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Deploying an Artifact to the Local Cache in Gradle

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Deploying an Artifact to the Local Cache in Gradle

· Java Zone ·
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Learn how to build stream processing applications in Java-includes reference application. Brought to you in partnership with Hazelcast.

One question that came up a couple times this week is how to set gradle up to deploy jars locally. For the most part I was satisfied with just having people push snapshot releases to our Artifactory server but some people did express a real desire to be able to publish a jar to the local resolution cache to test changes out locally. I’m still a fan of deploying snapshots from feature branches but luckily you can do a local publish and resolve with gradle. 

First off, ask yourself if the dependency is coupled enough to warrant being a submodule. Also, could just linking the project in your IDE be enough to get what you want done? If the answer to both questions are no then your next recourse is to use gradle’s excellent maven compatibility (don’t run!). :)

For the project you want to publish locally you simply need to apply the maven plugin and make sure you have version and group set for the project (usually I put group and version in gradle.properties).

apply plugin: 'java'
apply plugin: 'maven'

version = '0.5.1-SNAPSHOT'
group = 'org.jamescarr.examples'

That’s all you need to install it locally, just run gradle install from the project root to install it to the local m2 cache. Now let’s update your project that will depend on it.

...

repositories {
  mavenCentral()
  mavenLocal()
}

dependencies {
  compile('org.jamecarr.examples:example-api:0.5.1-SNAPSHOT'){
    changing=true
  }
}

 

The magic sauce here is using mavenLocal() as one of your resolution repositories. This will resolve against the local m2 cache. mavenCentral() can be replaced by whatever repositories you might use, it is only included since it’s the most often used.

That’s it! I know some people dislike this approach due to ingrained disdain for maven but the beauty of it is that maven is silently at work and you really don’t get bothered by it. :)

Learn how to build distributed stream processing applications in Java that elastically scale to meet demand- includes reference application.  Brought to you in partnership with Hazelcast.

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