========================= Announcing NumExpr 2.10.0 ========================= Hi everyone, NumExpr 2.10.0 is a release offering support for latest versions of NumPy 2.0. This is still experimental, so please report any issues you find. Thanks to Clément Robert and Thomas Caswell for the work. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.9.0 to 2.10.0 ---------------------------- * Support for NumPy 2.0.0. This is still experimental, so please report any issues you find. Thanks to Clément Robert and Thomas Caswell for the work. * Avoid erroring when OMP_NUM_THREADS is empty string. Thanks to Patrick Hoefler. * Do not warn if OMP_NUM_THREAD set. 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!