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Dask Distributed Computing

Guides Claude in scaling pandas/NumPy workloads beyond RAM using Dask DataFrames, Arrays, Bags, Futures, and schedulers.

Data & AnalyticsIntermediate★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

A reference skill that teaches Claude the right Dask patterns when data no longer fits in memory.

  • DataFrames: read many CSV/Parquet files as one table, run parallel groupby/join/aggregations
  • Arrays: chunked NumPy operations for larger-than-RAM arrays (HDF5, Zarr, XArray integration)
  • Bags: streaming cleanup of unstructured logs/JSON before converting to DataFrames
  • Futures: dynamic parallel workflows with client.submit and scatter
  • Schedulers: pick threads, processes, synchronous, or distributed per workload

It also encodes practical rules — ~100 MB chunks, never call compute() in a loop, don't load with pandas then from_pandas — plus a step-by-step debugging workflow.

Who it's for

  • Analysts hitting MemoryError on pandas pipelines
  • Data engineers batching hundreds of files
  • ML/scientific researchers moving from laptop to cluster
  • Anyone unsure which Dask collection fits their problem

Examples

  1. "Aggregate 300 files in data/2024-*.csv by category" → suggests dd.read_csv glob plus groupby().mean().compute()
  2. "My pipeline keeps running out of memory" → diagnoses chunk sizing, correct persist() usage, and task-graph reduction
  3. "Run simulations across thousands of parameter sets" → builds a parameter sweep with Client, scatter, and submit

· · · Install guide · · ·

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/dask folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/dask/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/dask ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal.
  2. Clone the skill repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Create the skills directory: mkdir -p ~/.claude/skills
  4. Copy the whole dask folder (the references/ subfolder matters): cp -r scientific-agent-skills/skills/dask ~/.claude/skills/
  5. Install Dask in your Python environment: pip install "dask[complete]" (add pip install s3fs for S3 paths).
  6. Restart Claude Code and try a prompt like "process this larger-than-RAM CSV with dask" to trigger the skill.
View source on GitHub ↗License: MIT