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dask package

dask 2021.09.1+dfsg-1ubuntu2 source package in Ubuntu

Changelog

dask (2021.09.1+dfsg-1ubuntu2) jammy; urgency=medium

  * Enable the documentation build again
  * Drop build-dependency on python3-sparse which was
    temporarily removed due to numba

 -- Graham Inggs <email address hidden>  Sat, 04 Dec 2021 09:11:24 +0000

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Uploaded by:
Graham Inggs
Uploaded to:
Jammy
Original maintainer:
Ubuntu Developers
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

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Jammy: [FULLYBUILT] amd64

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dask_2021.09.1+dfsg.orig.tar.xz 3.1 MiB 74933a33abc48ab157453e159861b8bdb91acb6204d7e5365fff9b9a58621df6
dask_2021.09.1+dfsg-1ubuntu2.debian.tar.xz 21.2 KiB eb6746ceca0119380cd97f5756e37339c2f263310762e351c88beb2b64fa9274
dask_2021.09.1+dfsg-1ubuntu2.dsc 3.0 KiB e2fd1cc7ae75786576125dba8dd0d8fb518105fe2215b30103dc35ef6c63cb65

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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.