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 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.
This is a maintenance release where an important bug in multithreading code has been fixed (#185 Benedikt Reinartz, Francesc Alted). Also, many harmless warnings (overflow/underflow, divide by zero and others) in the test suite have been silenced (#183, Francesc Alted).
In case you want to know more in detail what has changed in this version, see:
https://github.com/pydata/numexpr/blob/master/RELEASE_NOTES.rst
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
Let us know of any bugs, suggestions, gripes, kudos, etc. you may have.
Enjoy data!