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2012-05-11T22:39:27.717
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2012-05-11T22:39:27.717
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<p>Hmmm, using <a href="http://docs.python.org/library/dis.html">dis</a> to show the python bytes codes shows that the functions are identical. Python has optimised the constant (as expected). So I suspect the time differences are caching effects. The timings on my laptop bear this out (using Python 2.7.3 64 bit on linux)</p> <pre><code>Fri May 11 23:37:49 2012 results 8 function calls in 38.825 seconds Ordered by: call count, name/file/line ncalls tottime percall cumtime percall filename:lineno(function) 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects} 1 0.000 0.000 38.825 38.825 <string>:1(<module>) 1 0.000 0.000 38.825 38.825 z.py:31(run_tests) 1 7.880 7.880 7.880 7.880 z.py:6(test1) 1 7.658 7.658 7.658 7.658 z.py:11(test2) 1 7.806 7.806 7.806 7.806 z.py:16(test3) 1 7.784 7.784 7.784 7.784 z.py:21(test4) 1 7.697 7.697 7.697 7.697 z.py:26(test5) </code></pre> <p>All pretty much identical</p> <pre><code>>>> from dis import dis >>> def test1(): ... for i in xrange(AMOUNT): ... value = i % 65536 ... return ... >>> def test5(): ... for i in xrange(AMOUNT): ... value = i % (2**16) ... return ... >>> dis(test1) 2 0 SETUP_LOOP 30 (to 33) 3 LOAD_GLOBAL 0 (xrange) 6 LOAD_GLOBAL 1 (AMOUNT) 9 CALL_FUNCTION 1 12 GET_ITER >> 13 FOR_ITER 16 (to 32) 16 STORE_FAST 0 (i) 3 19 LOAD_FAST 0 (i) 22 LOAD_CONST 1 (65536) 25 BINARY_MODULO 26 STORE_FAST 1 (value) 29 JUMP_ABSOLUTE 13 >> 32 POP_BLOCK 4 >> 33 LOAD_CONST 0 (None) 36 RETURN_VALUE >>> dis(test5) 2 0 SETUP_LOOP 30 (to 33) 3 LOAD_GLOBAL 0 (xrange) 6 LOAD_GLOBAL 1 (AMOUNT) 9 CALL_FUNCTION 1 12 GET_ITER >> 13 FOR_ITER 16 (to 32) 16 STORE_FAST 0 (i) 3 19 LOAD_FAST 0 (i) 22 LOAD_CONST 3 (65536) 25 BINARY_MODULO 26 STORE_FAST 1 (value) 29 JUMP_ABSOLUTE 13 >> 32 POP_BLOCK 4 >> 33 LOAD_CONST 0 (None) 36 RETURN_VALUE >>> </code></pre>
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1. POWhy is taking the mod of a number in python faster with exponents?
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1. USNick Craig-Wood
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