sk Skill · dralkh
dask
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.
Open on skills.sh ↗read 2026-09-17
- installs 8w
- 0
- 30-day movement
- starts with the next reading
- Related entries
- 4
- Connections
- 1
pythonbashTypeScript
- Host repository
- dralkh/iktinah
- Version
- 1.1
- Allowed tools
- Read Write Edit Bash
- Compatible with
- 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]).
- Licence
- BSD-3-Clause license
- Host stars
- 78
- Host language
- TypeScript