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python3-Bottleneck-1.3.2-lp152.2.1 RPM for armv7hl

From OpenSuSE Ports Leap 15.2 for armv7hl

Name: python3-Bottleneck Distribution: openSUSE Leap 15.2
Version: 1.3.2 Vendor: openSUSE
Release: lp152.2.1 Build date: Tue Mar 31 07:34:23 2020
Group: Unspecified Build host: obs-arm-6
Size: 526067 Source RPM: python-Bottleneck-1.3.2-lp152.2.1.src.rpm
Packager: https://bugs.opensuse.org
Url: http://berkeleyanalytics.com/bottleneck/
Summary: A collection of fast NumPy array functions
Bottleneck is a collection of fast NumPy array functions written in C.

Provides

Requires

License

BSD-2-Clause AND BSD-3-Clause

Changelog

* Mon Mar 30 2020 John Vandenberg <jayvdb@gmail.com>
  - Require numpy 1.16.0, removing Python 2 support which provides
    a lower version
  - Activate test suite
* Sat Mar 14 2020 Arun Persaud <arun@gmx.de>
  - specfile:
    * update copyright year
  - update to version 1.3.2:
    * Bug Fixes
      + Explicitly declare numpy version dependency in pyproject.toml
      for Python 3.8, fixing certain cases where pip install would
      fail. Thanks to @goggle, @astrofrog, and @0xb0b for
      reporting. (:issue:`277`)
* Fri Nov 22 2019 Arun Persaud <arun@gmx.de>
  - specfile:
    * update copyright year
  - update to version 1.3.1:
    * Bug Fixes
      + Fix memory leak in :func:`bottleneck.nanmedian` with the default
      argument of axis=None. Thanks to @jsmodic for reporting!
      (:issue:`276`, :issue:`278`)
      + Add regression test for memory leak case (:issue:`279`)
  - changes from version 1.3.0:
    * Project Updates
      + Bottleneck has a new maintainer, Christopher Whelan (@qwhelan on
      GitHub).
      + Documentation now hosted at https://bottleneck.readthedocs.io
      + 1.3.x will be the last release to support Python 2.7
      + Bottleneck now supports and is tested against Python 3.7 and
      3.8. (:issue:`211`, :issue:`268`)
      + The LICENSE file has been restructured to only include the
      license for the Bottleneck project to aid license audit
      tools. There has been no change to the licensing of Bottleneck.
      + Licenses for other projects incorporated by Bottleneck are now
      reproduced in full in separate files in the LICENSES/ directory
      (eg, LICENSES/NUMPY_LICENSE)
      + All licenses have been updated. Notably, setuptools is now MIT
      licensed and no longer under the ambiguous dual PSF/Zope
      license.
      + Bottleneck now uses PEP 518 for specifying build dependencies,
      with per Python version specifications (:issue:`247`)
    * Enhancements
      + Remove numpydoc package from Bottleneck source distribution
      + :func:`bottleneck.slow.reduce.nansum` and
      :func:`bottleneck.slow.reduce.ss` now longer coerce output to
      have the same dtype as input
      + Test (tox, travis, appveyor) against latest numpy (in conda)
      + Performance benchmarking also available via asv
      + versioneer now used for versioning (:issue:`213`)
      + Test suite now uses pytest as nose is deprecated (:issue:`222`)
      + python setup.py build_ext --inplace is now incremental
      (:issue:`224`)
      + python setup.py clean now cleans all artifacts (:issue:`226`)
      + Compiler feature support now identified by testing rather than
      hardcoding (:issue:`227`)
      + The BN_OPT_3 macro allows selective use of -O3 at the function
      level (:issue:`223`)
      + Contributors are now automatically cited in the release notes
      (:issue:`244`)
    * Performance
      + Speed up :func:`bottleneck.reduce.anynan` and
      :func:`bottleneck.reduce.allnan` by 2x via BN_OPT_3
      (:issue:`223`)
      + All functions covered by asv benchmarks
      + :func:`bottleneck.nonreduce.replace` speedup of 4x via more
      explicit typing (:issue:`239`)
      + :func:`bottleneck.reduce.median` up to 2x faster for
      Fortran-ordered arrays (:issue:`248`)
    * Bug Fixes
      + Documentation fails to build on Python 3 (:issue:`170`)
      + :func:`bottleneck.benchmark.bench` crashes on python 3.6.3,
      numpy 1.13.3 (:issue:`175`)
      + :func:`bottleneck.nonreduce_axis.push` raises when n=None is
      explicitly passed (:issue:`178`)
      + :func:`bottleneck.reduce.nansum` wrong output when a =
      np.ones((2, 2))[..., np.newaxis] same issue of other reduce
      functions (:issue:`183`)
      + Silenced FutureWarning from NumPy in the slow version of move
      functions (:issue:`194`)
      + Installing bottleneck onto a system that does not already have
      Numpy (:issue:`195`)
      + Memory leaked when input was not a NumPy array (:issue:`201`)
      + Tautological comparison in :func:`bottleneck.move.move_rank`
      removed (:issue:`207`, :issue:`212`)
    * Cleanup
      + The ez_setup.py module is no longer packaged (:issue:`211`)
      + Building documentation is now self-contained in make doc
      (:issue:`214`)
      + Codebase now flake8 compliant and run on every commit
      + Codebase now uses black for autoformatting (:issue:`253`)
* Wed Sep 27 2017 arun@gmx.de
  - update to version 1.2.1:
    * #156 Installing bottleneck when two versions of NumPy are present
    * #157 Compiling on Ubuntu 14.04 inside a Windows 7 WMware
    * #159 Occasional segmentation fault in nanargmin, nanargmax,
      median, and nanmedian when all of the following conditions are
      met: axis is None, input array is 2d or greater, and input array
      is not C contiguous.
    * #163 Reducing np.array([2**31], dtype=np.int64) overflows on
      Windows
* Wed Apr 19 2017 toddrme2178@gmail.com
  - Implement single-spec version.
* Mon Nov 14 2016 dmueller@suse.com
  - update to 1.2.0:
    This release is a complete rewrite of Bottleneck.
    - Bottleneck is now written in C
    - Cython is no longer a dependency
    - Source tarball size reduced by 80%
    - Build time reduced by 66%
    - Install size reduced by 45%
* Mon Apr 27 2015 benoit.monin@gmx.fr
  - update to version 1.0.0:
    * "python setup.py build" is 18.7 times faster
    * Function-call overhead cut in half---a big speed up for small
      input arrays
    * Arbitrary ndim input arrays accelerated; previously only 1d,
      2d, and 3d
    * bn.nanrankdata is twice as fast for float input arrays
    * bn.move_max, bn.move_min are faster for int input arrays
    * No speed penalty for reducing along all axes when input is
      Fortran ordered
    * Compiled binaries 14.1 times smaller
    * Source tarball 4.7 times smaller
    * 9.8 times less C code
    * 4.3 times less Cython code
    * 3.7 times less Python code
    * Requires numpy 1.9.1
    * Single API, e.g.: bn.nansum instead of bn.nansum and
      nansum_2d_float64_axis0
    * On 64-bit systems bn.nansum(int32) returns int32 instead of
      int64
    * bn.nansum now returns 0 for all NaN slices (as does numpy
      1.9.1)
    * Reducing over all axes returns, e.g., 6.0; previously
      np.float64(6.0)
    * bn.ss() now has default axis=None instead of axis=0
    * bn.nn() is no longer in bottleneck
    * Previous releases had moving window function pairs: move_sum,
      move_nansum
    * This release only has half of the pairs: move_sum
    * Instead a new input parameter, min_count, has been added
    * min_count=None same as old move_sum; min_count=1 same as old
      move_nansum
    * If # non-NaN values in window < min_count, then NaN assigned
      to the window
    * Exception: move_median does not take min_count as input
    * Can now install bottleneck with pip even if numpy is not
      already installed
    * bn.move_max, bn.move_min now return float32 for float32 input
  - increase required numpy version to 1.9.1
* Thu May 08 2014 toddrme2178@gmail.com
  - Update to version 0.8.0
    - This version of Bottleneck requires NumPy 1.8
    - nanargmin and nanargmax behave like the corresponding functions in NumPy 1.8
    - nanargmax/nanargmin wrong for redundant max/min values in 1d int arrays
* Tue Oct 22 2013 toddrme2178@gmail.com
  - Update to version 0.7.0
    + bn.rankdata() is twice as fast (with input a = np.random.rand(1000000))
    + C files now included in github repo; cython not needed to try latest
    + C files are now generated with Cython 0.19.1 instead of 0.16
    + Test bottleneck across multiple python/numpy versions using tox
    + Source tarball size cut in half
* Fri Jun 22 2012 saschpe@suse.de
  - %py_requires is only needed for SLE_11_SP2 (and older), newer Python
    package releases generate the RPM requires for the Python ABI automatically

Files

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/usr/lib/python3.6/site-packages/Bottleneck-1.3.2-py3.6.egg-info/top_level.txt
/usr/lib/python3.6/site-packages/bottleneck
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/usr/lib/python3.6/site-packages/bottleneck/tests/util.py
/usr/share/doc/packages/python3-Bottleneck
/usr/share/doc/packages/python3-Bottleneck/README.rst
/usr/share/doc/packages/python3-Bottleneck/RELEASE.rst
/usr/share/licenses/python3-Bottleneck
/usr/share/licenses/python3-Bottleneck/LICENSE


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