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I was just messing around when I came across this quirk. And I wanted to make sure I am not crazy. The following code (works in 2.x and 3.x): from timeit import timeit print ('gen: %s' % timeit('"-".join(str(n) for n in range(1000))', number=10000)) print ('list: %s' % timeit('"-".join([str(n) for n in range(1000)])', number=10000)) Doing 3 runs on each version, same machine. note: I grouped the timings on the same line to save space here. On my Python 2.7.5: gen: 2.37875941643, 2.44095773486, 2.41718937347 list: 2.1132466183, 2.12248106441, 2.11737128131 On my Python 3.3.2: gen: 3.8801268438439718, 3.9939604983350185, 4.166233972077624 list: 2.976764740845537, 3.0062614747229555, 3.0734980312273894 I wonder why this is.... Might it have something to do with how strings are implemented? EDIT: I did it again without using range() since that has also changed slightly from 2.x to 3.x Instead I use the new code below: from timeit import timeit print ('gen: %s' % timeit('"-".join(str(n) for n in (1, 2, 3))', number=1000000)) print ('list: %s' % timeit('"-".join([str(n) for n in (1, 2, 3)])', number=1000000)) The Timing for Python 2.7.5: gen: 2.13911803683, 2.16418448199, 2.13403650485 list: 0.797961223325, 0.767758578433, 0.803272800119 The Timing for Python 3.3.2: gen: 2.8188347625218486, 2.882846655874985, 3.0317612259663718 list: 1.3590610502957934, 1.4878876089869366, 1.4978070529462615 EDIT2: It seems there were some more things throwing off the calculation, so I tried bringing it down to a bare-minimum. New Code: from timeit import timeit print ('gen: %s' % timeit('"".join(n for n in ("1", "2", "3"))', number=1000000)) print ('list: %s' %

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