**Desplegar** una aplicación significa realizar una serie de pasos para hacerla **disponible para los usuarios**.

Para una **API web**, normalmente implica ponerla en una **máquina remota**, con un **programa de servidor** que proporcione un buen rendimiento, estabilidad, etc, para que sus **usuarios** puedan **acceder** a la aplicación de manera eficiente y sin interrupciones o problemas.

      for (Entry<E> entry : insertionOrder) {
        map.put(entry.getElement(), entry);
      }

      Set<E> seen = new HashSet<>();
      List<Entry<E>> order = new ArrayList<>();
      for (E e : gen.order(new ArrayList<E>(map.keySet()))) {
        if (seen.add(e)) {
          order.add(map.get(e));
        }
      }
      return order;
    }
  }

import static java.lang.annotation.ElementType.METHOD;
import static java.lang.annotation.ElementType.TYPE;
import static java.lang.annotation.RetentionPolicy.RUNTIME;

/**
 * Indicates that the annotated bean has a lifespan limited to a given mojo execution,
 * which means each mojo execution will result in a different instance being injected.
 * <p>
 * The following objects will be bound to the mojo execution scope:
 *     <ul>

            if (data != null) {
                ((OpenSearchAccessResult) bean).setAccessResultData(new OpenSearchAccessResultData(data));
            }
            setId(bean, id);
            return bean;
        }
        return null;
    }

///

```Python hl_lines="11"
{!> ../../docs_src/path_params_numeric_validations/tutorial006.py!}
```

////

## Recap

With `Query`, `Path` (and others you haven't seen yet) you can declare metadata and string validations in the same ways as with [Query Parameters and String Validations](query-params-str-validations.md){.internal-link target=_blank}.

And you can also declare numeric validations:

                    randomSamplingPercentage:
                      description: Controls the rate at which traffic will be selected
                        for tracing if no prior sampling decision has been made.
                      format: double
                      maximum: 100
                      minimum: 0
                      nullable: true
                      type: number

```Python hl_lines="17-22  24"
{!../../docs_src/path_operation_advanced_configuration/tutorial007.py!}
```

Néanmoins, bien que nous n'utilisions pas la fonctionnalité par défaut, nous utilisons toujours un modèle Pydantic pour générer manuellement le schéma JSON pour les données que nous souhaitons recevoir en YAML.

 * limitations under the License.
 */

package com.google.common.math;

import com.google.common.testing.AbstractPackageSanityTests;

/**
 * Basic sanity tests for the entire package.
 *
 * @author Ben Yu
 */

public class PackageSanityTests extends AbstractPackageSanityTests {
  public PackageSanityTests() {
    publicApiOnly();
  }

        int clen = s.length();
        int blen = 2 * clen;
        byte[] b = new byte[blen];
        char[] c = new char[clen];
        s.getChars(0, clen, c, 0);
        for ( int i = 0, j = 0; i < clen; i++ ) {
            b[ j++ ] = (byte) ( c[ i ] >>> 8 );
            b[ j++ ] = (byte) ( c[ i ] >>> 0 );
        }
        write(b, 0, blen);
    }


    @Override

# Advanced Dependencies

## Parameterized dependencies

All the dependencies we have seen are a fixed function or class.

But there could be cases where you want to be able to set parameters on the dependency, without having to declare many different functions or classes.

Let's imagine that we want to have a dependency that checks if the query parameter `q` contains some fixed content.

But we want to be able to parameterize that fixed content.