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

Vous pouvez aussi retourner des models **Pydantic** (qui seront détaillés plus tard).

Il y a de nombreux autres objets et modèles qui seront automatiquement convertis en JSON. Essayez d'utiliser vos favoris, il est fort probable qu'ils soient déjà supportés.

## Récapitulatif

* Importez `FastAPI`.
* Créez une instance d'`app`.

    }

    private static final long serialVersionUID = 1;
  }

  /**
   * Returns a serializable converter object that converts between strings and doubles using {@link
   * Double#valueOf} and {@link Double#toString()}.
   *
   * @since 16.0
   */
  public static Converter<String, Double> stringConverter() {
    return DoubleConverter.INSTANCE;
  }

  /**

     */
    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

 * limitations under the License.
 */
package okhttp3.internal.idn

import okio.Buffer
import okio.ByteString.Companion.encodeUtf8

/**
 * An [RFC 3492] punycode decoder for converting ASCII to Unicode domain name labels. This is
 * intended for use in Internationalized Domain Names (IDNs).
 *
 * This class contains a Kotlin implementation of the pseudocode specified by RFC 3492. It includes

import org.apache.logging.log4j.Logger;
import org.codelibs.core.lang.StringUtil;
import org.codelibs.fess.suggest.analysis.SuggestAnalyzer;
import org.codelibs.fess.suggest.constants.FieldNames;
import org.codelibs.fess.suggest.converter.ReadingConverter;
import org.codelibs.fess.suggest.exception.SuggesterException;
import org.codelibs.fess.suggest.index.SuggestIndexer;
import org.codelibs.fess.suggest.normalizer.Normalizer;

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&...

* Um parâmetro de consulta `q` opcional do tipo `str`.
* Um parâmetro de consulta `skip` do tipo `int`, com valor padrão `0`.
* Um parâmetro de consulta `limit` do tipo `int`, com valor padrão `100`.

Os dados serão convertidos, validados, documentados no esquema da OpenAPI e etc nos dois casos.

## Utilizando

Agora você pode declarar sua dependência utilizando essa classe.

//// tab | Python 3.10+

```Python hl_lines="19"

    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of output data: converting from Python data and types to network data (as JSON):
    * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
    * `datetime` objects.
    * `UUID` objects.
    * Database models.

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.suggest.converter;

import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

import com.ibm.icu.text.Transliterator;