======================== Announcing NumExpr 2.8.4 ======================== Hi everyone, This is a maintenance and bug-fix release for NumExpr. In particular, now we have added Python 3.11 support. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.8.3 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. What's Numexpr? --------------- Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It has multi-threaded capabilities, as well as support for Intel's MKL (Math Kernel Library), which allows an extremely fast evaluation of transcendental functions (sin, cos, tan, exp, log...) while squeezing the last drop of performance out of your multi-core processors. Look here for a some benchmarks of numexpr using MKL: https://github.com/pydata/numexpr/wiki/NumexprMKL Its only dependency is NumPy (MKL is optional), so it works well as an easy-to-deploy, easy-to-use, computational engine for projects that don't want to adopt other solutions requiring more heavy dependencies. Where I can find Numexpr? ------------------------- The project is hosted at GitHub in: https://github.com/pydata/numexpr You can get the packages from PyPI as well (but not for RC releases): http://pypi.python.org/pypi/numexpr Documentation is hosted at: http://numexpr.readthedocs.io/en/latest/ Share your experience --------------------- Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy data! -- Robert McLeod robbmcleod@gmail.com robert.mcleod@hitachi-hightech.com