Dask is an open-source parallel computing library for Python, designed to scale data science workflows from a single machine to large distributed systems. It extends familiar Python libraries like NumPy, pandas, and scikit-learn for large datasets and parallel computing with minimal code changes.

Features of Dask:

• Parallel and distributed computing with minimal changes to existing Python code.
• Integrates seamlessly with NumPy, pandas, and scikit-learn.
• Supports task scheduling for optimized computation graphs.
• Real-time monitoring via a built-in dashboard.
• Works on laptops, clusters, and cloud environments.

To activate the Dask environment and check its version, run:

cd /opt
source /opt/dask-venv/bin/activate
python -c "import dask; print(dask.__version__)"

Disclaimer: Dask is an open-source project released under the BSD License. It is maintained by the Dask community and contributors. Dask is provided "as is," without any warranty or guarantees of suitability for any particular purpose.