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15.0 > Python > numexpr (2.7.2)

The numexpr package evaluates multiple-operator array expressions
many times faster than NumPy can. It accepts the expression as a
string, analyzes it, rewrites it more efficiently, and compiles it to
faster Python code on the fly. It's the next best thing to writing the
expression in C and compiling it with a specialized just-in-time (JIT)
compiler, i.e. it does not require a compiler at runtime.

Also, and since version 1.4, numexpr implements support for
multi-threading computations straight into its internal virtual
machine, written in C. This allows to bypass the GIL in Python, and
allows near-optimal parallel performance in your vector expressions,
most specially on CPU-bounded operations (memory-bounded were already
the strong point of Numexpr).

This requires: python3-numpy

Maintained by: Benjamin Trigona-Harany
ChangeLog: numexpr


Source Downloads:
numexpr-2.7.2.tar.gz (d41e3345b19209713b195f03ca5a3ee0)

Download SlackBuild:
numexpr.tar.gz.asc (FAQ)

(the SlackBuild does not include the source)

Individual Files:

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