{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "951180ec",
   "metadata": {},
   "source": [
    "# Honeycomb letter puzzle\n",
    "Solving the puzzle as posted on [FiveThirtyEight](https://fivethirtyeight.com/features/can-you-solve-the-vexing-vexillology/), also solved by [David Robinson](http://varianceexplained.org/r/honeycomb-puzzle/).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6f6fa3e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import string\n",
    "import collections\n",
    "from dataclasses import dataclass\n",
    "import itertools\n",
    "import ctypes\n",
    "import cProfile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "88f00e4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "172820"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open('enable1.txt') as f:\n",
    "    words = [line.strip() for line in f]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1e75fba2",
   "metadata": {},
   "outputs": [],
   "source": [
    "words = set(w for w in words \n",
    "            if len(w) >= 4\n",
    "            if len(frozenset(w)) <= 7\n",
    "            if 's' not in w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e1f9b35e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21661"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_sets = collections.defaultdict(set)\n",
    "for w in words:\n",
    "    letters = frozenset(w)\n",
    "    word_sets[letters].add(w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "95dc0eed-c759-481e-8598-9b861e3def8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def encode(letters):\n",
    "    encoded = 0\n",
    "    for l in string.ascii_lowercase:\n",
    "        encoded <<= 1\n",
    "        if l in letters:\n",
    "            encoded |= 1\n",
    "    return encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "53d9ae67-a5b5-4d01-9e69-930acca023bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def decode(letter_bits):\n",
    "    letters = set()\n",
    "    for l in string.ascii_lowercase:\n",
    "        e = encode(l)\n",
    "        if (e & letter_bits):\n",
    "            letters.add(l)\n",
    "    return letters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ab295a0a-6cb0-4f24-b57b-cb9f99517067",
   "metadata": {},
   "outputs": [],
   "source": [
    "def subset(this, that):\n",
    "    return this & that == this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "267130ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "@dataclass(frozen=True, init=False)\n",
    "class Honeycomb():\n",
    "    mandatory: int\n",
    "    letters: int\n",
    "    \n",
    "    def __init__(self, mandatory, letters):\n",
    "        object.__setattr__(self, 'mandatory', encode(mandatory))\n",
    "        object.__setattr__(self, 'letters', encode(letters))\n",
    "            \n",
    "    def __repr__(self):\n",
    "        return f'{\"\".join(decode(self.mandatory))}|{\"\".join(sorted(decode(self.letters) - set(decode(self.mandatory))))}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bb848e88",
   "metadata": {},
   "outputs": [],
   "source": [
    "def present(target, honeycomb):\n",
    "    return (subset(honeycomb.mandatory, target)\n",
    "           and subset(target, honeycomb.letters))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3c6f212e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def score(present_set):\n",
    "    score = 0\n",
    "    for w in word_sets[present_set]:\n",
    "        if len(w) == 4:\n",
    "            score += 1\n",
    "        else:\n",
    "            score += len(w)\n",
    "    if len(present_set) == 7:\n",
    "        score += len(word_sets[present_set]) * 7\n",
    "    return score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "979d9ed5",
   "metadata": {},
   "outputs": [],
   "source": [
    "scored_sets = {s: score(s) for s in word_sets}\n",
    "encoded_scored_sets = {encode(s): scored_sets[s] for s in scored_sets}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "78d423a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def raw_score_honeycomb(honeycomb):\n",
    "    return sum(sc for letters, sc in scored_sets.items() \n",
    "               # if honeycomb.mandatory in letters\n",
    "               # if letters.issubset(honeycomb.letters)\n",
    "               if present(letters, honeycomb)\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "eb0d2af1-437b-4be5-8736-0a18022e9de2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def score_honeycomb(honeycomb):\n",
    "    return sum(sc for letters, sc in encoded_scored_sets.items() \n",
    "               # if honeycomb.mandatory in letters\n",
    "               # if letters.issubset(honeycomb.letters)\n",
    "               if present(letters, honeycomb)\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "febee1c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pangram sets: 7986\n"
     ]
    }
   ],
   "source": [
    "pangram_sets = [s for s in word_sets.keys() if len(s) == 7 if 's' not in s]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "54a06bdf",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('pangaram_words.txt', 'w') as f:\n",
    "    for s in pangram_sets:\n",
    "        for w in word_sets[s]:\n",
    "            f.write(f'{w}\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c0b0807c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "55902 honeycombs\n"
     ]
    }
   ],
   "source": [
    "# ps_honeycombs = []\n",
    "\n",
    "# for ps in pangram_sets:\n",
    "#     for mand in ps:\n",
    "#         ps_honeycombs.append(Honeycomb(mandatory=mand, letters=ps))\n",
    "\n",
    "ps_honeycombs = [Honeycomb(mandatory=mand, letters=ps) \n",
    "                 for ps in pangram_sets\n",
    "                 for mand in ps]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "914fece8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "partitioned_scored_sets = {encode(l): {s: encoded_scored_sets[s] \n",
    "                               for s in encoded_scored_sets \n",
    "                               if subset(encode(l), s)}\n",
    "                           for l in string.ascii_lowercase}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "f1454ccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def partitioned_score_honeycomb(honeycomb):\n",
    "    return sum(sc for letters, sc in partitioned_scored_sets[honeycomb.mandatory].items() \n",
    "               if subset(letters, honeycomb.letters)\n",
    "              )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "7380dbd6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r|aegint 3898\n",
      "r|aegint 3898\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_1590851/2427168464.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_cell_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'timeit'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'best_honyecomb = max(ps_honeycombs, key=partitioned_score_honeycomb)\\nprint(best_honyecomb, partitioned_score_honeycomb(best_honyecomb))\\n'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_cell_magic\u001b[0;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[1;32m   2401\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2402\u001b[0m                 \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmagic_arg_s\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2403\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2404\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2405\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/decorator.py\u001b[0m in \u001b[0;36mfun\u001b[0;34m(*args, **kw)\u001b[0m\n\u001b[1;32m    230\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mkwsyntax\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    231\u001b[0m                 \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 232\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mcaller\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mextras\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    233\u001b[0m     \u001b[0mfun\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    234\u001b[0m     \u001b[0mfun\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/IPython/core/magic.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(f, *a, **k)\u001b[0m\n\u001b[1;32m    185\u001b[0m     \u001b[0;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    186\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m         \u001b[0mcall\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    189\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/IPython/core/magics/execution.py\u001b[0m in \u001b[0;36mtimeit\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n\u001b[1;32m   1171\u001b[0m                     \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1172\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1173\u001b[0;31m         \u001b[0mall_runs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtimer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1174\u001b[0m         \u001b[0mbest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_runs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1175\u001b[0m         \u001b[0mworst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_runs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.8/timeit.py\u001b[0m in \u001b[0;36mrepeat\u001b[0;34m(self, repeat, number)\u001b[0m\n\u001b[1;32m    203\u001b[0m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    204\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 205\u001b[0;31m             \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtimeit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    206\u001b[0m             \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    207\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/IPython/core/magics/execution.py\u001b[0m in \u001b[0;36mtimeit\u001b[0;34m(self, number)\u001b[0m\n\u001b[1;32m    167\u001b[0m         \u001b[0mgc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    168\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 169\u001b[0;31m             \u001b[0mtiming\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtimer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    170\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    171\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mgcold\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<magic-timeit>\u001b[0m in \u001b[0;36minner\u001b[0;34m(_it, _timer)\u001b[0m\n",
      "\u001b[0;32m/tmp/ipykernel_1590851/3736129931.py\u001b[0m in \u001b[0;36mpartitioned_score_honeycomb\u001b[0;34m(honeycomb)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpartitioned_score_honeycomb\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhoneycomb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     return sum(sc for letters, sc in partitioned_scored_sets[honeycomb.mandatory].items() \n\u001b[0m\u001b[1;32m      3\u001b[0m                \u001b[0;32mif\u001b[0m \u001b[0msubset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mletters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhoneycomb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mletters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m               )\n",
      "\u001b[0;32m/tmp/ipykernel_1590851/3736129931.py\u001b[0m in \u001b[0;36m<genexpr>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpartitioned_score_honeycomb\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhoneycomb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m     return sum(sc for letters, sc in partitioned_scored_sets[honeycomb.mandatory].items() \n\u001b[0;32m----> 3\u001b[0;31m                \u001b[0;32mif\u001b[0m \u001b[0msubset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mletters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhoneycomb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mletters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m               )\n",
      "\u001b[0;32m/tmp/ipykernel_1590851/3073138769.py\u001b[0m in \u001b[0;36msubset\u001b[0;34m(this, that)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msubset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mthis\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0mthat\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mthis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# %%timeit\n",
    "# best_honyecomb = max(ps_honeycombs, key=partitioned_score_honeycomb)\n",
    "# print(best_honyecomb, partitioned_score_honeycomb(best_honyecomb))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ecd0647-11df-4b5b-a487-cb30cfa080c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%timeit\n",
    "best_honyecomb = max(ps_honeycombs, key=score_honeycomb)\n",
    "print(best_honyecomb, score_honeycomb(best_honyecomb))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e4173b4-26a9-4198-b572-d57db321fe94",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# cProfile.run('max(ps_honeycombs, key=score_honeycomb)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a9070b7-a866-499e-a910-82337ecbd052",
   "metadata": {},
   "outputs": [],
   "source": [
    "# cProfile.run('max(ps_honeycombs, key=partitioned_score_honeycomb)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a77ce9b1-d5d8-4c8f-8666-5840af23c265",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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