» In which we take a critical look at a flawed speed contest, and improve Python code in spite of that.
This page has a comparison of list-processing scripts in various languages. Apparently the idea is to create a list (or vector, or table, or array) of 100,000 elements, populate them with random values between 0 and 1, add all those values, and compute the square root. [via]
Now... I don't know if the author intended all examples to be exactly the same, or that it's just filler to demonstrate his software. I am far from a benchmarking expert, but off the top of my head, I can think of a few things that are wrong here:
Vector), others do not. In any case, comparing a Python list to a C++ array is apples and pears, IMHO.
Anyway, of course I had to look at the Python script and see if I could make it run faster. Here's the original:
import time import random import math t=time.clock() a=[random.random() for i in range(1,100000)] def add(x,y): return x+y print(reduce(add, a)) def square(x): return x*x print(math.sqrt(reduce(add, map(square, a)))) print(time.clock()-t)
Aside from the fact that the Python version creates a list of 99,999 items rather than 100,000, there are many things that can be improved. This is what I came up with without trying very hard (it's about half the time of the original script):
import time import random import math t=time.clock() a = [random.random() for i in range(100000)] print sum(a) print math.sqrt(sum(x*x for x in a)) print time.clock() - t
The obvious improvements being, using
sum rather than
reduce and a custom
add function; and using a generator expression for the second part. I'm sure it can be made faster, possibly quite a bit so -- but that's not the point of this post. :-)
In the site's results, Io clocks in at a cool 0.04s. Even though the benchmark as a whole is flawed, it's nice to see that a very dynamic language can also be very fast. Then again, in normal circumstances you probably would use
List rather than
Vector. This post shows the two approaches. (
List is quite a bit slower and doesn't have special-case methods like