从列表中随机选择50个项目写入文件 [英] Select 50 items from list at random to write to file

问题描述

到目前为止，我已经弄清楚了如何导入文件，创建新文件以及将列表随机化.

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

我在从列表中随机选择50个项目以写入文件时遇到麻烦了吗?

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')   

因此，如果总随机文件为

So if the total randomization file was

example:

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

我想要3个文件(out_file1 | 2 | 3)，其中第一个随机集为3，第二个随机集为3，第三个随机集为3(对于此示例，但是我要创建的文件应具有50个)

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']

所以不会包含最后一个'4'.

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

如何从随机选择的列表中选择50个?

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

更好的是，如何从原始列表中随机选择50个?

推荐答案

如果列表是随机排列的，则只需取前50个即可.

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

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)

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