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' ]
]

作为迭代器对象实现的MetaTrader MQL4非常快速的组合。

代码很容易理解。

我对很多算法进行了基准测试，这个算法真的非常快——大约比大多数next_combination()函数快3倍。

class CombinationsIterator { private: int input_array[]; // 1 2 3 4 5 int index_array[]; // i j k int m_elements; // N int m_indices; // K public: CombinationsIterator(int &src_data[], int k) { m_indices = k; m_elements = ArraySize(src_data); ArrayCopy(input_array, src_data); ArrayResize(index_array, m_indices); // create initial combination (0..k-1) for (int i = 0; i < m_indices; i++) { index_array[i] = i; } } // https://stackoverflow.com/questions/5076695 // bool next_combination(int &item[], int k, int N) bool advance() { int N = m_elements; for (int i = m_indices - 1; i >= 0; --i) { if (index_array[i] < --N) { ++index_array[i]; for (int j = i + 1; j < m_indices; ++j) { index_array[j] = index_array[j - 1] + 1; } return true; } } return false; } void getItems(int &items[]) { // fill items[] from input array for (int i = 0; i < m_indices; i++) { items[i] = input_array[index_array[i]]; } } };

测试上述迭代器类的驱动程序:

//+------------------------------------------------------------------+ //| | //+------------------------------------------------------------------+ // driver program to test above class #define N 5 #define K 3 void OnStart() { int myset[N] = {1, 2, 3, 4, 5}; int items[K]; CombinationsIterator comboIt(myset, K); do { comboIt.getItems(items); printf("%s", ArrayToString(items)); } while (comboIt.advance()); }

输出: 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

为此，我在SQL Server 2005中创建了一个解决方案，并将其发布在我的网站上:http://www.jessemclain.com/downloads/code/sql/fn_GetMChooseNCombos.sql.htm

下面是一个例子来说明用法:

SELECT * FROM dbo.fn_GetMChooseNCombos('ABCD', 2, '')

结果:

Word
----
AB
AC
AD
BC
BD
CD

(6 row(s) affected)

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]);
        }
    }
}

我可以给出这个问题的递归Python解决方案吗?

def choose_iter(elements, length):
    for i in xrange(len(elements)):
        if length == 1:
            yield (elements[i],)
        else:
            for next in choose_iter(elements[i+1:], length-1):
                yield (elements[i],) + next
def choose(l, k):
    return list(choose_iter(l, k))

使用示例:

>>> len(list(choose_iter("abcdefgh",3)))
56

我喜欢它的简洁。

这个答案怎么样……这将打印所有长度为3的组合…它可以推广到任何长度… 工作代码…

#include<iostream>
#include<string>
using namespace std;

void combination(string a,string dest){
int l = dest.length();
if(a.empty() && l  == 3 ){
 cout<<dest<<endl;}
else{
  if(!a.empty() && dest.length() < 3 ){
     combination(a.substr(1,a.length()),dest+a[0]);}
  if(!a.empty() && dest.length() <= 3 ){
      combination(a.substr(1,a.length()),dest);}
 }

 }

 int main(){
 string demo("abcd");
 combination(demo,"");
 return 0;
 }