Why does Python code run faster in a function?

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def main():
    for i in xrange(10**8):
        pass
main()

This piece of code in Python runs in (Note: The timing is done with the time function in BASH in Linux.)

real    0m1.841s
user    0m1.828s
sys     0m0.012s

However, if the for loop isn"t placed within a function,

for i in xrange(10**8):
    pass

then it runs for a much longer time:

real    0m4.543s
user    0m4.524s
sys     0m0.012s

Why is this?

Answer rating: 668

Inside a function, the bytecode is:

  2           0 SETUP_LOOP              20 (to 23)
              3 LOAD_GLOBAL              0 (xrange)
              6 LOAD_CONST               3 (100000000)
              9 CALL_FUNCTION            1
             12 GET_ITER            
        >>   13 FOR_ITER                 6 (to 22)
             16 STORE_FAST               0 (i)

  3          19 JUMP_ABSOLUTE           13
        >>   22 POP_BLOCK           
        >>   23 LOAD_CONST               0 (None)
             26 RETURN_VALUE        

At the top level, the bytecode is:

  1           0 SETUP_LOOP              20 (to 23)
              3 LOAD_NAME                0 (xrange)
              6 LOAD_CONST               3 (100000000)
              9 CALL_FUNCTION            1
             12 GET_ITER            
        >>   13 FOR_ITER                 6 (to 22)
             16 STORE_NAME               1 (i)

  2          19 JUMP_ABSOLUTE           13
        >>   22 POP_BLOCK           
        >>   23 LOAD_CONST               2 (None)
             26 RETURN_VALUE        

The difference is that STORE_FAST is faster (!) than STORE_NAME. This is because in a function, i is a local but at toplevel it is a global.

To examine bytecode, use the dis module. I was able to disassemble the function directly, but to disassemble the toplevel code I had to use the compile builtin.

Answer rating: 564

You might ask why it is faster to store local variables than globals. This is a CPython implementation detail.

Remember that CPython is compiled to bytecode, which the interpreter runs. When a function is compiled, the local variables are stored in a fixed-size array (not a dict) and variable names are assigned to indexes. This is possible because you can"t dynamically add local variables to a function. Then retrieving a local variable is literally a pointer lookup into the list and a refcount increase on the PyObject which is trivial.

Contrast this to a global lookup (LOAD_GLOBAL), which is a true dict search involving a hash and so on. Incidentally, this is why you need to specify global i if you want it to be global: if you ever assign to a variable inside a scope, the compiler will issue STORE_FASTs for its access unless you tell it not to.

By the way, global lookups are still pretty optimised. Attribute lookups foo.bar are the really slow ones!

Here is small illustration on local variable efficiency.





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