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lib-dask

Official

Scale Python data workflows.

Software Engineering#scalability#data processing#big data#distributed computing#parallel computing#dask
Authorbiomaps-infra
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill tackles the challenge of processing datasets that are too large to fit into your computer's memory or require parallel computation for speed. It allows you to scale your existing pandas, NumPy, and Python code beyond the limitations of a single machine.

Core Features & Use Cases

  • Larger-than-memory computation: Process datasets that exceed available RAM.
  • Parallel processing: Speed up computations by utilizing multiple CPU cores.
  • Distributed computing: Scale computations across multiple machines in a cluster.
  • Familiar APIs: Works with familiar pandas and NumPy interfaces.
  • Use Case: Analyze a multi-terabyte dataset of sensor readings by distributing the computation across a cluster of machines, performing complex aggregations and transformations that would be impossible on a single laptop.

Quick Start

Use the lib-dask skill to read a CSV file named 'large_dataset.csv' into a Dask DataFrame and compute its mean value.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: lib-dask
Download link: https://github.com/biomaps-infra/blender-opencode/archive/main.zip#lib-dask

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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