pipeline_3.yaml

gooddata_staging:
 stage: analytics_staging
 image: python:latest
 script:
   - cd "$CI_PROJECT_DIR/analytics"
   - pip install -r requirements.txt
 
   # Deliver into staging workspace
   # Data source properties are stored in Gitlab ENV vars
   # If admin changes them, he has to run this job manually (RUN_ALL_JOBS=true) to deliver new DS definition
   - python gooddata_register_data_source.py
   # It takes the metadata of analytics saved in folder structure and put it in the staging workspace.
   # It is good to save metadata in the folder structure because you immediately gain versioning of analytics.
   - python gooddata_load_metadata.py
   # Notify GoodData that data has been changed by ETL
   - python gooddata_upload_notification.py
   # Test that all insights are still executable
   - python gooddata_tests.py
 rules:
   - if: '$CI_MERGE_REQUEST_TARGET_BRANCH_NAME == "main"'
     changes:
       - analytics/**/*
   - if: '$RUN_ALL_JOBS == "true"'
     when: manual