========================== Announcing Numexpr 2.6.5 ========================== Hi everyone, This is primarily an incremental performance improvement release, especially with regards to improving import times of downstream packages (e.g. `pandas`, `tables`, `sympy`). Import times have been reduced from ~300 ms to ~100 ms through removing a `pkg_resources` import and making the `cpuinfo` import lazy. The maximum number of threads is now set at import-time, similar to `numba`, by setting an environment variable 'NUMEXPR_MAX_THREADS'. The runtime number of threads can still be reduced by calling `numexpr.set_num_threads(N)`. DEPRECATION WARNING: The variable `numexpr.is_cpu_amd_intel` has been set to a dummy value of `False`. This variable may be removed in the future. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.6.4 to 2.6.5 --------------------------- - The maximum thread count can now be set at import-time by setting the environment variable 'NUMEXPR_MAX_THREADS'. The default number of max threads was lowered from 4096 (which was deemed excessive) to 64. - A number of imports were removed (pkg_resources) or made lazy (cpuinfo) in order to speed load-times for downstream packages (such as `pandas`, `sympy`, and `tables`). Import time has dropped from about 330 ms to 90 ms. Thanks to Jason Sachs for pointing out the source of the slow-down. - Thanks to Alvaro Lopez Ortega for updates to benchmarks to be compatible with Python 3. - Travis and AppVeyor now fail if the test module fails or errors. - Thanks to Mahdi Ben Jelloul for a patch that removed a bug where constants in `where` calls would raise a ValueError. - Fixed a bug whereby all-constant power operations would lead to infinite recursion. -- Robert McLeod, Ph.D. robbmcleod@gmail.com robbmcleod@protonmail.com robert.mcleod@hitachi-hhtc.ca www.entropyreduction.al