下面是一个使用宏的Lisp方法。这适用于Common Lisp，也适用于其他Lisp方言。

下面的代码创建了'n'个嵌套循环，并为列表lst中的'n'个元素的每个组合执行任意代码块(存储在body变量中)。变量var指向一个包含用于循环的变量的列表。

(defmacro do-combinations ((var lst num) &body body)
  (loop with syms = (loop repeat num collect (gensym))
        for i on syms
        for k = `(loop for ,(car i) on (cdr ,(cadr i))
                         do (let ((,var (list ,@(reverse syms)))) (progn ,@body)))
                then `(loop for ,(car i) on ,(if (cadr i) `(cdr ,(cadr i)) lst) do ,k)
        finally (return k)))

让我们看看…

(macroexpand-1 '(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p))))

(LOOP FOR #:G3217 ON '(1 2 3 4 5 6 7) DO
 (LOOP FOR #:G3216 ON (CDR #:G3217) DO
  (LOOP FOR #:G3215 ON (CDR #:G3216) DO
   (LOOP FOR #:G3214 ON (CDR #:G3215) DO
    (LET ((P (LIST #:G3217 #:G3216 #:G3215 #:G3214)))
     (PROGN (PPRINT (MAPCAR #'CAR P))))))))

(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p)))

(1 2 3 4)
(1 2 3 5)
(1 2 3 6)
...

由于默认情况下不存储组合，因此存储空间保持在最小值。选择主体代码而不是存储所有结果的可能性也提供了更大的灵活性。

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。

你可以使用Asif算法来生成所有可能的组合。这可能是最简单和最有效的方法。你可以在这里查看媒体文章。

让我们看看JavaScript中的实现。

function Combinations( arr, r ) {
    // To avoid object referencing, cloning the array.
    arr = arr && arr.slice() || [];

    var len = arr.length;

    if( !len || r > len || !r )
        return [ [] ];
    else if( r === len ) 
        return [ arr ];

    if( r === len ) return arr.reduce( ( x, v ) => {
        x.push( [ v ] );

        return x;
    }, [] );

    var head = arr.shift();

    return Combinations( arr, r - 1 ).map( x => {
        x.unshift( head );

        return x;
    } ).concat( Combinations( arr, r ) );
}

// Now do your stuff.

console.log( Combinations( [ 'a', 'b', 'c', 'd', 'e' ], 3 ) );

也许我错过了重点(你需要的是算法，而不是现成的解决方案)，但看起来scala已经开箱即用了(现在):

def combis(str:String, k:Int):Array[String] = {
  str.combinations(k).toArray 
}

使用这样的方法:

  println(combis("abcd",2).toList)

会产生:

  List(ab, ac, ad, bc, bd, cd)

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))