还有另一个递归解决方案(你应该能够使用字母而不是数字)使用堆栈，虽然比大多数更短:

stack = [] 
def choose(n,x):
   r(0,0,n+1,x)

def r(p, c, n,x):
   if x-c == 0:
      print stack
      return

   for i in range(p, n-(x-1)+c):
      stack.append(i)
      r(i+1,c+1,n,x)
      stack.pop()

4选3或者我想要从0到4的所有3种数字组合

choose(4,3) 

[0, 1, 2]
[0, 1, 3]
[0, 1, 4]
[0, 2, 3]
[0, 2, 4]
[0, 3, 4]
[1, 2, 3]
[1, 2, 4]
[1, 3, 4]
[2, 3, 4]

递归，一个很简单的答案，combo，在Free Pascal中。

    procedure combinata (n, k :integer; producer :oneintproc);

        procedure combo (ndx, nbr, len, lnd :integer);
        begin
            for nbr := nbr to len do begin
                productarray[ndx] := nbr;
                if len < lnd then
                    combo(ndx+1,nbr+1,len+1,lnd)
                else
                    producer(k);
            end;
        end;

    begin
        combo (0, 0, n-k, n-1);
    end;

“producer”处理为每个组合生成的产品数组。

static IEnumerable<string> Combinations(List<string> characters, int length)
{
    for (int i = 0; i < characters.Count; i++)
    {
        // only want 1 character, just return this one
        if (length == 1)
            yield return characters[i];

        // want more than one character, return this one plus all combinations one shorter
        // only use characters after the current one for the rest of the combinations
        else
            foreach (string next in Combinations(characters.GetRange(i + 1, characters.Count - (i + 1)), length - 1))
                yield return characters[i] + next;
    }
}

在c++中，以下例程将生成range [first,last)之间的长度距离(first,k)的所有组合:

#include <algorithm>

template <typename Iterator>
bool next_combination(const Iterator first, Iterator k, const Iterator last)
{
   /* Credits: Mark Nelson http://marknelson.us */
   if ((first == last) || (first == k) || (last == k))
      return false;
   Iterator i1 = first;
   Iterator i2 = last;
   ++i1;
   if (last == i1)
      return false;
   i1 = last;
   --i1;
   i1 = k;
   --i2;
   while (first != i1)
   {
      if (*--i1 < *i2)
      {
         Iterator j = k;
         while (!(*i1 < *j)) ++j;
         std::iter_swap(i1,j);
         ++i1;
         ++j;
         i2 = k;
         std::rotate(i1,j,last);
         while (last != j)
         {
            ++j;
            ++i2;
         }
         std::rotate(k,i2,last);
         return true;
      }
   }
   std::rotate(first,k,last);
   return false;
}

它可以这样使用:

#include <string>
#include <iostream>

int main()
{
    std::string s = "12345";
    std::size_t comb_size = 3;
    do
    {
        std::cout << std::string(s.begin(), s.begin() + comb_size) << std::endl;
    } while (next_combination(s.begin(), s.begin() + comb_size, s.end()));

    return 0;
}

这将打印以下内容:

123
124
125
134
135
145
234
235
245
345

在Python中，利用递归的优势和所有事情都是通过引用完成的事实。对于非常大的集合，这将占用大量内存，但其优点是初始集合可以是一个复杂的对象。它只会找到唯一的组合。

import copy

def find_combinations( length, set, combinations = None, candidate = None ):
    # recursive function to calculate all unique combinations of unique values
    # from [set], given combinations of [length].  The result is populated
    # into the 'combinations' list.
    #
    if combinations == None:
        combinations = []
    if candidate == None:
        candidate = []

    for item in set:
        if item in candidate:
            # this item already appears in the current combination somewhere.
            # skip it
            continue

        attempt = copy.deepcopy(candidate)
        attempt.append(item)
        # sorting the subset is what gives us completely unique combinations,
        # so that [1, 2, 3] and [1, 3, 2] will be treated as equals
        attempt.sort()

        if len(attempt) < length:
            # the current attempt at finding a new combination is still too
            # short, so add another item to the end of the set
            # yay recursion!
            find_combinations( length, set, combinations, attempt )
        else:
            # the current combination attempt is the right length.  If it
            # already appears in the list of found combinations then we'll
            # skip it.
            if attempt in combinations:
                continue
            else:
                # otherwise, we append it to the list of found combinations
                # and move on.
                combinations.append(attempt)
                continue
    return len(combinations)

你可以这样使用它。传递'result'是可选的，所以你可以用它来获取可能组合的数量…尽管这样做效率很低(最好通过计算来完成)。

size = 3
set = [1, 2, 3, 4, 5]
result = []

num = find_combinations( size, set, result ) 
print "size %d results in %d sets" % (size, num)
print "result: %s" % (result,)

您应该从测试数据中得到以下输出:

size 3 results in 10 sets
result: [[1, 2, 3], [1, 2, 4], [1, 2, 5], [1, 3, 4], [1, 3, 5], [1, 4, 5], [2, 3, 4], [2, 3, 5], [2, 4, 5], [3, 4, 5]]

如果你的集合是这样的，它也会工作得很好:

set = [
    [ 'vanilla', 'cupcake' ],
    [ 'chocolate', 'pudding' ],
    [ 'vanilla', 'pudding' ],
    [ 'chocolate', 'cookie' ],
    [ 'mint', 'cookie' ]
]

像Andrea Ambu一样用Python写的，但不是硬编码来选择三个。

def combinations(list, k):
    """Choose combinations of list, choosing k elements(no repeats)"""
    if len(list) < k:
        return []
    else:
        seq = [i for i in range(k)]
        while seq:
            print [list[index] for index in seq]
            seq = get_next_combination(len(list), k, seq)

def get_next_combination(num_elements, k, seq):
        index_to_move = find_index_to_move(num_elements, seq)
        if index_to_move == None:
            return None
        else:
            seq[index_to_move] += 1

            #for every element past this sequence, move it down
            for i, elem in enumerate(seq[(index_to_move+1):]):
                seq[i + 1 + index_to_move] = seq[index_to_move] + i + 1

            return seq

def find_index_to_move(num_elements, seq):
        """Tells which index should be moved"""
        for rev_index, elem in enumerate(reversed(seq)):
            if elem < (num_elements - rev_index - 1):
                return len(seq) - rev_index - 1
        return None