On Sun, Jul 18, 2010 at 11:07, bob gailer <bgai...@gmail.com> wrote:
> Check this out:
>
> import random, time
> s = time.time()
> cycles = 1000
> d = "0123456789"*100
> f = open("numbers.txt", "w")
> for i in xrange(n):
> l = []
> l.extend(random.sample(d, 1000))
> f.write(''.join(l))
> f.close()
> print time.time() - s
>
> 1 million in ~1.25 seconds
>
> Therefore 1 billion in ~21 minutes. 3 ghz processor 2 g ram.
>
> Changing length up or down seems to increase time.
Putting "cycles" where you have "n", I used
import random, time
s = time.time()
cycles = 1000000
d = "0123456789"*100
f = open("/p31working/Data/1billion_digits_rand_num_Gailor.txt", "w")
for i in range(cycles):
l = []
l.extend(random.sample(d, 1000))
f.write(''.join(l))
f.close()
print(time.time() - s)
to get 1 billion random digits into a file in 932 seconds (15.6
minutes). <http://tutoree7.pastebin.com/Ldh6SX3q>, which uses Steve
D'Aprano's random_digits function, took 201 seconds (3.35 minutes).
Still, I understand yours, and not his (the return line). I'd never
noticed random.sample() before, nor tried out extend() on a list. So
thanks, Bob.
Dick
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