dask
Distributed computing for larger-than-RAM pandas/NumPy workflows.
Skill by Zejie0920
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: data, ml
Reviews
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What's inside
- Skill name
dask- Description
- 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.
- License
- BSD-3-Clause license
- Compatibility
- Requires Python 3.10+ and dask 2025.1+. DataFrame workflows need pandas 2+ and PyArrow 16+. Cloud paths (s3://, gcs://) need s3fs or gcsfs. Cluster deployment uses dask.distributed (included with dask[complete]).
- Allowed tools
- Read, Write, Edit, Bash
- Metadata
- version: 1.1 · skill-author: K-Dense Inc.
- Instructions
- 473 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves any shell command
Files (7)
- SKILL.md
- arrays.md · references/
- bags.md · references/
- best-practices.md · references/
- dataframes.md · references/
- futures.md · references/
- schedulers.md · references/
The license isn't open source, so the instructions aren't shown here. Read SKILL.md on GitHub
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 8, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.1
- License
- BSD-3-Clause license
- Repository
- github.com/Zejie0920/mather-workflow
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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dask skill. Agent Mart. https://agentmart.dev/skills/zejie0920-dask (last updated 2026-10-24)