============================ Announcing Numexpr 2.1RC1 ============================
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 wears multi-threaded capabilities, as well as support for Intel's VML library, which allows for squeezing the last drop of performance out of your multi-core processors. What's new ========== This version adds compatibility for Python 3. A bunch of thanks to Antonio Valentino for his excelent work on this.I apologize for taking so long in releasing his contributions. In case you want to know more in detail what has changed in this version, see: http://code.google.com/p/numexpr/wiki/ReleaseNotes or have a look at RELEASE_NOTES.txt in the tarball. Where I can find Numexpr? ========================= The project is hosted at Google code in: http://code.google.com/p/numexpr/ This is a release candidate 1, so it will not be available on the PyPi repository. I'll post it there when the final version will released. Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy! -- Francesc Alted ------------------------------------------------------------------------------ Precog is a next-generation analytics platform capable of advanced analytics on semi-structured data. The platform includes APIs for building apps and a phenomenal toolset for data science. Developers can use our toolset for easy data analysis & visualization. Get a free account! http://www2.precog.com/precogplatform/slashdotnewsletter _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
