lambdacasserole/lizard

Lempel–Ziv–Welch data compression Maven package for Java.

Download

Step 1. Add the JitPack repository to your build file

Add it in your root settings.gradle at the end of repositories:

	dependencyResolutionManagement {
		repositoriesMode.set(RepositoriesMode.FAIL_ON_PROJECT_REPOS)
		repositories {
			mavenCentral()
			maven { url 'https://jitpack.io' }
		}
	}

Add it in your settings.gradle.kts at the end of repositories:

	dependencyResolutionManagement {
		repositoriesMode.set(RepositoriesMode.FAIL_ON_PROJECT_REPOS)
		repositories {
			mavenCentral()
			maven { url = uri("https://jitpack.io") }
		}
	}

Add to pom.xml

	<repositories>
		<repository>
		    <id>jitpack.io</id>
		    <url>https://jitpack.io</url>
		</repository>
	</repositories>

Add it in your build.sbt at the end of resolvers:

 
    resolvers += "jitpack" at "https://jitpack.io"

Add it in your project.clj at the end of repositories:

 
    :repositories [["jitpack" "https://jitpack.io"]]

Step 2. Add the dependency

	dependencies {
		implementation 'com.github.lambdacasserole:lizard:v1.0'
	}

	dependencies {
		implementation("com.github.lambdacasserole:lizard:v1.0")
	}

	<dependency>
	    <groupId>com.github.lambdacasserole</groupId>
	    <artifactId>lizard</artifactId>
	    <version>v1.0</version>
	</dependency>


                            
    libraryDependencies += "com.github.lambdacasserole" % "lizard" % "v1.0"


                            
    :dependencies [[com.github.lambdacasserole/lizard "v1.0"]]

Readme

Lizard

Lempel–Ziv–Welch data compression Maven package for Java.

Lizard is a compression library designed to apply LZW compression over byte arrays. When you need to squeeze some data down to a smaller size (for transmission over a network, for example) LZW is a good choice in a pinch. It'll give you a smaller byte array (usually) and you won't need to transfer any kind of lookup table along with your data for decompression (like you would with Huffman coding for instance).

Specifications

The term "LZW compression" is pretty vague. More specifically, Lizard:

Uses fixed-length, 16-bit codes.
Clears the dictionary as soon as it becomes full.

Installation

You can pull this package into your Maven project straight from here using JitPack. Add JitPack as a repository first:

<repositories>
    <repository>
        <id>jitpack.io</id>
        <url>https://jitpack.io</url>
    </repository>
</repositories>

Then add a dependency on Lizard:

<dependencies>
    <dependency>
        <groupId>com.github.lambdacasserole</groupId>
        <artifactId>lizard</artifactId>
        <version>v1.0</version>
    </dependency>
</dependencies>

Limitations

Lizard won't produce archive files out-of-the-box. It's a lower-level tool for dealing with LZW compression directly. It is not optimized for speed, memory efficiency or performance. This is a naïve implementation and oh boy is it slow. Seriously, I literally use hexadecimal strings to build dictionary entries (yeah, I know). Note also that the code dictionary is cleared as soon as it becomes full. This creates a way-less-than-optimal compression ratio.

Benchmarks

Once again, this package isn't designed for straight-up file compression out of the box. If you do use it for that, however, here are some benchmarks running against the Canterbury Corpus. Times are for a 1.58GHz x64 CPU with 4GB available RAM.

| File | Uncompressed (Bytes) | Compressed (Bytes) | Ratio | Space Saving | Time (ms) | |--------------|----------------------|--------------------|-------|--------------|-----------| | alice29.txt | 152089 | 74148 | 2.05 | 51% | 506.3 | | asyoulik.txt | 125179 | 62748 | 1.99 | 50% | 183.8 | | cp.html | 24603 | 14948 | 1.65 | 39% | 17.2 | | fields.c | 11150 | 7084 | 1.57 | 36% | 11.9 | | grammar.lsp | 3721 | 2818 | 1.32 | 24% | 2.5 | | kennedy.xls | 1029744 | 339080 | 3.03 | 67% | 1608.1 | | lcet10.txt | 426754 | 203626 | 2.10 | 52% | 556.0 | | plrabn12.txt | 481861 | 243968 | 1.98 | 49% | 771.5 | | ptt5 | 513216 | 72850 | 7.04 | 86% | 1127.4 | | sum | 38240 | 25054 | 1.53 | 34% | 88.6 | | xargs.1 | 4227 | 3584 | 1.18 | 15% | 2.5 |

Contributing

For most intents and purposes, Lizard is considered to fulfil its original use case. Bug fixes and suggestions are welcome, however, from any member of the community.