implement random selection in Python

[Scott David Daniels]

J. Clifford Dyer wrote:
> My understanding of what you are looking for is that on each individual selection, 
> the probability of picking a given name is that name's prob value, divided by the 
 > sum of all prob values.  That is, in the following case:
> items = [('Mary',  96),('Shimon', 1), ('Aisha', 1), ('Toshiro', 2)]
> ... On the first pass Mary has a 96% chance of getting selected, ....
> If that is correct, then the following might meet your needs:
> 
> from random import choice
> 
> def select(weighted_list, n=1):
>     selected = set()
>     for iteration in xrange(n):
>         print iteration
>         selection_list = []
>         for item in weighted_list:
>             if item[0] not in selected:
>                 selection_list.extend([item[0]] * item[1])
>         #print selection_list
>         this_choice = choice(selection_list)
>         #print this_choice
>         selected.add(this_choice)
>         return selected

or even:

def picks(weighted_list, N):
     result = []
     adict = dict(weighted_list)
     total = sum(adict.values())
     for i in range(N):
         score = random.random() * total
         for choice, weight in cp.iteritems():
             if weight < score:
                 score -= weight
             else:
                 result.append(choice)
                 total -= cp.pop(choice)
                 break
         else:
             raise ValueError('ran out of data')
     return result

-Scott