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' ]
]

下面是一个方法，它从一个随机长度的字符串中给出指定大小的所有组合。类似于昆玛斯的解，但适用于不同的输入和k。

代码可以更改为换行，即'dab'从输入'abcd' w k=3。

public void run(String data, int howMany){
    choose(data, howMany, new StringBuffer(), 0);
}


//n choose k
private void choose(String data, int k, StringBuffer result, int startIndex){
    if (result.length()==k){
        System.out.println(result.toString());
        return;
    }

    for (int i=startIndex; i<data.length(); i++){
        result.append(data.charAt(i));
        choose(data,k,result, i+1);
        result.setLength(result.length()-1);
    }
}

"abcde"的输出:

ABC abd ace ade BCD bce bde cde

下面是Clojure版本，它使用了我在OCaml实现答案中描述的相同算法:

(defn select
  ([items]
     (select items 0 (inc (count items))))
  ([items n1 n2]
     (reduce concat
             (map #(select % items)
                  (range n1 (inc n2)))))
  ([n items]
     (let [
           lmul (fn [a list-of-lists-of-bs]
                     (map #(cons a %) list-of-lists-of-bs))
           ]
       (if (= n (count items))
         (list items)
         (if (empty? items)
           items
           (concat
            (select n (rest items))
            (lmul (first items) (select (dec n) (rest items))))))))) 

它提供了三种调用方法:

(a)按问题要求，选出n项:

  user=> (count (select 3 "abcdefgh"))
  56

(b) n1至n2个选定项目:

user=> (select '(1 2 3 4) 2 3)
((3 4) (2 4) (2 3) (1 4) (1 3) (1 2) (2 3 4) (1 3 4) (1 2 4) (1 2 3))

(c)在0至所选项目的集合大小之间:

user=> (select '(1 2 3))
(() (3) (2) (1) (2 3) (1 3) (1 2) (1 2 3))

赶时髦，发布另一个解决方案。这是一个通用的Java实现。输入:(int k)是要选择的元素数量，(List<T> List)是要选择的列表。返回一个组合列表(list < list <T>>)。

public static <T> List<List<T>> getCombinations(int k, List<T> list) {
    List<List<T>> combinations = new ArrayList<List<T>>();
    if (k == 0) {
        combinations.add(new ArrayList<T>());
        return combinations;
    }
    for (int i = 0; i < list.size(); i++) {
        T element = list.get(i);
        List<T> rest = getSublist(list, i+1);
        for (List<T> previous : getCombinations(k-1, rest)) {
            previous.add(element);
            combinations.add(previous);
        }
    }
    return combinations;
}

public static <T> List<T> getSublist(List<T> list, int i) {
    List<T> sublist = new ArrayList<T>();
    for (int j = i; j < list.size(); j++) {
        sublist.add(list.get(j));
    }
    return sublist;
}

用c#的另一个解决方案:

 static List<List<T>> GetCombinations<T>(List<T> originalItems, int combinationLength)
    {
        if (combinationLength < 1)
        {
            return null;
        }

        return CreateCombinations<T>(new List<T>(), 0, combinationLength, originalItems);
    }

 static List<List<T>> CreateCombinations<T>(List<T> initialCombination, int startIndex, int length, List<T> originalItems)
    {
        List<List<T>> combinations = new List<List<T>>();
        for (int i = startIndex; i < originalItems.Count - length + 1; i++)
        {
            List<T> newCombination = new List<T>(initialCombination);
            newCombination.Add(originalItems[i]);
            if (length > 1)
            {
                List<List<T>> newCombinations = CreateCombinations(newCombination, i + 1, length - 1, originalItems);
                combinations.AddRange(newCombinations);
            }
            else
            {
                combinations.Add(newCombination);
            }
        }

        return combinations;
    }

用法示例:

   List<char> initialArray = new List<char>() { 'a','b','c','d'};
   int combinationLength = 3;
   List<List<char>> combinations = GetCombinations(initialArray, combinationLength);

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);
    }
}