I have a misinformed theory that I'd like to share with the list.
I believe that profiler calibration no longer makes sense in Python 2.4
because C functions are tracked and they have a different call overhead
than Python functions (and calibration is done only using Python
functions). Here is my reasoning (in code form):
% c:\python24\python
...
>>> import profile
>>> p = profile.Profile()
>>> for i in range(5):
... print p.calibrate(1000000)
...
4.00375499355e-006
3.95700929469e-006
3.94034406478e-006
4.00315854962e-006
3.99454335716e-006
Code
----
import profile
profile.Profile.bias = 3.90e-006 # very conservative
def bar():
l = []
for i in range(100000):
l += [i]
def foo():
l = []
for i in range(100000):
l.append(i) # C function that can be tracked
def baz():
bar()
foo()
profile.run('baz()', "out.prof")
from pstats import Stats
s = Stats('out.prof')
s.sort_stats('time', 'calls')
s.print_stats()
from timeit import Timer
t1 = Timer(
'bar()', 'from __main__ import bar',)
print 'bar():', t1.timeit(1000) / 1000
t2 = Timer(
'foo()', 'from __main__ import foo',)
print 'foo():', t2.timeit(1000) / 1000
Output
------
Thu Jun 15 10:22:29 2006 out.prof
100008 function calls in -0.090 CPU seconds
Ordered by: internal time, call count
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.058 0.058 0.062 0.062 cal-test.py:4(bar)
2 0.006 0.003 0.006 0.003 :0(range)
1 0.004 0.004 -0.090 -0.090 cal-test.py:14(baz)
1 0.001 0.001 0.001 0.001 :0(setprofile)
1 0.000 0.000 -0.090 -0.090 profile:0(baz())
1 0.000 0.000 -0.090 -0.090 <string>:1(?)
0 0.000 0.000 profile:0(profiler)
1 -0.066 -0.066 -0.157 -0.157 cal-test.py:9(foo)
100000 -0.094 -0.000 -0.094 -0.000 :0(append)
bar(): 0.0582713573932
foo(): 0.0370039776005
Analysis
--------
As you can see, the profiler result for "bar" is pretty reasonable but
it is not for "foo" or "append". I believe that is because the calling
of the C function "append" takes less time than is accounted for in the
bias measurement (which was generated by measuring the call time of a
Python function).
So the bias computation doesn't make sense in Python 2.4.
What do y'all think? Is this a well known fact? Should I construct a
test to see if C function call overhead is actually less than Python
function call overhead?
Cheers,
Brian
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