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CI/CD for PySpark data pipelines
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Module 3
Building a CI Pipeline with GitHub Actions
1
Dissecting GitHub Actions: Workflows, Jobs, Steps, and Triggers
Identify the core components of a GitHub Actions workflow (workflows, jobs, steps, triggers) by examining an example file.
2
Creating GitHub Actions Workflows
Write a GitHub Actions workflow YAML that triggers on push and pull request events.
Automating Python Testing with GitHub Actions
Configure a GitHub Actions job to set up Python, install dependencies, and run pytest.
Integrate Ruff Linting into CI
Add a ruff linting step to the CI workflow to enforce code quality.
5
Secure CI/CD with GitHub Actions Secrets
Use GitHub Actions secrets to securely manage credentials and environment variables in CI jobs.
Debugging GitHub Actions Workflows
Interpret GitHub Actions workflow logs to diagnose and fix failing CI steps.
Previous module
Data Quality Testing and Code Standards
Next module
Containerizing PySpark ETL Jobs