Top 10 Python libraries for data engineering in 2026
KDnuggets curated ten Python libraries that speed up pipeline development, reduce boilerplate, and improve maintainability.
• Performance: faster execution on large datasets
• Code clarity: less boilerplate, more readable workflows
• Maintainability: built-in testing, versioning, and monitoring
• Ecosystem fit: integrates with existing dbt, Airflow, Spark setups