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Comment by fauigerzigerk | Hacker News Reader

Apparently there's a function call overhead as well that the % operator doesn't incur because

  for i in xrange(10000000):
    s = "%s" % i

is also faster than

  lstr = str
  for i in xrange(10000000):
    s = lstr(i)

[Edit] After thinking about it a second longer, I wonder whether there is some lookup for lstr as well even though it's local. But storing the function in lstr is faster than using str so I'm not sure how this is actually implemented. I'm sure someone here will know more.

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You need to make sure you do all your benchmarks in a function. In a funtion, local variables translate to indexes into a local variable array; outside of a function, they remain globals lookups.

Your first reply that "there's always a lookup" isn't right. Some variable accesses (specifically: local variable accesses) do simply map to array accesses.

Yes there is lookup, always lookup. Dynamic language, something in loop could change what lstr is.

Each "dot" incurs lookup. Your example reminds me of one idiom. Assigning nested.look.up to local var for access inside loop.

>Yes there is lookup, always lookup. Dynamic language, something in loop could change what lstr is.

And why is that presented as something inevitable?

The interpreter/compiler could analyze that part and see that the function/name is not changed during the loop, and cache for that.

I'd guess that PyPy tries to do it that way, anyway...

Yes, that's one of the many optimizations PyPy does, however it's only a very limited one. PyPy goes much, much deeper than this, with tools like function inlining and escape analysis.

CPython compiles to bytecode, turning all local variable references into offsets into a local variable array. So, getting the "str" function requires a global name lookup, while getting your local "lstr" only requires an array lookup with a constant embedded in the bytecode.

You can have a lot of fun playing with the dis module to look at the bytecode that Python generates for your functions:

http://docs.python.org/library/dis.html

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