Merge pull request #1 from shah-zeb-naveed/test_feature_branch

feat: push dummy change

.github/workflows/auto_tests.yml

@@ -0,0 +1,31 @@
+name: Automaticalyl test linting and unit tests
+
+on:
+  pull_request:
+    branches:
+      - main
+
+permissions:
+  id-token: write
+  contents: read
+
+jobs:
+  checks:
+    runs-on: ubuntu-latest
+    environment: dev
+    steps:
+    - name: Check out repo
+      uses: actions/checkout@main
+    - name: Use Python version 3.8
+      uses: actions/setup-python@v3
+      with:
+        python-version: '3.8'
+    # - name: Install Flake8
+    #   run: |
+    #     python -m pip install flake8
+    # - name: Run linting tests
+    #   run: | 
+    #     flake8 src/model/ 
+    - name: Run unittests
+      run: | 
+        pip install -r requirements.txt && pytest tests/

.github/workflows/prod_and_dev_jobs.yml

@@ -0,0 +1,47 @@
+name: Manually trigger an Azure Machine Learning job
+
+on: [push]
+
+permissions:
+  id-token: write
+  contents: read
+
+jobs:
+  devtrain:
+    runs-on: ubuntu-latest
+    environment: dev
+    steps:
+    - name: Check out repo
+      uses: actions/checkout@main
+    - name: Install az ml extension
+      run: az extension add -n ml -y
+    - name: Azure login
+      uses: azure/login@v1
+      with:
+        client-id: ${{ secrets.AZURE_CLIENT_ID }}
+        tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+        subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+    - name: Set defaults
+      run: az configure --defaults group=testshahzeb && az configure --defaults workspace=mlshah
+    - name: Run command
+      run: az ml job create --file src/job.yml --stream
+  prodtrain:
+    needs: devtrain
+    runs-on: ubuntu-latest
+    environment: prod
+    steps:
+    - name: Check out repo
+      uses: actions/checkout@main
+    - name: Install az ml extension
+      run: az extension add -n ml -y
+    - name: Azure login
+      uses: azure/login@v1
+      with:
+        client-id: ${{ secrets.AZURE_CLIENT_ID }}
+        tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+        subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+    - name: Set defaults
+      run: az configure --defaults group=testshahzeb && az configure --defaults workspace=mlshah
+    - name: Run command
+      run: az ml job create --file src/prod_job.yml --stream
+

.github/workflows/test_login.yml

@@ -1,5 +1,6 @@
 name: Run Azure Login with OpenID Connect and PowerShell
-on: [push]
+on: workflow_dispatch:
+#[push]
 
 permissions:
   id-token: write

requirements.txt

@@ -3,3 +3,4 @@ mlflow==1.27.0
 pandas==1.4.3
 sklearn==0.0
 scikit-learn==1.1.1
+matplotlib

src/prod_job.yml

@@ -0,0 +1,22 @@
+$schema: https://azuremlschemas.azureedge.net/latest/commandJob.schema.json
+code: model
+command: |
+  echo "Hello, world!"
+  ls -la
+  python train.py --training_data ${{inputs.training_data}} --reg_rate ${{inputs.reg_rate}}
+inputs:
+  training_data: 
+    type: uri_folder 
+    path: azureml:diabetes-prod-folder:1
+  reg_rate: 0.01
+environment: azureml:AzureML-sklearn-0.24-ubuntu18.04-py37-cpu@latest
+compute: azureml:shahcluster # maybe local needs docker
+experiment_name: DummyExperiment 
+description: |
+  # Azure Machine Learning "hello world" job
+
+  This is a "hello world" job running in the cloud via Azure Machine Learning!
+
+  ## Description
+
+  Markdown is supported in the studio for job descriptions! You can edit the description there or via CLI.