azure-ml-devops

Azure DevOps workflow for ML

Steps to run this project

• Create a Github Repo (if not created)
• Open Azure Cloud Shell
• Create ssh-keys in Azure Cloud Shell
• Upload ssh-keys to Github
• Create scaffolding for project (if not created)
  • Makefile

Should look similar to the file below

install:
	pip install --upgrade pip &&\
		pip install -r requirements.txt

test:
	python -m pytest -vv test_hello.py


lint:
	pylint --disable=R,C hello.py

all: install lint test

• requirements.txt

The requirements.txt should include:

pylint
pytest

• Create a python virtual environment and source it if not created

python3 -m venv ~/.myrepo
source ~/.myrepo/bin/activate

• Create initial hello.py and test_hello.py

hello.py

def toyou(x):
    return "hi %s" % x


def add(x):
    return x + 1


def subtract(x):
    return x - 1

test_hello.py

from hello import toyou, add, subtract


def setup_function(function):
    print("Running Setup: %s" % {function.__name__})
    function.x = 10


def teardown_function(function):
    print("Running Teardown: %s" % {function.__name__})
    del function.x


### Run to see failed test
#def test_hello_add():
#    assert add(test_hello_add.x) == 12

def test_hello_subtract():
    assert subtract(test_hello_subtract.x) == 9

• Run make all which will install, lint and test code.

• Setup Github Actions in pythonapp.yml

name: Python application test with Github Actions

on: [push]

jobs:
  build:

    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@v2
    - name: Set up Python 3.5
      uses: actions/setup-python@v1
      with:
        python-version: 3.5
    - name: Install dependencies
      run: |
        make install
    - name: Lint with pylint
      run: |
        make lint
    - name: Test with pytest
      run: |
        make test

• Commit changes and push to Github

• Verify Github Actions Test Software

• Run project in Azure Shell

• Push container to Azure Registery

• Setup Azure Pipelines

• Setup Kubernetes Cluster

• Deploy to Kubernetes