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Updated README.md, v1.0.0
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README.md

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This is a companion library to [the identical Python version](https://github.com/jlumbroso/python-random-hash).
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A [JAR file](https://github.com/jlumbroso/java-random-hash/releases/tag/v0.8.0) for this library can be downloaded from this repo, or it can be installed with [Apache Maven](https://maven.apache.org/guides/getting-started/maven-in-five-minutes.html) by adding the following to the `dependencies` section of your `pom.xml`:
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## Installation
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A [JAR file](https://github.com/jlumbroso/java-random-hash/releases/tag/v1.0.0) for this library can be downloaded from this repo.
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Alternatively, this library can also be installed with [Apache Maven](https://maven.apache.org/guides/getting-started/maven-in-five-minutes.html). First, add the following to the `dependencies` section of your `pom.xml`:
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```xml
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<dependency>
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<groupId>edu.princeton.cs.randomhash</groupId>
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<artifactId>randomhash</artifactId>
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<version>0.8.0</version>
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<version>1.0.0</version>
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</dependency>
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```
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Then run Maven:
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```shell
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$ mvn install
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```
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## Features
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This introduces a family of hash functions that can be used to implement probabilistic
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To try out the hash functions, you can compile and run the example program:
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```shell
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javac -cp 'randomhash-0.8.0.jar:.' Example.java
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java -cp 'randomhash-0.8.0.jar:.' Example
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javac -cp 'randomhash-1.0.0.jar:.' Example.java
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java -cp 'randomhash-1.0.0.jar:.' Example
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```
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This will generate a report, such as the one below, which shows how a hundred

pom.xml

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<groupId>edu.princeton.cs</groupId>
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<artifactId>randomhash</artifactId>
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<packaging>jar</packaging>
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<version>0.8.0</version>
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<version>1.0.0</version>
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<name>randomhash</name>
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<url>https://github.com/jlumbroso/java-random-hash</url>
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<description>

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