dask 2023.8.0+dfsg-1 source package in Ubuntu
Changelog
dask (2023.8.0+dfsg-1) unstable; urgency=medium
* New upstream release.
* Remove reproducible-version.patch, use-debian-version.patch
Upstream removed the embedded copy of versioneer.
* Add python3-versioneer dependency.
* Refresh patches.
* Add python3-sphinx-design dependency for better documentation
* Add pybuild-plugin-pyproject build dependency for pyproject.toml
* Change disable autopkgtests
- test_describe_empty seems to work now.
- test_RandomState_only_funcs fails for not throwing a
deprecationwarning
* Add python3-importlib-metadata Build-Depends for sphinx autosummary
* Disable patches that may not be needed
- skip-dtype-test-on-32bit.patch
- no_newline_error.patch
* add tzdata-legacy to control and test/control for some timezone tests
* Add verbatim-sphinx-ipython.patch to avoid updating ipython output
during the build process. This should improve reproducibility.
-- Diane Trout <email address hidden> Thu, 10 Aug 2023 16:02:14 -0700
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_2023.8.0+dfsg-1.dsc | 3.0 KiB | f99c47e061525c22ae0085dbf54727cc879f19ceb6f29fe4db1f9ad295155afc |
| dask_2023.8.0+dfsg.orig.tar.xz | 7.4 MiB | d3051ddea3ea189f125227b8b302883b11ef32196c2f3d1ac36446d63be723fa |
| dask_2023.8.0+dfsg-1.debian.tar.xz | 45.5 KiB | 909980147b74791aa6fb63b5a9af043e44c89f731a4fc9e020584475aad7dbbc |
Available diffs
- diff from 2022.12.1+dfsg-2 to 2023.8.0+dfsg-1 (311.4 KiB)
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.
