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dask package

dask 2022.02.0+dfsg-2 source package in Ubuntu

Changelog

dask (2022.02.0+dfsg-2) unstable; urgency=medium

  * Add skip-dtype-test-on-32bit.patch (Closes: #1016719)

 -- Diane Trout <email address hidden>  Thu, 18 Aug 2022 14:23:16 -0700

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Uploaded by:
Debian Python Team
Uploaded to:
Sid
Original maintainer:
Debian Python Team
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

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Kinetic: [FULLYBUILT] amd64

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dask_2022.02.0+dfsg-2.dsc 3.0 KiB 06221e10462e8ec9a09e63892b4409ade86fd829392dc8bd5f2ee168e58bc57f
dask_2022.02.0+dfsg.orig.tar.xz 4.2 MiB 39b522dbea018d2f8fabfb6af90b96c86595197078d74a8115d82e3cba6783f9
dask_2022.02.0+dfsg-2.debian.tar.xz 25.0 KiB d9c44c27e511d80a43716cdeff867a1aa11c82cd36fe0f31c89dce87343fbbfb

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Binary packages built by this source

python-dask-doc: Minimal task scheduling abstraction documentation

 Dask is a flexible parallel computing library for analytics,
 containing two components.
 .
 1. Dynamic task scheduling optimized for computation. This is similar
 to Airflow, Luigi, Celery, or Make, but optimized for interactive
 computational workloads.
 2. "Big 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.
 .
 This contains the documentation

python3-dask: Minimal task scheduling abstraction for Python 3

 Dask is a flexible parallel computing library for analytics,
 containing two components.
 .
 1. Dynamic task scheduling optimized for computation. This is similar
 to Airflow, Luigi, Celery, or Make, but optimized for interactive
 computational workloads.
 2. "Big 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.
 .
 This contains the Python 3 version.