3 ms·

Note that since this article was written (2004) CPython performs an in-place optimisation for assignments of the form s1 += s2 There are details at point

by inglesp 13y ago

Note that since this article was written (2004) CPython performs an in-place optimisation for assignments of the form s1 += s2 There are details at point six of http://docs.python.org/2/library/stdtypes.html#sequence-types-str-unicode-list-tuple-bytearray-buffer-xrange http://docs.python.org/2/library/stdtypes.html#sequence-type..., where it also says that str.join() is preferable.

anaphor 13y ago
Does PyPy have the same heuristic? If not, I wouldn't recommend relying on it.
- zokier 13y ago
  If not, I would recommend submitting a bug to PyPy.
  - kingkilr 13y ago
    No it doesn't, and that heuristic isn't possible. It's based on looking at the reference counting and mutating an immutable object. It's pretty awful.
  - ewoodrich 13y ago
    If GP is referring to CPython patch #980695, it appears to be available in PyPy, but requires an additional flag. "We have it, just not enabled by default. --objspace-with-strbuf I think" [1] [1] https://mail.python.org/pipermail/python-dev/2013-February/124004.html https://mail.python.org/pipermail/python-dev/2013-February/1...
MBCook 13y ago
OK, so for fun I did a ran this on my machine (MacBook Pro, 2.53GHz, 10.8.4, 8GB ram, Python 2.7.2 shipped by Apple). I had to emulate the old timing module using code from [1]. Method 1: 0.115 seconds Method 2: I gave up after >120s Method 3: 0.265 Method 4: 0.160 Method 5: 0.220 Method 6: 0.098 I ran each one a few times to make sure the times were roughly correct. Method 6 is still the fastest, but the naive method one is really close. it obviously got optimized. Actually, they're all pretty close with the obvious (and hideous) outlier of using MutableString. EDIT: I just remembered I have an old version of PyPy (1.8) on my Mac. Thought I'd give that a try. Method 1: I gave up after >120s Method 2: I gave up after >120s Method 3: 0.090 seconds Method 4: 0.102 Method 5: 0.430 Method 6: 0.102 Method one is a problem again, and method 5 (the pseudo file) is noticeably slower. Otherwise the results aren't too far off. [1] http://effbot.org/librarybook/timing.htm http://effbot.org/librarybook/timing.htm
- pkj 13y ago
  Similar relative results, except that method 1 is always the fastest and even better than method 6. Ran loop count with large numbers (10 million & 30 million) to reduce measurement noise. Profiling was with cProfile on Core i3 2.53Ghz, 6 GB ram, Python 2.7.3 on Ubuntu 12.04 for 10M loop count, method 1 -> 1.599 s, method 6 -> 1.91 s for 30M loop count,method 1 -> 4.967 s, method 6 -> 5.871 s Summary: The KISS s1 += s2 always wins

by inglesp 13y ago

anaphor 13y ago

Does PyPy have the same heuristic? If not, I wouldn't recommend relying on it.

zokier 13y ago
If not, I would recommend submitting a bug to PyPy.
- kingkilr 13y ago
  No it doesn't, and that heuristic isn't possible. It's based on looking at the reference counting and mutating an immutable object. It's pretty awful.
- ewoodrich 13y ago
  If GP is referring to CPython patch #980695, it appears to be available in PyPy, but requires an additional flag. "We have it, just not enabled by default. --objspace-with-strbuf I think" [1] [1] https://mail.python.org/pipermail/python-dev/2013-February/124004.html https://mail.python.org/pipermail/python-dev/2013-February/1...

MBCook 13y ago

OK, so for fun I did a ran this on my machine (MacBook Pro, 2.53GHz, 10.8.4, 8GB ram, Python 2.7.2 shipped by Apple). I had to emulate the old timing module using code from [1]. Method 1: 0.115 seconds Method 2: I gave up after >120s Method 3: 0.265 Method 4: 0.160 Method 5: 0.220 Method 6: 0.098 I ran each one a few times to make sure the times were roughly correct. Method 6 is still the fastest, but the naive method one is really close. it obviously got optimized. Actually, they're all pretty close with the obvious (and hideous) outlier of using MutableString. EDIT: I just remembered I have an old version of PyPy (1.8) on my Mac. Thought I'd give that a try. Method 1: I gave up after >120s Method 2: I gave up after >120s Method 3: 0.090 seconds Method 4: 0.102 Method 5: 0.430 Method 6: 0.102 Method one is a problem again, and method 5 (the pseudo file) is noticeably slower. Otherwise the results aren't too far off. [1] http://effbot.org/librarybook/timing.htm http://effbot.org/librarybook/timing.htm

pkj 13y ago
Similar relative results, except that method 1 is always the fastest and even better than method 6. Ran loop count with large numbers (10 million & 30 million) to reduce measurement noise. Profiling was with cProfile on Core i3 2.53Ghz, 6 GB ram, Python 2.7.3 on Ubuntu 12.04 for 10M loop count, method 1 -> 1.599 s, method 6 -> 1.91 s for 30M loop count,method 1 -> 4.967 s, method 6 -> 5.871 s Summary: The KISS s1 += s2 always wins