Ubuntu
dask package

dask 2.6.0+dfsg-0ubuntu2 source package in Ubuntu

Changelog

dask (2.6.0+dfsg-0ubuntu2) focal; urgency=medium

  * Add python3-fsspec to the autopkg test dependencies.

 -- Matthias Klose <email address hidden>  Mon, 11 Nov 2019 19:52:25 +0100

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Uploaded by:
Matthias Klose
Uploaded to:
Focal
Original maintainer:
Debian Python Modules Team
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

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Series Pocket Published Component Section

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Focal: [FULLYBUILT] amd64

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File Size SHA-256 Checksum
dask_2.6.0+dfsg.orig.tar.xz 2.0 MiB 28f3872eef98d545ea10b680337ba91bf6ae8e8a4b28b3c0a8a7e84a54c49736
dask_2.6.0+dfsg-0ubuntu2.debian.tar.xz 6.5 KiB 8bdd726d3c0b337d36437ecff501cef86cc1638afd53b6e46550ddf73310b08f
dask_2.6.0+dfsg-0ubuntu2.dsc 2.8 KiB 464a9ceca80df19b862adef93b618be5f2a64db5551259f32633642c1e70a768

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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.