# Tipos de Datos Extra

Hasta ahora, has estado usando tipos de datos comunes, como:

* `int`
* `float`
* `str`
* `bool`

Pero también puedes usar tipos de datos más complejos.

Y seguirás teniendo las mismas funcionalidades como hasta ahora:

* Gran soporte de editor.
* Conversión de datos de requests entrantes.
* Conversión de datos para datos de response.
* Validación de datos.
* Anotación y documentación automática.

# Declarar Ejemplos de Request

Puedes declarar ejemplos de los datos que tu aplicación puede recibir.

Aquí tienes varias formas de hacerlo.

## Datos extra de JSON Schema en modelos de Pydantic

Puedes declarar `examples` para un modelo de Pydantic que se añadirá al JSON Schema generado.

//// tab | Pydantic v2

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

////

//// tab | Pydantic v1

Sebastián Ramírez <******@****.***> 1731896744 +0100

Sebastián Ramírez <******@****.***> 1731896744 +0100

    echo "Please remove the following extra licenses from $LICENSES_TARGET:"
    cat $BATS_TEST_TMPDIR/actual_extra_licenses
  fi

  if [[ -s $BATS_TEST_TMPDIR/actual_missing_licenses ]]; then
    echo "Please include the missing licenses for the following packages in $LICENSES_TARGET:"
    cat $BATS_TEST_TMPDIR/actual_missing_licenses
  fi

  # Fail if either of the two "extras" or "missing" lists are present. If so,

 *
 * <p>The extractor supports two types of password management:
 * <ul>
 *   <li>Static passwords configured via {@link #addPassword(String, String)}</li>
 *   <li>Dynamic passwords provided through extraction parameters</li>
 * </ul>
 *
 * <p>Passwords are matched against URLs or resource names using regular expression patterns.

 * 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.crawler.extractor.impl;

import java.io.InputStream;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.core.io.CloseableUtil;
import org.codelibs.core.io.ResourceUtil;

    // InputStream in =
    // ResourceUtil.getResourceAsStream("extractor/test_pass.pdf");
    // TikaExtractor extractor =
    // (TikaExtractor) getContainer().getComponent(
    // "tikaExtractorForPdfPassword");
    // Map<String, String> params = new HashMap<String, String>();
    // params.put(ExtractData.URL, "http://example.com/test_pass.pdf");
    // ExtractData extractData = extractor.getText(in, params);

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

"""Extracts ResultStore links from a log containing Bazel invocations.

The links and the invocations' status can then be printed out, or output in the
form of JUnit-based XML.
"""
import argparse
import datetime
import os

/**
 * A response processor implementation that handles sitemaps.
 * It parses the response body as a SitemapSet, extracts URLs from the sitemaps,
 * and adds them as child URLs to be crawled.
 *
 * <p>
 * This class uses a {@link SitemapsHelper} to parse the sitemap XML or text.
 * It then iterates through the sitemaps in the SitemapSet, extracts the URL
 * from each sitemap, and creates a new {@link RequestData} object for each URL.