<artifactId>tika-parser-html-module</artifactId>
			<version>${tika.version}</version>
		</dependency>
		<dependency>
			<groupId>org.apache.tika</groupId>
			<artifactId>tika-parser-image-module</artifactId>
			<version>${tika.version}</version>
		</dependency>
		<dependency>
			<groupId>org.apache.tika</groupId>
			<artifactId>tika-parser-mail-module</artifactId>

import java.util.Map;
import java.util.Set;

import org.apache.tika.metadata.ClimateForcast;
import org.apache.tika.metadata.CreativeCommons;
import org.apache.tika.metadata.Geographic;
import org.apache.tika.metadata.HttpHeaders;
import org.apache.tika.metadata.Message;
import org.apache.tika.metadata.TIFF;
import org.apache.tika.metadata.TikaCoreProperties;
import org.apache.tika.metadata.TikaMimeKeys;

/**

import org.apache.logging.log4j.Logger;
import org.apache.tika.config.TikaConfig;
import org.apache.tika.detect.Detector;
import org.apache.tika.exception.TikaException;
import org.apache.tika.extractor.EmbeddedDocumentExtractor;
import org.apache.tika.extractor.ParsingEmbeddedDocumentExtractor;
import org.apache.tika.io.TemporaryResources;
import org.apache.tika.io.TikaInputStream;
import org.apache.tika.metadata.Metadata;

/// info

<a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerasi (atau enum) tersedia di Python</a> sejak versi 3.4.

///

/// tip | Tips

"AlxexNet", "ResNet", dan "LeNet" adalah nama <abbr title="Secara teknis, arsitektur model Deep Learning">model</abbr> *Machine Learning*.

///

### Mendeklarasikan *parameter path*

import java.util.Arrays;
import java.util.Map;
import java.util.stream.Collectors;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.apache.tika.language.detect.LanguageDetector;
import org.apache.tika.language.detect.LanguageResult;
import org.codelibs.core.lang.StringUtil;
import org.codelibs.fess.mylasta.direction.FessConfig;
import org.codelibs.fess.util.ComponentUtil;

			<groupId>com.ibm.icu</groupId>
			<artifactId>icu4j</artifactId>
			<version>${icu4j.version}</version>
		</dependency>
		<dependency>
			<groupId>org.apache.tika</groupId>
			<artifactId>tika-langdetect-optimaize</artifactId>
			<version>${tika.version}</version>
			<exclusions>
				<exclusion>
					<groupId>javax.annotation</groupId>
					<artifactId>javax.annotation-api</artifactId>
				</exclusion>

    assertTrue(tokL.isSupertypeOf(new TypeToken<List<?>>() {}));

    TypeToken<Second> tokS = new TypeToken<Second>() {};
    assertTrue(tokS.isSupertypeOf(new TypeToken<Second>() {}));
    assertTrue(tokS.isSupertypeOf(new TypeToken<Third>() {}));
    assertTrue(tokS.isSupertypeOf(new TypeToken<Third<String, Integer>>() {}));

    TypeToken<List[]> tokA = new TypeToken<List[]>() {};

mihsim?ra&biah?honikam??tawi?wa&g&ekak?ukik??kijuf??yimonijuf??i&a&ra?sok??hcamirom?juf?kaz&eamo?ustam??ma&nnak?ta??nukonuzi?orukuf??nohenawak?o&nosus?ti??u&stamamah?z&a&mun?wak??i!ay?i&hs&agih?in??manim??mihs????????m&a&tias!.&a&d&ihsoy?ot?usah??k&a&dih?sa??o&arihs?s???m&a&tias?y&as?o&rom?tah??ustamihsagih???i&hsagurust?jawak??uri??ni?wa&g&e&ko?man??ikot?o??k&ara?i&hsoy?mak???ru?zorokot??y&a&g&amuk?ihsok?otah??kuf??imo??ziin??e&bakusak?ogawak?sogo?ttas?zokoy??i&baraw?h&cugawak?s&oyim?ubustam???...

    assertTrue(tokL.isSupertypeOf(new TypeToken<List<?>>() {}));

    TypeToken<Second> tokS = new TypeToken<Second>() {};
    assertTrue(tokS.isSupertypeOf(new TypeToken<Second>() {}));
    assertTrue(tokS.isSupertypeOf(new TypeToken<Third>() {}));
    assertTrue(tokS.isSupertypeOf(new TypeToken<Third<String, Integer>>() {}));

    TypeToken<List[]> tokA = new TypeToken<List[]>() {};

You can combine `dataclasses` with other type annotations in many different combinations to form complex data structures.

Check the in-code annotation tips above to see more specific details.

## Learn More { #learn-more }

You can also combine `dataclasses` with other Pydantic models, inherit from them, include them in your own models, etc.