alterlab-dask

alterlab-dask is a Data pipelines & ETL skill for AI agents, published by AlterLab-IEU in the AlterLab-Academic-Skills repository on GitHub. Skillspace rates alterlab-dask C (77/100) and it passed the safety scan; the rating is based on static analysis only.

Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution. Use when existing pandas/NumPy code must run on larger-than-RAM data or across clusters, for parallel file processing, distributed ML, or integration with existing pandas code. For out-of-core analytics on a single machine prefer vaex; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.

Grade
C
Quality
77 / 100
Safety
Passed
GitHub stars
43

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubAlterLab-IEU/AlterLab-Academic-Skills

Our review

Architecture
100 / 100
Maturity
Packaged: licensed, with a version or references
Security scan
Low-risk patterns
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

What the scanner flagged

  • over-broad allowed-tools ('*')

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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