Changelog for python3-numexpr-2.8.4-qubes.lp155.2.21.x86_64.rpm :

* Mon Jan 02 2023 Dirk Müller - update to 2.8.4:
* Support for Python 3.11 has been added.
* Thanks to Tobias Hangleiter for an improved accuracy complex `expm1` function. While it is 25 % slower, it is significantly more accurate for the real component over a range of values and matches NumPy outputs much more closely.
* Thanks to Kirill Kouzoubov for a range of fixes to constants parsing that was resulting in duplicated constants of the same value.
* Thanks to Mark Harfouche for noticing that we no longer need `numpy` version checks. `packaging` is no longer a requirement as a result.
* Sun Jul 17 2022 Ben Greiner - Fix requirements
* Sat Jul 09 2022 Arun Persaud - specfile:
* require python >= 3.7- update to version 2.8.3:
* Support for Python 3.6 has been dropped due to the need to substitute the flag NPY_ARRAY_WRITEBACKIFCOPY for NPY_ARRAY_UPDATEIFCOPY. This flag change was initiated in NumPy 1.14 and finalized in 1.23. The only changes were made to cases where an unaligned constant was passed in with a pre-allocated output variable: ``` x = np.empty(5, dtype=np.uint8)[1:].view(np.int32) ne.evaluate(\'3\', out=x) ``` We think the risk of issues is very low, but if you are using NumExpr as a expression evaluation tool you may want to write a test for this edge case.
* Thanks to Matt Einhorn (AATTmatham) for improvements to the GitHub Actions build process to add support for Apple Silicon and aarch64.
* Thanks to Biswapriyo Nath (AATTbiswa96) for a fix to allow mingw builds on Windows.
* There have been some changes made to not import platform.machine() on sparc but it is highly advised to upgrade to Python 3.9+ to avoid this issue with the Python core package platform.- changes from version 2.8.2:
* skipped due to an error in uploading to PyPi.
* Mon Feb 07 2022 Arun Persaud - specfile:
* update copyright year
* skip build for python2- update to version 2.8.1:
* Fixed dependency list.
* Added \"pyproject.toml\" and modernize the \"setup.py\" script. Thanks to Antonio Valentino for the PR.- changes from version 2.8.0:
* Wheels for Python 3.10 are now provided.
* Support for Python 2.7 and 3.5 has been discontinued.
* All residual support for Python 2.X syntax has been removed, and therefore the setup build no longer makes calls to the `2to3` script. The `setup.py` has been refactored to be more modern.
* The examples on how to link into Intel VML/MKL/oneAPI now use the dynamic library.
* Fri Mar 12 2021 Dirk Müller - skip python3.6 build (no numpy)
* Wed Mar 03 2021 Arun Persaud - update to version 2.7.3:
* Pinned Numpy versions to minimum supported version in an effort to alleviate issues seen in Windows machines not having the same MSVC runtime installed as was used to build the wheels.
* ARMv8 wheels are now available, thanks to odidev for the pull request.
* Sat Jan 09 2021 Arun Persaud - specfile:
* update copyright year- update to version 2.7.2:
* Support for Python 2.7 and 3.5 is deprecated and will be discontinued when cibuildwheels and/or GitHub Actions no longer support these versions.
* Wheels are now provided for Python 3.7, 3.5, 3.6, 3.7, 3.8, and 3.9 via GitHub Actions.
* The block size is now exported into the namespace as numexpr.__BLOCK_SIZE1__ as a read-only value.
* If using MKL, the number of threads for VML is no longer forced to 1 on loading the module. Testing has shown that VML never runs in multi-threaded mode for the default BLOCKSIZE1 of 1024 elements, and forcing to 1 can have deleterious effects on NumPy functions when built with MKL. See issue #355 for details.
* Use of ndarray.tostring() in tests has been switch to ndarray.tobytes() for future-proofing deprecation of .tostring(), if the version of NumPy is greater than 1.9.
* Added a utility method get_num_threads that returns the (maximum) number of threads currently in use by the virtual machine. The functionality of set_num_threads whereby it returns the previous value has been deprecated and will be removed in 2.8.X.
* Wed Jan 08 2020 Todd R - 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 - 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 AATTeltoder 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 - 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 arunAATTgmx.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 toddrme2178AATTgmail.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 jengelhAATTinai.de- Ensure neutrality of description.
* Sun Sep 24 2017 arunAATTgmx.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 toddrme2178AATTgmail.com- Source url must be https.
* Wed Apr 19 2017 toddrme2178AATTgmail.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 AATT 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 AATTnbecker.- 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 toddrme2178AATTgmail.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.moninAATTgmx.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