Reputation: 15996
I want to know which one is better in performance terms: a "regular" python function with state, or a generator. Unlike similar questions, I'm using the most simplified function to isolate the problem:
Regular function:
>>> def counter_reg():
if not hasattr(count_regular,"c"):
count_regular.c = -1
count_regular.c +=1
return count_regular.c
Generator functions:
>>> def counter_gen():
c = 0
while True:
yield c
c += 1
>>> counter = counter_gen()
>>> counter = counter.next
In both cases, calling counter()
and counter_reg()
will produce the same output.
Which one is better in terms of performance? Thanks,
Upvotes: 2
Views: 1339
Reputation: 880389
Here is an example of how you can benchmark Python functions using the timeit module:
test.py:
import itertools as IT
def count_regular():
if not hasattr(count_regular,"c"):
count_regular.c = -1
count_regular.c +=1
return count_regular.c
def counter_gen():
c = 0
while True:
yield c
c += 1
def using_count_regular(N):
return [count_regular() for i in range(N)]
def using_counter_gen(N):
counter = counter_gen()
return [next(counter) for i in range(N)]
def using_itertools(N):
count = IT.count()
return [next(count) for i in range(N)]
Run python like this to time the functions:
% python -mtimeit -s'import test as t' 't.using_count_regular(1000)'
1000 loops, best of 3: 336 usec per loop
% python -mtimeit -s'import test as t' 't.using_counter_gen(1000)'
10000 loops, best of 3: 172 usec per loop
% python -mtimeit -s'import test as t' 't.using_itertools(1000)'
10000 loops, best of 3: 105 usec per loop
For a more thorough benchmarking, try different values of N
, though in this case I don't think it is going to matter.
So as you would expect, using itertools.count
is faster than either count_regular
or counter_gen
.
Upvotes: 5