Adding private Azure DevOps Artifact feeds to Azure Machine Learning

private_repo.md

Steps:

• Create private Feed in Azure DevOps
• Create Personal Access Token (PAT) in Azure DevOps with Feed Read permission (details)
• Navigate to the Azure DevOps Artifacts Feed page where you can see the details for the next steps (you'll need feed name, project name, organization name and later also package name):
• Create Build pipeline in Azure DevOps to create package and push to private feed:

trigger:
- master

pool:
  vmImage: 'ubuntu-latest'

steps:
- task: UsePythonVersion@0
  inputs:
    versionSpec: '3.8'
    
- script: 'python setup.py sdist'

- script: 'pip install twine'

- task: TwineAuthenticate@1
  inputs:
    artifactFeed: '<PROJECT NAME>/<FEED NAME>'
    
- script: 'twine upload -r <FEED NAME> --config-file $(PYPIRC_PATH) dist/*'

• Register PAT in the workspace:

from azureml.core import Workspace

ws = Workspace.from_config()
pat_token = input("Enter secret token")
ws.set_connection(name="token-name", 
   category = "PythonFeed",
   target = "https://<ORGANIZATION NAME>.pkgs.visualstudio.com", 
   authType = "PAT", 
   value = pat_token)

• Create enviroment:

from azureml.core import Environment
from azureml.core.conda_dependencies import CondaDependencies

env = Environment(name="my-env")
cd = CondaDependencies()
cd.add_pip_package("<PACKAGE NAME>")
cd.set_pip_option("--extra-index-url https://<ORGANIZATION NAME>.pkgs.visualstudio.com/<PROJECT NAME>/_packaging/<FEED NAME>/pypi/simple")
env.python.conda_dependencies=cd

• When working from CLI/with Conda environment YAML files, the use:

name: project_environment
dependencies:
- python=3.6.2
- pip:
  - azureml-defaults
  - <PACKAGE NAME>
  - --extra-index-url https://<ORGANIZATION NAME>.pkgs.visualstudio.com/<PROJECT NAME>/_packaging/<FEED NAME>/pypi/simple
channels:
- anaconda
- conda-forge

@csiebler Why have you used visualstudio.com, want to confirm if the url is still valid with the name being Azure dev ops now ? Also, could you share how to import the package inside the azureml notebook or python file.