TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized
in taking those formats, modifying them, and/or converting them to intermediate
formats that can be processed by TensorFlow.

These modifications and conversions are handled by a variety of libraries that
have different security properties and provide different levels of confidence

                    that `password`.
                * Validation: whatever you return will be serialized with the
                    `response_model`, converting any data as necessary to generate the
                    corresponding JSON. But if the data in the object returned is not
                    valid, that would mean a violation of the contract with the client,

    consistent with the length of the response body.

 *  Fix: Don't crash when converting a `HttpUrl` instance with an unresolvable hostname to a URI.
    The new behavior strips invalid characters like `"` and `{` from the hostname before converting.

 *  Fix: Undo a performance regression introduced in OkHttp 4.0 caused by differences in behavior

     */
    checkState(future.isDone(), "Future was expected to be done: %s", future);
    return getUninterruptibly(future);
  }

  /**
   * Returns the result of {@link Future#get()}, converting most exceptions to a new instance of the
   * given checked exception type. This reduces boilerplate for a common use of {@code Future} in

constraints.TypeLong.message = {item} deve ser um número.
constraints.TypeFloat.message = {item} deve ser um número.
constraints.TypeDouble.message = {item} deve ser um número.
constraints.TypeAny.message = {item} não pode ser convertido para {propertyType}.
constraints.UriType.message = {item} tem uma URI não reconhecida.
constraints.CronExpression.message = {item} não é uma expressão CRON válida.

# ----------------------------------------------------------

s)if(s[i]&&s[i].test(r)){u.unshift(i);break}if(u[0]in n)o=u[0];else{for(i in n){if(!u[0]||e.converters[i+" "+u[0]]){o=i;break}a||(a=i)}o=o||a}if(o)return o!==u[0]&&u.unshift(o),n[o]}(v,T,n)),!i&&-1<ce.inArray("script",v.dataTypes)&&ce.inArray("json",v.dataTypes)<0&&(v.converters["text script"]=function(){}),s=function(e,t,n,r){var i,o,a,s,u,l={},c=e.dataTypes.slice();if(c[1])for(a in e.converters)l[a.toLowerCase()]=e.converters[a];o=c.shift();while(o)if(e.responseFields[o]&&(n[e.responseFields[o]]=t),!u&&r&...

                    that `password`.
                * Validation: whatever you return will be serialized with the
                    `response_model`, converting any data as necessary to generate the
                    corresponding JSON. But if the data in the object returned is not
                    valid, that would mean a violation of the contract with the client,

Vous déclarez la « forme » de la donnée sous forme de classes avec des attributs.

Et chaque attribut a un type.

Ensuite, vous créez une instance de cette classe avec certaines valeurs et elle validera les valeurs, les convertira dans le type approprié (le cas échéant) et vous donnera un objet avec toutes les données.

Et vous obtenez tout le support de l'éditeur avec cet objet résultant.

Un exemple tiré de la documentation officielle de Pydantic :

Il convertira ensuite et validera les données. Ainsi, lorsque vous utilisez cet objet `settings`, vous aurez des données des types que vous avez déclarés (par exemple, `items_per_user` sera un `int`).

### Utiliser `settings` { #use-the-settings }

Puedes retornar un `dict`, `list`, valores singulares como `str`, `int`, etc.

También puedes retornar modelos de Pydantic (verás más sobre eso más adelante).

Hay muchos otros objetos y modelos que serán automáticamente convertidos a JSON (incluyendo ORMs, etc). Intenta usar tus favoritos, es altamente probable que ya sean compatibles.

### Paso 6: Despliégalo { #step-6-deploy-it }