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MMLSpark Development Setup

  1. Install SBT - Make sure to download JDK 1.8 if you don't have it
  2. Git Clone Repository - git clone https://github.com/Azure/mmlspark.git
  3. Run sbt to compile and grab datasets - cd mmlspark - sbt setup
  4. Install IntelliJ - Install Scala plugins during install
  5. Configure IntelliJ - OPEN the mmlspark directory - If the project does not automatically import,click on build.sbt and import project

Publishing and Using Build Secrets

To use secrets in the build you must be part of the mmlspark keyvault and azure subscription. If you are MSFT internal would like to be added please reach out mmlspark-support@microsoft.com

SBT Command Guide

Scala build commands

compile, test:compile and it:compile

Compiles the main, test, and integration test classes respectively

test

Runs all mmlspark tests

scalastyle

Runs scalastyle check

unidoc

Generates documentation for scala sources

Python Commands

createCondaEnv

Creates a conda environment mmlspark from environment.yaml if it does not already exist. This env is used for python testing. Activate this env before using python build commands.

cleanCondaEnv

Removes mmlspark conda env

packagePython

Compiles scala, runs python generation scripts, and creates a wheel

generatePythonDoc

Generates documentation for generated python code

installPipPackage

Installs generated python wheel into existing env

testPython

Generates and runs python tests

Environment + Publishing Commands

getDatasets

Downloads all datasets used in tests to target folder

setup

Combination of compile, test:compile, it:compile, getDatasets

package

Packages the library into a jar

publishBlob

Publishes Jar to mmlspark's azure blob based maven repo. (Requires Keys)

publishLocal

Publishes library to local maven repo

publishDocs

Publishes scala and python doc to mmlspark's build azure storage account. (Requires Keys)

publishSigned

Publishes the library to sonatype staging repo

sonatypeRelease

Promotes the published sonatype artifact

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