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dask package

dask 2022.12.1+dfsg-1 source package in Ubuntu

Changelog

dask (2022.12.1+dfsg-1) unstable; urgency=medium

  [ Andreas Tille ]
  * Team upload.
  * New upstream version
    Closes: #1025393, #1027254
  * Simplify watch file
  * Standards-Version: 4.6.2 (routine-update)
  * Add salsa-ci file (routine-update)
  * Set upstream metadata fields: Bug-Database, Bug-Submit, Repository-Browse.
  * Ignore some sphinx packages that are not packaged yet
  * yaml.min.js should be properly excluded from upstream source.  Just
    in case it is needed it can be taken from debian/missing-sources.

  [ Rebecca N. Palmer ]
  * Docs: continue to use our js-yaml.
  * Temporarily remove python3-distributed B-D to break cycle.
    Closes: #1028667
  * Docs: ignore build errors.
  * Tests: be compatible with our CI setup.
  * Remove newline from error message, to not break python3-intake.

 -- Andreas Tille <email address hidden>  Mon, 16 Jan 2023 10:22:16 +0100

Upload details

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

See full publishing history Publishing

Series Pocket Published Component Section

Builds

Lunar: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
dask_2022.12.1+dfsg-1.dsc 2.9 KiB e474074e3a70579aed837f71dd0fc99bdd2b268cf18299a42f1f49c1081fc051
dask_2022.12.1+dfsg.orig.tar.xz 7.2 MiB bc9331d6f47f37f21b3025baccbaa7f1a1b85dafc47d024e41bb3a44c3a41fd0
dask_2022.12.1+dfsg-1.debian.tar.xz 45.8 KiB fe39feec3da12e624878d42e65d1393ab8c0678605c60f932b6947358101f188

No changes file available.

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.