dask 2022.01.0+dfsg-1 source package in Ubuntu
Changelog
dask (2022.01.0+dfsg-1) unstable; urgency=medium
* New upstream release
* Refresh patches
* split tests/control Tests-Command: into a separate shell script
* Add sphinx-remove-toctree and sphinx-tabs to build-depends
* add 32-bit compatibility patch for pandas 1.3
See https://github.com/dask/dask/issues/8169
* Copy conftest.py into test directory for autopkgtests
* Add python3-ipython as a build-dependency.
- it provides a sphinx formatting extension.
* Add patch pytest-futurewarning.patch for compatibility with our pytest
* Disable python3-sparse for tests since numba is broken (Closes: #1005962)
-- Diane Trout <email address hidden> Sun, 20 Feb 2022 17:11:53 -0800
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 | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| dask_2022.01.0+dfsg-1.dsc | 3.0 KiB | 2fd7db2e7e1d74b6b086d6f8199e58cec107cf8057e8c8531f02a66304c954a6 |
| dask_2022.01.0+dfsg.orig.tar.xz | 4.1 MiB | 77f81416b9e618cb33bd038679fec36371bf7c5796c9234d7de1f605ffe56bd9 |
| dask_2022.01.0+dfsg-1.debian.tar.xz | 22.7 KiB | 592aa9a388583925a637b999fd6892ea1fe46f9d0f263c19642e7310846dd530 |
Available diffs
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.
