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python3-numexpr-2.7.1-lp152.1.4 RPM for ppc64le

From OpenSuSE Ports Leap 15.2 for ppc64le

Name: python3-numexpr Distribution: openSUSE:Leap:15.2:PowerPC / ports
Version: 2.7.1 Vendor: openSUSE
Release: lp152.1.4 Build date: Sat May 16 12:09:34 2020
Group: Development/Languages/Python Build host: obs-power8-03
Size: 749646 Source RPM: python-numexpr-2.7.1-lp152.1.4.src.rpm
Packager: https://bugs.opensuse.org
Url: https://github.com/pydata/numexpr/
Summary: Numerical expression evaluator for NumPy
Numexpr is a numerical expression evaluator for NumPy. It is a C++
module. With it, expressions that operate on arrays (like "3*a+4*b")
can be accelerated and use less memory than doing the same
calculation in Python.

Provides

Requires

License

MIT

Changelog

* Wed Jan 08 2020 Todd R <toddrme2178@gmail.com>
  - Update to 2.7.1
    * Python 3.8 support has been added.
    * Python 3.4 support is discontinued.
    * The tests are now compatible with NumPy 1.18.
    * site.cfg.example was updated to use the libraries tag instead
      of mkl_libs, which is recommended for newer version of NumPy.
  - Drop upstream-included fix_test.patch
* Sat Aug 31 2019 Arun Persaud <arun@gmx.de>
  - specfile:
    * update copyright year
    * added fix to call python in tests: fix_test.patch
  - update to version 2.7.0:
    * The default number of 'safe' threads has been restored to the
      historical limit of 8, if the environment variable
      "NUMEXPR_MAX_THREADS" has not been set.
    * Thanks to @eltoder who fixed a small memory leak.
    * Support for Python 2.6 has been dropped, as it is no longer
      available via TravisCI.
    * A typo in the test suite that had a less than rather than greater
      than symbol in the NumPy version check has been corrected thanks
      to dhomeier.
    * The file site.cfg was being accidently included in the sdists on
      PyPi. It has now been excluded.
* Sat Dec 22 2018 Todd R <toddrme2178@gmail.com>
  - Update to 2.6.9
    * Thanks to Mike Toews for more robust handling of the thread-setting environment variables.
    * With Appveyor updating to Python 3.7.1, wheels for Python 3.7 are now available in addition to those for other OSes.
* Sun Sep 02 2018 arun@gmx.de
  - update to version 2.6.8:
    * Add check to make sure that f_locals is not actually f_globals
      when we do the f_locals clear to avoid the #310 memory leak issue.
    * Compare NumPy versions using distutils.version.LooseVersion to
      avoid issue #312 when working with NumPy development versions.
    * As part of multibuild, wheels for Python 3.7 for Linux and MacOSX
      are now available on PyPI.
  - changes from version 2.6.7:
    * Thanks to Lehman Garrison for finding and fixing a bug that
      exhibited memory leak-like behavior. The use in numexpr.evaluate
      of sys._getframe combined with .f_locals from that frame object
      results an extra refcount on objects in the frame that calls
      numexpr.evaluate, and not evaluate's frame. So if the calling
      frame remains in scope for a long time (such as a procedural
      script where numexpr is called from the base frame) garbage
      collection would never occur.
    * Imports for the numexpr.test submodule were made lazy in the
      numexpr module.
* Mon Aug 06 2018 toddrme2178@gmail.com
  - Update to 2.6.6
    * Thanks to Mark Dickinson for a fix to the thread barrier that occassionally suffered from spurious wakeups on MacOSX.
  - Update to 2.6.5
    * The maximum thread count can now be set at import-time by setting the environment variable ‘NUMEXPR_MAX_THREADS’. The default number of max threads was lowered from 4096 (which was deemed excessive) to 64.
    * A number of imports were removed (pkg_resources) or made lazy (cpuinfo) in order to speed load-times for downstream packages (such as pandas, sympy, and tables). Import time has dropped from about 330 ms to 90 ms. Thanks to Jason Sachs for pointing out the source of the slow-down.
    * Thanks to Alvaro Lopez Ortega for updates to benchmarks to be compatible with Python 3.
    * Travis and AppVeyor now fail if the test module fails or errors.
    * Thanks to Mahdi Ben Jelloul for a patch that removed a bug where constants in where calls would raise a ValueError.
    * Fixed a bug whereby all-constant power operations would lead to infinite recursion.
* Mon Oct 02 2017 jengelh@inai.de
  - Ensure neutrality of description.
* Sun Sep 24 2017 arun@gmx.de
  - update to version 2.6.4:
    * Christoph Gohkle noticed a lack of coverage for the 2.6.3 floor
      and ceil functions for MKL that caused seg-faults in
  - changes from version 2.6.2:
    * Documentation now available at readthedocs.io.
    * Support for floor() and ceil() functions added by Caleb P. Burns.
    * NumPy requirement increased from 1.6 to 1.7 due to changes in
      iterator flags (#245).
    * Sphinx autodocs support added for documentation on
      readthedocs.org.
    * Fixed a bug where complex constants would return an error, fixing
      problems with sympy when using NumExpr as a backend.
    * Fix for #277 whereby arrays of shape (1,...) would be reduced as
      if they were full reduction. Behavoir now matches that of NumPy.
    * String literals are automatically encoded into 'ascii' bytes for
      convience (see #281).
* Wed Apr 19 2017 toddrme2178@gmail.com
  - Source url must be https.
* Wed Apr 19 2017 toddrme2178@gmail.com
  - Update to 2.6.2
    * Updates to keep with API changes in newer NumPy versions (#228).
      Thanks to Oleksandr Pavlyk.
    * Removed several warnings (#226 and #227).  Thanks to Oleksander Pavlyk.
    * Fix bugs in function `stringcontains()` (#230).  Thanks to Alexander Shadchin.
    * Detection of the POWER processor (#232).  Thanks to Breno Leitao.
    * Fix pow result casting (#235).  Thanks to Fernando Seiti Furusato.
    * Fix integers to negative integer powers (#240).  Thanks to Antonio Valentino.
    * Detect numpy exceptions in expression evaluation (#240).  Thanks to Antonio Valentino.
    * Better handling of RC versions (#243).  Thanks to Antonio Valentino.
  - Update to 2.6.1
    * Fixed a performance regression in some situations as consequence of
      increasing too much the BLOCK_SIZE1 constant.  After more careful
      benchmarks (both in VML and non-VML modes), the value has been set
      again to 1024 (down from 8192).  The benchmarks have been made with
      a relatively new processor (Intel Xeon E3-1245 v5 @ 3.50GHz), so
      they should work well for a good range of processors again.
    * Added NetBSD support to CPU detection.  Thanks to Thomas Klausner.
  - Update to 2.6.0
    * Introduced a new re_evaluate() function for re-evaluating the
      previous executed array expression without any check.  This is meant
      for accelerating loops that are re-evaluating the same expression
      repeatedly without changing anything else than the operands.  If
      unsure, use evaluate() which is safer.
    * The BLOCK_SIZE1 and BLOCK_SIZE2 constants have been re-checked in
      order to find a value maximizing most of the benchmarks in bench/
      directory.  The new values (8192 and 16 respectively) give somewhat
      better results (~5%) overall.  The CPU used for fine tuning is a
      relatively new Haswell processor (E3-1240 v3).
    * The '--name' flag for `setup.py` returning the name of the package
      is honored now (issue #215).
  - Update to 2.5.2
    * conj() and abs() actually added as VML-powered functions, preventing
      the same problems than log10() before (PR #212).  Thanks to Tom Kooij
      for the fix!
  - Update to 2.5.1
    * Fix for log10() and conj() functions.  These produced wrong results
      when numexpr was compiled with Intel's MKL (which is a popular build
      since Anaconda ships it by default) and non-contiguous data (issue
      [#210]).  Thanks to Arne de Laat and Tom Kooij for reporting and
      providing a nice test unit.
    * Fix that allows numexpr-powered apps to be profiled with pympler.
      Thanks to @nbecker.
  - Update to 2.5
    * Added locking for allowing the use of numexpr in multi-threaded
      callers (this does not prevent numexpr to use multiple cores
      simultaneously).  (PR #199, Antoine Pitrou, PR #200, Jenn Olsen).
    * Added new min() and max() functions (PR #195, CJ Carey).
  - Implement single-spec version
* Mon Feb 01 2016 toddrme2178@gmail.com
  - update to version 2.4.6:
    * Fixed some UserWarnings in Solaris (PR #189, Graham Jones).
    * Better handling of MSVC defines. (#168, Francesc Alted).
  - update to version 2.4.5:
    * Undone a 'fix' for a harmless data race. (#185 Benedikt Reinartz,
      Francesc Alted).
    * Ignore NumPy warnings (overflow/underflow, divide by zero and
      others) that only show up in Python3. Masking these warnings in
      tests is fine because all the results are checked to be
      valid. (#183, Francesc Alted).
  - update to version 2.4.4:
    * Honor OMP_NUM_THREADS as a fallback in case NUMEXPR_NUM_THREADS is
      not set. Fixes #161. (PR #175, Stefan Erb).
    * Added support for AppVeyor (PR #178 Andrea Bedini)
    * Fix to allow numexpr to be imported after eventlet.monkey_patch(),
      as suggested in #118 (PR #180 Ben Moran).
    * Fix harmless data race that triggers false positives in
      ThreadSanitizer. (PR #179, Clement Courbet).
    * Fixed some string tests on Python 3 (PR #182, Antonio Valentino).
* Thu May 07 2015 benoit.monin@gmx.fr
  - update to version 2.4.3:
    * Comparisons with empty strings work correctly now. Fixes #121
      and PyTables #184.
  - additional changes from version 2.4.2:
    * Improved setup.py so that pip can query the name and version
      without actually doing the installation. Thanks to Joris
      Borgdorff.
  - additional changes from version 2.4.1:
    * Added more configuration examples for compiling with MKL/VML
      support. Thanks to Davide Del Vento.
    * Symbol MKL_VML changed into MKL_DOMAIN_VML because the former
      is deprecated in newer MKL. Thanks to Nick Papior Andersen.
    * Better determination of methods in cpuinfo module. Thanks to
      Marc Jofre.
    * Improved NumPy version determination (handy for 1.10.0). Thanks
      to Åsmund Hjulstad.
    * Benchmarks run now with both Python 2 and Python 3. Thanks to
      Zoran Plesivčak.
  - remove shebang of cpuinfo.py instead of setting it executable
  - remove unneeded clean section

Files

/usr/lib64/python3.6/site-packages/numexpr
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info/PKG-INFO
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info/SOURCES.txt
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info/dependency_links.txt
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info/not-zip-safe
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info/requires.txt
/usr/lib64/python3.6/site-packages/numexpr-2.7.1-py3.6.egg-info/top_level.txt
/usr/lib64/python3.6/site-packages/numexpr/__config__.py
/usr/lib64/python3.6/site-packages/numexpr/__init__.py
/usr/lib64/python3.6/site-packages/numexpr/__pycache__
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/__config__.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/__config__.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/__init__.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/__init__.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/cpuinfo.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/cpuinfo.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/expressions.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/expressions.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/necompiler.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/necompiler.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/utils.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/utils.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/version.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/__pycache__/version.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/cpuinfo.py
/usr/lib64/python3.6/site-packages/numexpr/expressions.py
/usr/lib64/python3.6/site-packages/numexpr/interpreter.cpython-36m-powerpc64le-linux-gnu.so
/usr/lib64/python3.6/site-packages/numexpr/necompiler.py
/usr/lib64/python3.6/site-packages/numexpr/tests
/usr/lib64/python3.6/site-packages/numexpr/tests/__init__.py
/usr/lib64/python3.6/site-packages/numexpr/tests/__pycache__
/usr/lib64/python3.6/site-packages/numexpr/tests/__pycache__/__init__.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/tests/__pycache__/__init__.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/tests/__pycache__/test_numexpr.cpython-36.opt-1.pyc
/usr/lib64/python3.6/site-packages/numexpr/tests/__pycache__/test_numexpr.cpython-36.pyc
/usr/lib64/python3.6/site-packages/numexpr/tests/test_numexpr.py
/usr/lib64/python3.6/site-packages/numexpr/utils.py
/usr/lib64/python3.6/site-packages/numexpr/version.py
/usr/share/doc/packages/python3-numexpr
/usr/share/doc/packages/python3-numexpr/ANNOUNCE.rst
/usr/share/doc/packages/python3-numexpr/AUTHORS.txt
/usr/share/doc/packages/python3-numexpr/README.rst
/usr/share/doc/packages/python3-numexpr/RELEASE_NOTES.rst
/usr/share/doc/packages/python3-numexpr/site.cfg.example
/usr/share/licenses/python3-numexpr
/usr/share/licenses/python3-numexpr/LICENSE.txt


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