从列表中随机选择50个项目写入文件

Question

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')   

example:

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

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

Answer 1

如果列表的顺序是随机的，你可以只取前50个。

否则，请使用

import random
random.sample(the_list, 50)

random.sample帮助文本：

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)