I am trying to write an algorithm that would pick N distinct items from an sequence at random, without knowing the size of the sequence in advance, and where it is expensive to iterate over the sequence more than once. For example, the elements of the sequence might be the lines of a huge file.

I have found a solution when N=1 (that is, when trying to pick exactly one element at random from a huge sequence):

```
import random
items = range(1, 10) # Imagine this is a huge sequence of unknown length
count = 1
selected = None
for item in items:
if random.random() * count < 1:
selected = item
count += 1
```

But how can I achieve the same thing for other values of N (say, N=3)?

Use reservoir sampling. It's a very simple algorithm that works for any `N`

.

If your sequence is short enough that reading it into memory and randomly sorting it is acceptable, then a straightforward approach would be to just use `random.shuffle`

:

```
import random
arr=[1,2,3,4]
# In-place shuffle
random.shuffle(arr)
# Take the first 2 elements of the now randomized array
print arr[0:2]
[1, 3]
```

Depending upon the type of your sequence, you may need to convert it to a list by calling `list(your_sequence)`

on it, but this will work regardless of the types of the objects in your sequence.

Naturally, if you can't fit your sequence into memory or the memory or CPU requirements of this approach are too high for you, you will need to use a different solution.

Licensed under: CC-BY-SA with attribution

Not affiliated with: Stack Overflow