On Wed, Feb 26, 2014 at 11:30 PM, Frank Millman <fr...@chagford.com> wrote:
> Hi all
>
> I noticed this a little while ago, but dismissed it as a curiosity. On
> reflection, I decided to mention it here in case it indicates a problem.
>
> This is with python 3.3.2.
>
> C:\>python -m timeit -s "import copy" "copy.copy('a'*1000)"
> 100000 loops, best of 3: 6.91 usec per loop
>
> C:\>python -m timeit -s "import copy" "copy.deepcopy('a'*1000)"
> 100000 loops, best of 3: 11.8 usec per loop
>
> C:\>python -m timeit -s "import copy" "copy.copy(b'a'*1000)"
> 10000 loops, best of 3: 79.9 usec per loop
>
> C:\>python -m timeit -s "import copy" "copy.deepcopy(b'a'*1000)"
> 100000 loops, best of 3: 11.7 usec per loop
>
> As you can see, deepcopying a string is slightly slower than copying it.
>
> However, deepcopying a byte string is orders of magnitude quicker than
> copying it.
>
> Actually, looking closer, it is the 'copy' that is slow, not the 'deepcopy'
> that is quick..
>
> Expected, or odd?This will shed some light: >>> a = 'a' * 1000 >>> b = copy.copy(a) >>> a is b True >>> c = copy.deepcopy(a) >>> a is c True >>> d = b'a' * 1000 >>> e = copy.copy(d) >>> d is e False >>> f = copy.deepcopy(d) >>> d is f True For some reason, calling copy.copy on a bytes object actually copies the bytes, rather than just returning the immutable object passed in. That's probably not intentional and is worth opening a ticket for. The difference between copy and deepcopy is probably just due to the extra overhead of deepcopy. -- https://mail.python.org/mailman/listinfo/python-list
