Your question is Testing and CI for Data Pipelines. Take a moment with it on the right.
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How do you implement automated testing and continuous integration for a Python-based data pipeline codebase?
Describe a practical approach covering unit, integration, data quality, and end-to-end tests. Explain how you would isolate external systems, validate transformations and schemas, run tests in CI, manage dependencies and secrets, and prevent faulty pipeline changes from reaching deployment. Include how Airflow DAG validation, fixtures, test data, coverage, linting, and failure reporting would fit together.