Dask

Overview

Dask is a Python library for parallel and distributed computing that enables three critical capabilities:

• Larger-than-memory execution on single machines for data exceeding available RAM
• Parallel processing for improved computational speed across multiple cores
• Distributed computation supporting terabyte-scale datasets across multiple machines

Dask scales from laptops (processing ~100 GiB) to clusters (processing ~100 TiB) while maintaining familiar Python APIs.

When to Use This Skill

This skill should be used when:

• Process datasets that exceed available RAM
• Scale pandas or NumPy operations to larger datasets
• Parallelize computations for performance improvements
• Process multiple files efficiently (CSVs, Parquet, JSON, text logs)
• Build custom parallel workflows with task dependencies