Monday 4 November 2019
performance - Why does Python code run faster in a function?
Answer
Answer
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
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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