A Micronaut configuration that integrates your app with an existing Jupyter installation.

A special Micronaut kernel is provided to Jupyter that can be used to run notebooks. This kernel can:

• Execute Groovy code
• Import classes on your Micronaut app's classpath
• Access Micronaut beans
• Use Micronaut Data repositories
• Use GORM Data Services and dynamic finders
• Access functionality available to the BeakerX Groovy kernel
  • Note: This requires that the beakerx Python package (and possibly other Jupyter packages) be installed on the system separately.

The micronaut2 branch of this repository has been updated to support Micronaut 2.0+, however, it requires BeakerX 2.0 libraries which have not yet been published by the BeakerX project team at the time of this writing. To build the required libraries locally, follow these steps:

git clone --recurse-submodules https://github.com/stainlessai/beakerx-jlab2  

cd beakerx-jlab2/beakerx_kernel_base
./gradlew install -xtest        

cd ../beakerx_kernel_groovy
./gradlew install -xtest

The beakerx-*-2.0-SNAPSHOT jars should now be in your local maven cache, e.g.:

~/.m2/repository/com/twosigma/beakerx-kernel-base/2.0-SNAPSHOT/beakerx-kernel-base-2.0-SNAPSHOT.jar 

Build the library and publish to local maven:

./gradlew publishToMavenLocal

To set a specific version on your library:

./gradlew publishToMavenLocal -PprojectVersion=0.0.1-mysemanticversion

Ensure the following repositories are added to your gradle build:

repositories {
    mavenCentral()
    maven { url 'https://jitpack.io' }
}

Add the following dependency to your gradle build:

dependencies {
    implementation "ai.stainless:micronaut-jupyter:0.2.4"
}

Ensure that your app can write to a directory where Jupyter will search for kernels.

The default directory is /usr/local/share/jupyter/kernels, so the following is sufficient:

chmod 777 /usr/local/share/jupyter/kernels

Create a separate directory, say at /opt/jupyter-alt/kernels, that your app can write to. Then, configure Jupyter to search this directory using JUPYTER_PATH. Lastly, add the following config to your application.yml:

jupyter:
  kernel:
    location: /opt/jupyter-alt/kernels

When your app starts up, this configuration will make any necessary configurations to Jupyter. Once both your app and Jupyter are running, login to Jupyter to start using the features.

See the /examples directory for example apps that use this configuration along with sample Jupyter notebooks that take advantage of the available features.

The master branch contains the latest production release. The develop branch contains the latest stable build. It is recommended that most PRs be submitted to the develop branch in order to ensure that they are based on the most recent version of the code. Most PRs that are submitted to master will be rebased onto develop. Exceptions to this would include things like critical bugfixes that need to be pushed ahead of the next planned release.

In order to run the tests, you must have Docker installed on your dev environment. The tests use a library called Testcontainers, so you'll need to meet its system requirements (see link) in order to run the tests. The tests run in Travis CI out of the box; on a local machine, installing Docker Desktop should be sufficient.

Run all the tests:

./gradlew test

Run integration and unit tests separately

./gradlew integrationTest
./gradlew unitTest

Gradle's --tests option won't apply to subtasks, so use -Ptests to filter the tests:

./gradlew test -Ptests=*BasicGroovy*
./gradlew integrationTest -Ptests=*Finder*

• Import classes on app classpath in Jupyter script
• Access GORM methods in Jupyter scripts
• Access beans in Jupyter script
• Ability to add custom methods and properties to scope of Jupyter script
• Access GORM Data Services from Jupyter script
• Access Micronaut Data repositories from Jupyter script