_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
python-dask 2026.3.0
Propagated dependencies: python-click@8.4.1 python-cloudpickle@3.1.0 python-fsspec@2026.1.0 python-packaging@26.2 python-partd@1.4.2 python-pyyaml@6.0.3 python-toolz@1.1.0 python-lz4@4.4.4 python-numpy@2.4.6 python-pandas@3.0.3 python-pyarrow@24.0.0
Channel: guix
Location: gnu/packages/python-science.scm (gnu packages python-science)
Home page: https://www.dask.org/
Licenses: Modified BSD
Build system: pyproject
Synopsis: Parallel computing with task scheduling
Description:

Dask is a flexible parallel computing library for analytics. It consists of two components: dynamic task scheduling optimized for computation, and large data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers.

Total packages: 1