Changelog for python-numexpr-2.1-4.6.i586.rpm :
Mon May 6 14:00:00 2013 highwaystar.ruAATTgmail.com
- python3 package added
- update to 2.1

* New compatibility with Python 3:

* switch from PyString to PyBytes API (requires Python >= 2.6).

* fixed incompatibilities regarding the int/long API

* use the Py_TYPE macro

* use the PyVarObject_HEAD_INIT macro instead of PyObject_HEAD_INIT

* Dropped compatibility with Python < 2.6.

* Fixed several issues with different platforms not supporting
multithreading or subprocess properly (see tickets #75 and #77).

* Now, when trying to use pure Python boolean operators, \'and\',
\'or\' and \'not, an error is issued and suggesting that \'&\', \'|\'
and \'~\' should be used instead (fixes #24).

Tue Aug 14 14:00:00 2012 scorotAATTfree.fr
- fix requiements for SLE 11

Tue Jul 31 14:00:00 2012 toddrme2178AATTgmail.com
- Update to 2.0.1

* Added compatibility with Python 2.5 (2.4 is definitely not supported
anymore).

* `numexpr.evaluate` is fully documented now, in particular the new
`out`, `order` and `casting` parameters.

* Reduction operations are fully documented now.

* Negative axis in reductions are not supported (they have never been
actually), and a `ValueError` will be raised if they are used.
- Update to 2.0
- Added support for the new iterator object in NumPy 1.6 and later.
This allows for better performance with operations that implies
broadcast operations, fortran-ordered or non-native byte orderings.
Performance for other scenarios is preserved (except for very small
arrays).
- Division in numexpr is consistent now with Python/NumPy. Fixes #22
and #58.
- Constants like \"2.\" or \"2.0\" must be evaluated as float, not
integer. Fixes #59.
- `evaluate()` function has received a new parameter `out` for storing
the result in already allocated arrays. This is very useful when
dealing with large arrays, and a allocating new space for keeping
the result is not acceptable. Closes #56.
- Maximum number of threads raised from 256 to 4096. Machines with a
higher number of cores will still be able to import numexpr, but
limited to 4096 (which is an absurdly high number already).
- Update to 1.4.2
- Multithreaded operation is disabled for small arrays (< 32 KB).
This allows to remove the overhead of multithreading for such a
small arrays. Closes #36.
- Dividing int arrays by zero gives a 0 as result now (and not a
floating point exception anymore. This behaviour mimics NumPy.
Thanks to Gaëtan de Menten for the fix. Closes #37.
- When compiled with VML support, the number of threads is set to 1
for VML core, and to the number of cores for the native pthreads
implementation. This leads to much better performance. Closes #39.
- Fixed different issues with reduction operations (`sum`, `prod`).
The problem is that the threaded code does not work well for
broadcasting or reduction operations. Now, the serial code is used
in those cases. Closes #41.
- Optimization of \"compilation phase\" through a better hash. This can
lead up to a 25% of improvement when operating with variable
expressions over small arrays. Thanks to Gaëtan de Menten for the
patch. Closes #43.
- The ``set_num_threads`` now returns the number of previous thread
setting, as stated in the docstrings.

Fri Jul 1 14:00:00 2011 saschpeAATTsuse.de
- Require python-numpy

Fri Jul 1 14:00:00 2011 saschpeAATTsuse.de
- Initial version