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13 lines
763 B
Text
13 lines
763 B
Text
The numexpr package evaluates multiple-operator array expressions
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many times faster than NumPy can. It accepts the expression as a
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string, analyzes it, rewrites it more efficiently, and compiles it to
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faster Python code on the fly. It's the next best thing to writing the
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expression in C and compiling it with a specialized just-in-time (JIT)
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compiler, i.e. it does not require a compiler at runtime.
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Also, and since version 1.4, numexpr implements support for
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multi-threading computations straight into its internal virtual
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machine, written in C. This allows to bypass the GIL in Python, and
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allows near-optimal parallel performance in your vector expressions,
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most specially on CPU-bounded operations (memory-bounded were already
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the strong point of Numexpr).
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