Why this list comprehension is faster than equivalent generator expression?

Question

I'm using Python 3.3.1 64-bit on Windows and this code snippet:

len ([None for n in range (1, 1000000) if n%3 == 1])

executes in 136ms, compared to this one:

sum (1 for n in range (1, 1000000) if n%3 == 1)

which executes in 146ms. Shouldn't a generator expression be faster or the same speed as the list comprehension in this case?

I quote from Guido van Rossum From List Comprehensions to Generator Expressions:

...both list comprehensions and generator expressions in Python 3 are actually faster than they were in Python 2! (And there is no longer a speed difference between the two.)

EDIT:

I measured the time with timeit. I know that it is not very accurate, but I care only about relative speeds here and I'm getting consistently shorter time for list comprehension version, when I test with different numbers of iterations.

Answer 1

I believe the difference here is entirely in the cost of 1000000 additions. Testing with 64-bit Python.org 3.3.0 on Mac OS X:

In [698]: %timeit len ([None for n in range (1, 1000000) if n%3 == 1])
10 loops, best of 3: 127 ms per loop
In [699]: %timeit sum (1 for n in range (1, 1000000) if n%3 == 1)
10 loops, best of 3: 138 ms per loop
In [700]: %timeit sum ([1 for n in range (1, 1000000) if n%3 == 1])
10 loops, best of 3: 139 ms per loop

So, it's not that the comprehension is faster than the genexp; they both take about the same time. But calling len on a list is instant, while summing 1M numbers adds another 7% to the total time.

Throwing a few different numbers at it, this seems to hold up unless the list is very tiny (in which case it does seem to get faster), or large enough that memory allocation starts to become a significant factor (which it isn't yet, at 333K).