
 |                 -s /path/to/user/settings.xml
 |
 |  2. Installation Level.
 |                 This settings.xml file provides configuration for all Maven
 |                 users on a machine (assuming they're all using the same Maven
 |                 installation). It's normally provided in
 |                 ${maven.installation.conf}/settings.xml.
 |

Ça, ajouté au fait que Python soit le langage le plus populaire pour la **Data Science**, le **Machine Learning** et surtout le **Deep Learning**, font de **FastAPI** un très bon choix pour les APIs et applications de **Data Science** / **Machine Learning**.

import org.apache.maven.api.annotations.Experimental;
import org.apache.maven.api.annotations.Immutable;
import org.apache.maven.api.annotations.Nonnull;

/**
 * <p>The <dfn>local repository</dfn> is a directory on the developer's machine where
 * Maven stores all the downloaded artifacts (such as dependencies, plugins,
 * and project artifacts). When Maven builds a project, it first checks the

#
#	GOOS=linux GOARCH=ppc64 bootstrap.bash
#
# this script cross-compiles a toolchain for that GOOS/GOARCH
# combination, leaving the resulting tree in ../../go-${GOOS}-${GOARCH}-bootstrap.
# That tree can be copied to a machine of the given target type
# and used as $GOROOT_BOOTSTRAP to bootstrap a local build.
#
# Only changes that have been committed to Git (at least locally,
# not necessary reviewed and submitted to master) are included in the tree.

## `fastapi run` { #fastapi-run }

Executing `fastapi run` starts FastAPI in production mode.

- Mozilla Developer Network: Мережа Розробників Mozilla
- tutorial: навчальний посібник
- advanced user guide: просунутий посібник користувача
- deep learning: глибоке навчання
- machine learning: машинне навчання
- dependency injection: впровадження залежностей
- digest (HTTP): дайджест
- basic authentication (HTTP): базова автентифікація
- JSON schema: Схема JSON
- password flow: потік паролю