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Development Guide

Git workflow

You should follow the git workflow to contribute, fork the repo and pull request

Dev Dependencies

  • This project use JDK17 & Maven
  • Springboot 3.0+
  • lombok plugin
  • For macOS, you need install coreutils & wget via brew install
  • For ZenML spec, please refer to ZenML Introduction

Build

$ mvn clean install

Package

$ ./build/scripts/package.sh

package.sh generates tar.gz files as below:

  • General package without embedded openjdk17
    • Kyligence-ZenML-Toolkit-${project.version}.tar.gz
  • OS specific package with openjdk17
    • Kyligence-ZenML-Toolkit-Darwin-AArch64-${project.version}.tar.gz
    • Kyligence-ZenML-Toolkit-Darwin-x64-${project.version}.tar.gz
    • Kyligence-ZenML-Toolkit-Linux-x64-${project.version}.tar.gz

The openjdk17 is downloaded during package process, you can refer to build/scripts/download-jdk.sh for more details.

Docker Build

$ ./build/scripts/build_docker_image.sh

Start docker container

docker run -p 9000:9000 -dit kyligence/zenml-toolkit:${project.version}

Entry Class

For Command Line Interface Entry

We provide an CLI interface for user via command ./bin/zen.sh -i <arg> -o <arg>. The command options is defined in io.kyligence.zenml.toolkit.ZenMlToolkitCLI

For Server Interface Entry

We also provide a server mode and API for user to upload a file, the metrics metadata will be extracted to a ZenML file and an Excel file, compressed as a zip file to download.

The entry class is io.kyligence.zenml.toolkit.ZenMlToolkitServer

Debug

Debug io.kyligence.zenml.toolkit.ZenMlToolkitServer#main(), in debug configuration, you need to define an Environment variable named ZEN_HOME, the value is a directory path, put build/conf/toolkit.properties to $ZEN_HOME/conf/toolkit.properties

Frontend

See Frontend README

License

We use the Apache License 2.0, you should put the license content in the beginning of source code files