Select 50 items from list at random to write to file

O.rka picture O.rka · Mar 19, 2013 · Viewed 143.9k times · Source

So far I have figured out how to import the file, create new files, and randomize the list.

I'm having trouble selecting only 50 items from the list randomly to write to a file?

def randomizer(input,output1='random_1.txt',output2='random_2.txt',output3='random_3.txt',output4='random_total.txt'):

#Input file 
    query=open(input,'r').read().split()
    dir,file=os.path.split(input)

    temp1 = os.path.join(dir,output1)
    temp2 = os.path.join(dir,output2)
    temp3 = os.path.join(dir,output3)
    temp4 = os.path.join(dir,output4)


    out_file4=open(temp4,'w')

    random.shuffle(query)

    for item in query:
        out_file4.write(item+'\n')   

So if the total randomization file was

example:

random_total = ['9','2','3','1','5','6','8','7','0','4']

I would want 3 files (out_file1|2|3) with the first random set of 3, second random set of 3, and third random set of 3 (for this example, but the one I want to create should have 50)

random_1 = ['9','2','3']
random_2 = ['1','5','6']
random_3 = ['8','7','0']

So the last '4' will not be included which is fine.

How can I select 50 from the list that I randomized ?

Even better, how could I select 50 at random from the original list ?

Answer

John La Rooy picture John La Rooy · Mar 19, 2013

If the list is in random order, you can just take the first 50.

Otherwise, use

import random
random.sample(the_list, 50)

random.sample help text:

sample(self, population, k) method of random.Random instance
    Chooses k unique random elements from a population sequence.

    Returns a new list containing elements from the population while
    leaving the original population unchanged.  The resulting list is
    in selection order so that all sub-slices will also be valid random
    samples.  This allows raffle winners (the sample) to be partitioned
    into grand prize and second place winners (the subslices).

    Members of the population need not be hashable or unique.  If the
    population contains repeats, then each occurrence is a possible
    selection in the sample.

    To choose a sample in a range of integers, use xrange as an argument.
    This is especially fast and space efficient for sampling from a
    large population:   sample(xrange(10000000), 60)