import pandas as pd
import itertools
import numpy as np

def combinations_permuted(n_elm):
    items = list(range(0,n_elm+1,1))
    combinations = pd.DataFrame(list(filter(lambda x: np.sum(x)==n_elm,list(itertools.combinations_with_replacement(items, n_elm)))))
    comb_permuted = pd.DataFrame()
    for index, combination in combinations.iterrows():
        comb_permuted=comb_permuted.append(list(filter(lambda x: np.sum(x)==n_elm,list(itertools.permutations(combination.tolist(), n_elm)))))

    return(comb_permuted.drop_duplicates().as_matrix())

array([[0, 0, 3],
       [0, 3, 0],
       [3, 0, 0],
       [0, 1, 2],
       [0, 2, 1],
       [1, 0, 2],
       [1, 2, 0],
       [2, 0, 1],
       [2, 1, 0],
       [1, 1, 1]], dtype=int64)

def combinations_permuted(n_elm):

items = list(range(0,n_elm+1,1))

combinations = pd.DataFrame(list(filter(lambda x: np.sum(x)==n_elm,list(itertools.combinations_with_replacement(items, n_elm)))))
    comb_permuted = pd.DataFrame()
    for index, combination in combinations.iterrows():
        comb_permuted=comb_permuted.append(list(filter(lambda x: np.sum(x)==n_elm,list(itertools.permutations(combination.tolist(), n_elm)))))

    return(comb_permuted.drop_duplicates().as_matrix())

def combinations_recursive_inner(n, buf, gaps, sum, accum):
  if gaps == 0:
    accum.append(list(buf))
  else:
    for x in range(0, n+1):
      if sum + x + (gaps - 1) * n < n: continue
      if sum + x > n: break
      combinations_recursive_inner(n, buf + [x], gaps - 1, sum + x, accum)

def combinations_recursive(n):
  accum = []
  combinations_recursive_inner(n, [], n, 0, accum)
  return pd.DataFrame(accum).as_matrix()