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]

如果你可以使用SQL语法——比如，如果你使用LINQ访问一个结构或数组的字段，或者直接访问一个数据库，其中有一个名为“Alphabet”的表，只有一个字符字段“Letter”，你可以适应以下代码:

SELECT A.Letter, B.Letter, C.Letter
FROM Alphabet AS A, Alphabet AS B, Alphabet AS C
WHERE A.Letter<>B.Letter AND A.Letter<>C.Letter AND B.Letter<>C.Letter
AND A.Letter<B.Letter AND B.Letter<C.Letter

这将返回所有3个字母的组合，不管你在表格“字母表”中有多少个字母(它可以是3,8,10,27等)。

如果你想要的是所有的排列，而不是组合(也就是说，你想要“ACB”和“ABC”被视为不同的，而不是只出现一次)，只需删除最后一行(and一行)，就完成了。

Post-Edit:重新阅读问题后，我意识到需要的是通用算法，而不仅仅是选择3个项目的特定算法。Adam Hughes的答案是完整的，不幸的是我还不能投票。这个答案很简单，但只适用于你想要三样东西的时候。

假设你的字母数组是这样的:"ABCDEFGH"。你有三个下标(i, j, k)来表示你要用哪个字母来表示当前单词。

A B C D E F G H
^ ^ ^
i j k

首先你改变k，所以下一步看起来像这样:

A B C D E F G H
^ ^   ^
i j   k

如果你到达终点，你继续改变j和k。

A B C D E F G H
^   ^ ^
i   j k

A B C D E F G H
^   ^   ^
i   j   k

一旦j达到G, i也开始变化。

A B C D E F G H
  ^ ^ ^
  i j k

A B C D E F G H
  ^ ^   ^
  i j   k
...

用代码写出来是这样的

void print_combinations(const char *string)
{
    int i, j, k;
    int len = strlen(string);

    for (i = 0; i < len - 2; i++)
    {
        for (j = i + 1; j < len - 1; j++)
        {
            for (k = j + 1; k < len; k++)
                printf("%c%c%c\n", string[i], string[j], string[k]);
        }
    }
}

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' ]
]

下面是我最近用Java写的一段代码，它计算并返回从“outOf”元素中“num”元素的所有组合。

// author: Sourabh Bhat (heySourabh@gmail.com)

public class Testing
{
    public static void main(String[] args)
    {

// Test case num = 5, outOf = 8.

        int num = 5;
        int outOf = 8;
        int[][] combinations = getCombinations(num, outOf);
        for (int i = 0; i < combinations.length; i++)
        {
            for (int j = 0; j < combinations[i].length; j++)
            {
                System.out.print(combinations[i][j] + " ");
            }
            System.out.println();
        }
    }

    private static int[][] getCombinations(int num, int outOf)
    {
        int possibilities = get_nCr(outOf, num);
        int[][] combinations = new int[possibilities][num];
        int arrayPointer = 0;

        int[] counter = new int[num];

        for (int i = 0; i < num; i++)
        {
            counter[i] = i;
        }
        breakLoop: while (true)
        {
            // Initializing part
            for (int i = 1; i < num; i++)
            {
                if (counter[i] >= outOf - (num - 1 - i))
                    counter[i] = counter[i - 1] + 1;
            }

            // Testing part
            for (int i = 0; i < num; i++)
            {
                if (counter[i] < outOf)
                {
                    continue;
                } else
                {
                    break breakLoop;
                }
            }

            // Innermost part
            combinations[arrayPointer] = counter.clone();
            arrayPointer++;

            // Incrementing part
            counter[num - 1]++;
            for (int i = num - 1; i >= 1; i--)
            {
                if (counter[i] >= outOf - (num - 1 - i))
                    counter[i - 1]++;
            }
        }

        return combinations;
    }

    private static int get_nCr(int n, int r)
    {
        if(r > n)
        {
            throw new ArithmeticException("r is greater then n");
        }
        long numerator = 1;
        long denominator = 1;
        for (int i = n; i >= r + 1; i--)
        {
            numerator *= i;
        }
        for (int i = 2; i <= n - r; i++)
        {
            denominator *= i;
        }

        return (int) (numerator / denominator);
    }
}

在c#中:

public static IEnumerable<IEnumerable<T>> Combinations<T>(this IEnumerable<T> elements, int k)
{
  return k == 0 ? new[] { new T[0] } :
    elements.SelectMany((e, i) =>
      elements.Skip(i + 1).Combinations(k - 1).Select(c => (new[] {e}).Concat(c)));
}

用法:

var result = Combinations(new[] { 1, 2, 3, 4, 5 }, 3);

结果:

123
124
125
134
135
145
234
235
245
345