purge:
          # retainVersions: 0 # (default) delete all versions of the object. This option is the fastest.
          # retainVersions: 5 # keep the latest 5 versions of the object including delete markers.

  notify:
    endpoint: https://notify.endpoint # notification endpoint to receive job completion status
    token: Bearer xxxxx # optional authentication token for the notification endpoint
  
  retry:

 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.core.xml;

import javax.xml.parsers.DocumentBuilder;

import junit.framework.TestCase;

import org.codelibs.core.io.ResourceUtil;
import org.w3c.dom.Document;
import org.w3c.dom.Element;

/**
 * @author higa
 *
 */

that if active-active replication is set up with delete marker replication, there is potential for duplicate delete markers to be created if both source and target concurrently set a Delete Marker or if one/both of the clusters went down at tandem before the replication event was synced.This is an unavoidable side-effect in active-active replication caused by allowing delete markers set on a object version with `REPLICA` status back to source.

In the case of versioned deletes a.k.a permanent...

     */
    ModelSource resolveModel(Dependency dependency) throws UnresolvableModelException;

    /**
     * Adds a repository to use for subsequent resolution requests. The order in which repositories are added matters,
     * repositories that were added first should also be searched first. When multiple repositories with the same
     * identifier are added, only the first repository being added will be used.
     *

Está diseñado para tener funciones que reciben dos parámetros, un "request" y un "response". Luego "lees" partes del request y "escribes" partes en el response. Debido a este diseño, no es posible declarar parámetros de request y cuerpos con las anotaciones de tipos estándar de Python como parámetros de función.

Ele é projetado para ter funções que recebem dois parâmetros, uma "request" e uma "response". Então você "lê" partes da requisição, e "escreve" partes para a resposta. Por causa desse design, não é possível declarar parâmetros de requisição e corpos com as anotações de tipo padrão do Python como parâmetros de função.

 */
package org.codelibs.core.xml;

import static org.codelibs.core.misc.AssertionUtil.assertArgumentNotNull;

import java.io.IOException;
import java.io.InputStream;

import javax.xml.parsers.DocumentBuilder;

import org.codelibs.core.exception.IORuntimeException;
import org.codelibs.core.exception.SAXRuntimeException;
import org.w3c.dom.Document;
import org.xml.sax.SAXException;

/**

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Several of these are explored in the next chapters of the tutorial.

## Order matters { #order-matters }

When creating *path operations*, you can find situations where you have a fixed path.

Like `/users/me`, let's say that it's to get data about the current user.

import org.gradle.internal.util.PropertiesUtils
import org.gradle.work.DisableCachingByDefault
import org.w3c.dom.Element
import java.util.Properties
import javax.xml.XMLConstants
import javax.xml.parsers.DocumentBuilderFactory

@DisableCachingByDefault(because = "Not worth tracking")
abstract class AbstractVersionsUpdateTask : DefaultTask() {

    @get:Internal
    abstract val comment: Property<String>

#

[![GoDoc](https://godoc.org/github.com/bcicen/jstream?status.svg)](https://godoc.org/github.com/bcicen/jstream)


`jstream` is a streaming JSON parser and value extraction library for Go.

Unlike most JSON parsers, `jstream` is document position- and depth-aware -- this enables the extraction of values at a specified depth, eliminating the overhead of allocating encompassing arrays or objects; e.g:

Using the below example document: