On Fri, 02 Nov 2007 17:08:06 -0500, Chris Mellon wrote:
>>>> def test_func():
> ... pass
> ...
>>>> import new
>>>> test_func2 = new.function(test_func.func_code, {}, "test_func2")
[snip results of timeit]
> Why almost twice the calling overhead for a dynamic function?
When I time the functions, I get a lot of variability. The minimum value
is probably the best one to look at:
>>> min(timeit.Timer("test_func()",
... "from __main__ import test_func").repeat(20))
0.35664010047912598
>>> min(timeit.Timer("test_func2()",
... "from __main__ import test_func2").repeat(20))
0.68138217926025391
Disassembling the code does not give any hints:
>>> import dis
>>> dis.dis(test_func)
2 0 LOAD_CONST 0 (None)
3 RETURN_VALUE
>>> dis.dis(test_func2)
2 0 LOAD_CONST 0 (None)
3 RETURN_VALUE
Which is what we should expect, because both functions have the same code:
>>> test_func.func_code is test_func2.func_code
True
But try this:
>>> test_func3 = new.function(test_func.func_code,
... globals(), 'test_func3')
>>> min(timeit.Timer("test_func3()",
... "from __main__ import test_func3").repeat(20))
0.35772204399108887
Hmmm... it looks like the difference in speed has to do with the globals,
not the fact that it is created dynamically. I wonder why?
--
Steven.
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