Word Weight.ipynb

{
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   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('A',)\n",
      "('B',)\n",
      "('C',)\n",
      "('D',)\n",
      "('A', 'B')\n",
      "('A', 'C')\n",
      "('A', 'D')\n",
      "('B', 'C')\n",
      "('B', 'D')\n",
      "('C', 'D')\n",
      "('A', 'B', 'C')\n",
      "('A', 'B', 'D')\n",
      "('A', 'C', 'D')\n",
      "('B', 'C', 'D')\n",
      "('A', 'B', 'C', 'D')\n"
     ]
    }
   ],
   "source": [
    "import itertools\n",
    "\n",
    "s = 'ABCD'\n",
    "for l in range(1, len(s) + 1):\n",
    "    for c in itertools.combinations(s, l):\n",
    "        print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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