Install the Kubeflow Pipelines SDK

Setting up your Kubeflow Pipelines development environment

This guide tells you how to install theKubeflow Pipelines SDKwhich you can use to build machine learning pipelines. You can use the SDKto execute your pipeline, or alternatively you can upload the pipeline tothe Kubeflow Pipelines UI for execution.

All of the SDK’s classes and methods are described in the auto-generated SDK reference docs.

Set up Python

You need Python 3.5 or later to use the Kubeflow Pipelines SDK. Thisguide uses Python 3.7.

If you haven’t yet set up a Python 3 environment, do so now. This guiderecommends Miniconda, but you can usea virtual environment manager of your choice, such as virtualenv.

Follow the steps below to setup Python using Miniconda:

  • Choose one of the following methods to install Miniconda, depending on yourenvironment:

  1. apt-get update; apt-get install -y wget bzip2
  2. wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
  3. bash Miniconda3-latest-Linux-x86_64.sh

  • Windows: Download theinstallerand make sure you select the option toAdd Miniconda to my PATH environment variable during the installation.

  • MacOS: Download theinstallerand run the following command:

  1. bash Miniconda3-latest-MacOSX-x86_64.sh
  • Check that the conda command is available:
  1. which conda

If the conda command is not found, add Miniconda to your path:

  1. export PATH=<YOUR_MINICONDA_PATH>/bin:$PATH
  • Create a clean Python 3 environment with a name of your choosing. Thisexample uses Python 3.7 and an environment name of mlpipeline.:
  1. conda create --name mlpipeline python=3.7
  2. conda activate mlpipeline

Install the Kubeflow Pipelines SDK

Run the following command to install the Kubeflow Pipelines SDK:

  1. pip install https://storage.googleapis.com/ml-pipeline/release/latest/kfp.tar.gz --upgrade

After successful installation, the command dsl-compile should be available.You can use this command to verify it:

  1. which dsl-compile

The response should be something like this:

  1. /<PATH_TO_YOUR_USER_BIN>/miniconda3/envs/mlpipeline/bin/dsl-compile

Next steps