On Aug 22, 2007, at 7:56 AM, David Cournapeau wrote:
For example, the following python code:class A: def _foo(self): return None def foo(self): return self._foo() Is extremely slow compared to a compiled language like C. On mycomputer, I can only execute the above function around 1 millon times a second (it takes around 3500 cycles by using %timeit from ipython). Thisforces me to avoid functions in some performance intensive code, which is ugly. Basically, I am interested in the kind of things described there: http://www.avibryant.com/2006/09/index.html.
The self technology is extremely interesting. For more information, you can read Urs thesis [0], which is the bases for the cool optimization tricks in the
strongtalk vm [1]. The important trick here is that the vm is able to dooptimistic inlining based on type feedback during runtime, and deoptimize
the compiled code when it guesses wrong or when you enter the debugger.I guess you can do the same thing with partial evaluation if you gather enough
runtime statistics to figure out which functions to specialize/inline.More specific for your example, it will result in code looking something like this:
class A_compiled:
def foo(self):
if type(self) == A:
return None # _foo has been inlined
else:
return self._foo() # uncommon case
Of course, the higher up you can start inlining, the less calls is
needed and
better performance is achieved:
a = obj.foo()
turns into:
if type(obj) == A:
a = None
else:
a = obj.foo()
[0] http://www.cs.ucsb.edu/~urs/oocsb/self/papers/urs-thesis.html
[1] http://strongtalk.org/
- Erik Gorset
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