Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill dasknpx skills add K-Dense-AI/scientific-agent-skills --skill dask -a claude-code -gnpx skills add K-Dense-AI/scientific-agent-skills --skill dask -a codex -ggemini skills install https://github.com/K-Dense-AI/scientific-agent-skills.git --path scientific-skills/daskgh skill install K-Dense-AI/scientific-agent-skills daskgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills /tmp/K-Dense-AI__scientific-agent-skills
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/K-Dense-AI__scientific-agent-skills/scientific-skills/dask ~/.claude/skills/dask # Claude Code
cp -R /tmp/K-Dense-AI__scientific-agent-skills/scientific-skills/dask ~/.agents/skills/dask # Codex, Cursor, Gemini CLI, Copilot, OpenCode