crosswords/data/data_tests.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import re\n",
    "import tqdm\n",
    "from IPython.display import Markdown"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## prepare raw wikiextract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%bash\n",
    "cat english.words| jq -s . > english.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('english.json', 'r') as f:\n",
    "    english_vocab_db = json.load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## helper functions to filter senses, synonyms and antonyms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_senses(senses_list, word):\n",
    "    filtered_senses = []\n",
    "    for entry in senses_list:\n",
    "        if 'glosses' in entry:\n",
    "            glosses = entry['glosses']\n",
    "            for gloss_entry in glosses:\n",
    "                for gloss in gloss_entry.split(';'):\n",
    "                    s = re.sub('\\s+', ' ', re.sub(\"[\\(\\[].*?[\\)\\]]\", \"\", gloss).replace(\".\", \"\")).strip()\n",
    "                    if len(s) > 0 and word not in s:\n",
    "                        filtered_senses.append(s)\n",
    "    return filtered_senses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_synonyms(synonyms_list):\n",
    "    filtered_synonyms = []\n",
    "    for entry in synonyms_list:\n",
    "        if 'word' in entry:\n",
    "            filtered_synonyms.append(entry['word'])\n",
    "    return filtered_synonyms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_antonyms(antonym_list):\n",
    "    filtered_antonyms = []\n",
    "    for entry in antonym_list:\n",
    "        if 'word' in entry:\n",
    "            filtered_antonyms.append(entry['word'])\n",
    "    return filtered_antonyms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_wiktionary_item(item, db):\n",
    "    item = {}\n",
    "    if 'word' not in item.keys():\n",
    "        return\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## build a dictionary_database from the raw extract\n",
    "using words as keys, enumerate those keys (e.g. `house`, `house1`, `house2` etc.) on duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1023195/1023195 [00:00<00:00, 1368488.50it/s]\n"
     ]
    }
   ],
   "source": [
    "dictionary_database = {}\n",
    "for item in tqdm.tqdm(english_vocab_db):\n",
    "    if 'word' in item:\n",
    "        word = item['word']\n",
    "        i = 0\n",
    "        while word in dictionary_database:\n",
    "            i += 1\n",
    "            word = f\"{item['word']}{i}\"\n",
    "        dictionary_database[word] = item\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "class NoDataException(Exception):\n",
    "    pass\n",
    "\n",
    "def get_attribute(word:str, attr:str, db = dictionary_database):\n",
    "    if word not in db:\n",
    "        raise NoDataException\n",
    "    item = db[word]\n",
    "    if attr not in item:\n",
    "        raise NoDataException\n",
    "    return item[attr]\n",
    "\n",
    "def get_senses(word: str):\n",
    "    \n",
    "    senses = get_attribute(word, 'senses')\n",
    "    \n",
    "    return filter_senses(senses, word)\n",
    "\n",
    "def get_synonyms(word: str):\n",
    "    syns = get_attribute(word, 'synonyms')\n",
    "    \n",
    "    return filter_synonyms(syns)\n",
    "\n",
    "def get_antonyms(word: str):\n",
    "    ants = get_attribute(word, 'antonyms')\n",
    "    \n",
    "    return filter_antonyms(ants)\n",
    "\n",
    "def display_info(word: str):\n",
    "    \n",
    "    if word not in dictionary_database:\n",
    "        raise NoDataException\n",
    "    \n",
    "    try:\n",
    "        senses = get_senses(word)\n",
    "    except NoDataException:\n",
    "        senses = []\n",
    "    \n",
    "    try:\n",
    "        synonyms = get_synonyms(word)\n",
    "    except NoDataException:\n",
    "        synonyms = []\n",
    "    \n",
    "    try:\n",
    "        antonyms = get_antonyms(word)\n",
    "    except NoDataException:\n",
    "        antonyms = []\n",
    "        \n",
    "    senses_str = '\\n'.join([f\"* {sense}\" for sense in senses])\n",
    "    \n",
    "    synonyms_str = '\\n'.join([f\"* {syn}\" for syn in synonyms])\n",
    "    \n",
    "    antonyms_str = '\\n'.join([f\"* {ant}\" for ant in antonyms])\n",
    "    \n",
    "    markdown_string = f\"\"\"\n",
    "## {word}\n",
    "\n",
    "### Senses:\n",
    "\n",
    "{senses_str}\n",
    "\n",
    "### Synonyms:\n",
    "\n",
    "{synonyms_str}\n",
    "\n",
    "### Antonyms:\n",
    "\n",
    "{antonyms_str}\n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    return Markdown(markdown_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1023195/1023195 [00:08<00:00, 125917.77it/s]\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "list_words = []\n",
    "for word in tqdm.tqdm(dictionary_database.keys()):\n",
    "    item = dictionary_database[word]\n",
    "    try:\n",
    "        senses = get_senses(word)\n",
    "        if len(senses) > 4:\n",
    "            list_words.append(word)\n",
    "            continue\n",
    "        try:\n",
    "            if len(get_antonyms(word)) >= 1:\n",
    "                list_words.append(word)\n",
    "                continue\n",
    "        except NoDataException:\n",
    "            if len(get_synonyms(word)) >= 1:\n",
    "                list_words.append(word)\n",
    "            \n",
    "    except NoDataException:\n",
    "        pass\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "## cockmonger\n",
       "\n",
       "### Senses:\n",
       "\n",
       "* A frequent consumer of cocks\n",
       "* A procurer of cocks\n",
       "* A person with a large penis\n",
       "\n",
       "### Synonyms:\n",
       "\n",
       "\n",
       "\n",
       "### Antonyms:\n",
       "\n",
       "\n",
       "    \n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(display_info(\"cockmonger\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "## algorithm to build a grid of words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 68842/68842 [00:01<00:00, 50914.78it/s]\n"
     ]
    }
   ],
   "source": [
    "## store an optimized library version for production\n",
    "optimized_lib = {}\n",
    "for word in tqdm.tqdm(list_words):\n",
    "    item = {}\n",
    "    senses = None\n",
    "    antonyms = None\n",
    "    synonyms = None\n",
    "    try:\n",
    "        senses = get_senses(word)\n",
    "    except:\n",
    "        pass\n",
    "    try:\n",
    "        synonyms = get_synonyms(word)\n",
    "    except:\n",
    "        pass\n",
    "    try:\n",
    "        antonyms = get_antonyms(word)\n",
    "    except:\n",
    "        pass\n",
    "    \n",
    "    item['senses'] = senses\n",
    "    item['antonyms'] = antonyms\n",
    "    item['synonyms'] = synonyms\n",
    "    item['word'] = dictionary_database[word]['word']\n",
    "    optimized_lib[word] = item"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"en.json\",'w') as f:\n",
    "    json.dump(optimized_lib, f, indent = 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[0;31mSignature:\u001b[0m\n",
       "\u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mfp\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m*\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mskipkeys\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mensure_ascii\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mcheck_circular\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mallow_nan\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mcls\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mseparators\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mdefault\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0msort_keys\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\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;31mDocstring:\u001b[0m\n",
       "Serialize ``obj`` as a JSON formatted stream to ``fp`` (a\n",
       "``.write()``-supporting file-like object).\n",
       "\n",
       "If ``skipkeys`` is true then ``dict`` keys that are not basic types\n",
       "(``str``, ``int``, ``float``, ``bool``, ``None``) will be skipped\n",
       "instead of raising a ``TypeError``.\n",
       "\n",
       "If ``ensure_ascii`` is false, then the strings written to ``fp`` can\n",
       "contain non-ASCII characters if they appear in strings contained in\n",
       "``obj``. Otherwise, all such characters are escaped in JSON strings.\n",
       "\n",
       "If ``check_circular`` is false, then the circular reference check\n",
       "for container types will be skipped and a circular reference will\n",
       "result in an ``OverflowError`` (or worse).\n",
       "\n",
       "If ``allow_nan`` is false, then it will be a ``ValueError`` to\n",
       "serialize out of range ``float`` values (``nan``, ``inf``, ``-inf``)\n",
       "in strict compliance of the JSON specification, instead of using the\n",
       "JavaScript equivalents (``NaN``, ``Infinity``, ``-Infinity``).\n",
       "\n",
       "If ``indent`` is a non-negative integer, then JSON array elements and\n",
       "object members will be pretty-printed with that indent level. An indent\n",
       "level of 0 will only insert newlines. ``None`` is the most compact\n",
       "representation.\n",
       "\n",
       "If specified, ``separators`` should be an ``(item_separator, key_separator)``\n",
       "tuple.  The default is ``(', ', ': ')`` if *indent* is ``None`` and\n",
       "``(',', ': ')`` otherwise.  To get the most compact JSON representation,\n",
       "you should specify ``(',', ':')`` to eliminate whitespace.\n",
       "\n",
       "``default(obj)`` is a function that should return a serializable version\n",
       "of obj or raise TypeError. The default simply raises TypeError.\n",
       "\n",
       "If *sort_keys* is true (default: ``False``), then the output of\n",
       "dictionaries will be sorted by key.\n",
       "\n",
       "To use a custom ``JSONEncoder`` subclass (e.g. one that overrides the\n",
       "``.default()`` method to serialize additional types), specify it with\n",
       "the ``cls`` kwarg; otherwise ``JSONEncoder`` is used.\n",
       "\u001b[0;31mFile:\u001b[0m      /usr/lib/python3.9/json/__init__.py\n",
       "\u001b[0;31mType:\u001b[0m      function\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?json.dump"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import random\n",
    "from string import digits\n",
    "\n",
    "class WordInfo(object):\n",
    "    def __init__(self, word:str, y:int, x:int, is_vertical: bool, database=dictionary_database):\n",
    "        self._dictionary_database = dictionary_database\n",
    "        self._y = y\n",
    "        self._x = x\n",
    "        self._word = word\n",
    "        self._hint = None\n",
    "        self._is_vertical = is_vertical\n",
    "        \n",
    "        self.choose_info()\n",
    "    \n",
    "    def get_best_antonym(self) -> str:\n",
    "        antonyms = get_antonyms(self._word)\n",
    "        return random.choice(antonyms)\n",
    "    \n",
    "    def get_best_synonym(self) -> str:\n",
    "        synonyms = get_synonyms(self._word)\n",
    "        return random.choice(synonyms)\n",
    "    \n",
    "    def get_best_sense(self) -> str:\n",
    "        senses = get_senses(self._word)\n",
    "        return random.choice(senses)\n",
    "        \n",
    "    def choose_info(self):\n",
    "        # first choose antonyms, then synonyms, then senses\n",
    "        \n",
    "        try:\n",
    "            self._hint = f\"opposite of {self.get_best_antonym()}\"\n",
    "        except NoDataException:\n",
    "            pass\n",
    "        \n",
    "        try:\n",
    "            self._hint = f\"other word for {self.get_best_synonym()}\"\n",
    "        except NoDataException:\n",
    "            pass\n",
    "        \n",
    "        self._hint = self.get_best_sense()\n",
    "    \n",
    "    def get_hint(self) -> str:\n",
    "        return self._hint\n",
    "    \n",
    "    def get_hint_location(self):\n",
    "        x = self._x if self._is_vertical else self._x - 1\n",
    "        y = self._y if self._is_vertical else self._y - 1\n",
    "        return (y, x)\n",
    "    \n",
    "    def is_vertical(self):\n",
    "        return self._is_vertical\n",
    "\n",
    "def create_word_grid(w: int, h: int, word_list = list_words, target_density = 0.5):\n",
    "    grid = np.full(shape=(h,w), dtype=np.unicode, fill_value = ' ')\n",
    "    \n",
    "    locations = {}\n",
    "    \n",
    "    word_hints = {}\n",
    "    \n",
    "    def store_location(char: str, y: int, x: int):\n",
    "        assert len(char) == 1\n",
    "        \n",
    "        if char not in locations:\n",
    "            locations[char] = []\n",
    "        \n",
    "        locations[char].append([y,x])\n",
    "        \n",
    "    remove_digits = str.maketrans('', '', digits)\n",
    "    n_words = len(list_words)\n",
    "    \n",
    "    def get_word(max_length: int, min_length = 0):\n",
    "        assert max_length > 1\n",
    "        \n",
    "        index = random.randint(0,n_words-1)\n",
    "        word = list_words[index][:]\n",
    "        \n",
    "        while len(word) >= max_length or not word.isalnum() or len(word) <= min_length:\n",
    "            index = random.randint(0,n_words-1)\n",
    "            word = list_words[index][:]\n",
    "        \n",
    "        return word\n",
    "            \n",
    "    def normalize_word(word:str):\n",
    "        word = word.translate(remove_digits)\n",
    "        return word.lower()\n",
    "    \n",
    "    def place_word(word:str, y: int, x:int, vertical:bool = False):\n",
    "        normalized_word = normalize_word(word)\n",
    "        n = len(normalized_word)\n",
    "        if vertical:\n",
    "            assert grid.shape[0] - n >= y\n",
    "            for i, char in enumerate(normalized_word):\n",
    "                grid[y + i,x] = char\n",
    "                store_location(char, y+i, x)\n",
    "        else:\n",
    "            assert grid.shape[1] - n >= x\n",
    "            for i, char in enumerate(normalized_word):\n",
    "                grid[y,x + i] = char\n",
    "                store_location(char, y, x+i)\n",
    "        \n",
    "        word_hints[normalized_word] = WordInfo(word, y, x, vertical)\n",
    "        \n",
    "        \n",
    "    \n",
    "    def density():\n",
    "        return 1 - (grid == \" \").sum() / (w * h)\n",
    "    \n",
    "    \n",
    "    \n",
    "    def check_if_fits(word:str, y:int, x:int, vertical:bool):\n",
    "        n = len(word)\n",
    "        if vertical:\n",
    "            \n",
    "            # check if there is space before and after\n",
    "            if y - 1 >= 0 and grid[y - 1, x] != \" \":\n",
    "                return False\n",
    "            if y + n < grid.shape[0] - 1 and grid[y+n,x] != \" \":\n",
    "                return False\n",
    "            \n",
    "            if grid.shape[0] - n < y or y < 0:\n",
    "                #print(\"over board\")\n",
    "                return False\n",
    "            \n",
    "            for i, char in enumerate(word):\n",
    "                char_x = x\n",
    "                char_y = y + i\n",
    "                \n",
    "                if not (grid[char_y, char_x] == \" \" or grid[char_y, char_x] == char):\n",
    "                    #print(\"not matching\")\n",
    "                    return False\n",
    "                \n",
    "                if grid[char_y, char_x] == \" \":\n",
    "                    # check for horizonatal neighbors:\n",
    "                    if char_x - 1 >= 0 and grid[char_y, char_x - 1] != \" \":\n",
    "                        #print(\"3\")\n",
    "                        return False\n",
    "                    if char_x + 1 < grid.shape[1] and grid[char_y, char_x + 1] != \" \":\n",
    "                        #print(\"4\")\n",
    "                        return False\n",
    "        \n",
    "        else:\n",
    "            \n",
    "            # check if there is space before and after\n",
    "            if x - 1 >= 0 and grid[y, x - 1] != \" \":\n",
    "                return False\n",
    "            if x + n < grid.shape[1] - 1 and grid[y,x + n] != \" \":\n",
    "                return False\n",
    "            \n",
    "            if grid.shape[1] - n < x or x < 0:\n",
    "                #print(\"over board\")\n",
    "                return False\n",
    "            \n",
    "            for i, char in enumerate(word):\n",
    "                char_x = x + i\n",
    "                char_y = y\n",
    "                \n",
    "                if not (grid[char_y, char_x] == \" \" or grid[char_y, char_x] == char):\n",
    "                    #print(\"not matching\")\n",
    "                    return False\n",
    "                \n",
    "                if grid[char_y, char_x] == \" \":\n",
    "                    # check for vertical neighbors:\n",
    "                    if char_y - 1 >= 0 and grid[char_y - 1, char_x] != \" \":\n",
    "                        #print(\"1\")\n",
    "                        return False\n",
    "                    if char_y + 1 < grid.shape[0] and grid[char_y + 1, char_x] != \" \":\n",
    "                        #print(\"2\")\n",
    "                        return False\n",
    "        \n",
    "        return True\n",
    "        \n",
    "    \n",
    "    def get_crossover(word: str):\n",
    "        # returns Tuple of: (y,x, is_vertical?) or None\n",
    "        \n",
    "        shuffled_order = list(range(len(word)))\n",
    "        random.shuffle(shuffled_order)\n",
    "        \n",
    "        for index in shuffled_order:\n",
    "            # check for existing locations\n",
    "            char = word[index]\n",
    "            if char in locations:\n",
    "                char_locations = locations[char]\n",
    "                \n",
    "                for char_loc in char_locations:\n",
    "                    # test vertical\n",
    "                    y = char_loc[0] - index\n",
    "                    x = char_loc[1]\n",
    "                    \n",
    "                    if check_if_fits(word, y, x, vertical=True):\n",
    "                        return (y,x,True)\n",
    "                    \n",
    "                    # test horizontal\n",
    "                    y = char_loc[0]\n",
    "                    x = char_loc[1] - index\n",
    "                    \n",
    "                    if check_if_fits(word, y, x, vertical=False):\n",
    "                        return (y,x,False)\n",
    "        \n",
    "        return None\n",
    "    \n",
    "    min_shape = min(w,h,30)\n",
    "    \n",
    "    # place first word:\n",
    "    first_word = get_word(max_length=min_shape, min_length=min(10,grid.shape[1] - 2))\n",
    "    \n",
    "    # find random place:\n",
    "    x = random.randint(0, grid.shape[1] - len(first_word) - 1)\n",
    "    y = random.randint(0, grid.shape[0] - 1)\n",
    "    \n",
    "    place_word(first_word, y, x, vertical=False)\n",
    "                \n",
    "    i = 0\n",
    "    \n",
    "    \n",
    "    current_density = density()\n",
    "    \n",
    "    while current_density < target_density:\n",
    "        word = get_word(max_length=(1 - current_density ** 0.4) * min_shape,\n",
    "                        min_length=max(min(10, 0.5 * (1 - current_density ** 0.3) * min_shape), 2))\n",
    "        \n",
    "        normalized_word = normalize_word(word)\n",
    "        \n",
    "        if normalized_word in word_hints:\n",
    "            continue\n",
    "        \n",
    "        # check if matching characters exist:\n",
    "        crossover = get_crossover(normalized_word)\n",
    "        \n",
    "        i += 1\n",
    "        if i % 100000 == 0:\n",
    "            print(i)\n",
    "        if i > 100000:\n",
    "            break\n",
    "        \n",
    "        if crossover == None:\n",
    "            current_density = density()\n",
    "            continue\n",
    "        \n",
    "        y,x,is_vertical = crossover\n",
    "        \n",
    "        place_word(word, y,x, is_vertical)\n",
    "        \n",
    "        current_density = density()\n",
    "    \n",
    "    print(i)\n",
    "    return grid, word_hints\n",
    "        \n",
    "        \n",
    "        \n",
    "        \n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name '__file__' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-24-358d5687b810>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0m__file__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name '__file__' is not defined"
     ]
    }
   ],
   "source": [
    "__file__\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "762\n"
     ]
    },
    {
     "data": {
      "text/markdown": [
       "|     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |     |\n",
       "|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|\n",
       "|     |     |     |     |     |**d**|**e**|**n**|**s**|**i**|**t**|**o**|**m**|**e**|**t**|**e**|**r**|     |     |**h**|     |     |**z**|     |     |     |**h**|**a**|**m**|**m**|**e**|**r**|**s**|     |     |**p**|**p**|**l**|     |     |     |     |**d**|     |**h**|**a**|**w**|**k**|\n",
       "|     |     |     |**v**|     |     |     |**o**|     |     |     |     |     |**x**|     |     |**m**|     |**w**|**o**|**r**|**k**|**e**|**r**|**y**|     |     |**u**|     |     |     |     |     |     |**d**|     |**e**|     |**t**|**e**|**n**|**o**|**u**|**s**|     |**m**|     |     |\n",
       "|     |     |**m**|**a**|**s**|**l**|**e**|**n**|**i**|**t**|**s**|**a**|     |     |     |     |     |     |     |**i**|     |     |**k**|     |     |     |**f**|**r**|**e**|**e**|     |**c**|**u**|**m**|**m**|**e**|**r**|     |     |**c**|     |     |**f**|     |     |**i**|     |**m**|\n",
       "|     |     |     |**g**|     |     |     |**i**|     |**h**|     |     |**c**|     |     |**p**|**l**|**e**|**c**|**t**|**i**|**l**|**e**|     |     |**d**|     |**e**|     |     |**p**|     |**n**|     |**v**|     |**u**|     |**s**|**t**|**a**|**m**|**f**|**o**|**r**|**d**|     |**r**|\n",
       "|     |     |     |**u**|**l**|**c**|**e**|**r**|**o**|**u**|**s**|     |**o**|     |**i**|     |**i**|     |**o**|     |     |     |     |**c**|     |**a**|**j**|**o**|**g**|     |**a**|     |**j**|     |     |     |**s**|     |     |**h**|     |     |     |     |     |**s**|**e**|**t**|\n",
       "|     |**d**|**u**|**e**|     |     |     |**r**|     |**s**|     |**a**|**m**|**e**|**n**|     |**q**|     |**i**|     |**p**|**i**|**l**|**l**|**a**|**r**|     |**l**|     |     |**n**|     |**o**|     |     |**r**|**a**|**d**|**c**|**l**|**i**|**f**|**f**|**e**|     |**t**|     |     |\n",
       "|     |**e**|     |     |     |**b**|     |**i**|     |     |**h**|     |**m**|     |**c**|     |**u**|     |**n**|     |**o**|     |     |**a**|     |**t**|     |**e**|     |     |**t**|     |**c**|     |**a**|     |**l**|     |     |**i**|     |     |**a**|     |**l**|     |**i**|     |\n",
       "|     |**c**|**o**|**n**|**s**|**u**|**l**|**t**|**i**|**v**|**e**|     |**e**|**x**|**o**|**t**|**i**|**c**|     |**b**|**l**|**n**|     |**d**|     |**o**|     |     |**v**|     |**s**|**q**|**u**|**a**|**s**|**h**|     |**k**|**i**|**p**|     |     |**n**|     |**i**|     |**n**|     |\n",
       "|**m**|**i**|     |     |     |**t**|     |**a**|     |     |**x**|     |**a**|     |**n**|     |**d**|     |     |     |**y**|     |**c**|     |**w**|**i**|**t**|**h**|**e**|     |     |     |**l**|     |**t**|     |     |     |     |**s**|     |**s**|**t**|**e**|**m**|     |**s**|     |\n",
       "|     |**d**|     |**u**|     |**t**|**u**|**t**|     |**o**|     |     |**s**|     |**s**|     |**a**|     |**s**|     |**s**|     |**r**|**x**|     |**d**|     |     |**g**|**g**|     |     |**a**|     |     |**e**|     |**b**|     |**i**|     |     |**o**|     |**n**|     |**u**|     |\n",
       "|     |**a**|     |**p**|     |**r**|     |**i**|**n**|**s**|**t**|**r**|**u**|**m**|**e**|**n**|**t**|**a**|**l**|**l**|**y**|     |**y**|     |     |     |     |     |**i**|     |**p**|**a**|**r**|**v**|**o**|**v**|**i**|**r**|**u**|**s**|     |     |**d**|     |**e**|**o**|**f**|     |\n",
       "|     |**b**|**a**|**w**|**n**|**e**|**e**|**n**|     |**t**|     |     |**r**|     |**q**|     |**i**|     |**i**|     |**n**|     |**s**|**h**|**r**|**o**|**u**|**d**|**e**|**d**|     |**m**|     |**a**|     |**p**|     |**i**|     |     |     |**m**|     |     |**m**|     |**f**|     |\n",
       "|     |**l**|     |**i**|     |**s**|     |**g**|**a**|**r**|**b**|     |**a**|     |**u**|     |**o**|     |**c**|**a**|**o**|     |**t**|     |**f**|     |     |     |     |     |**s**|**h**|**a**|**r**|**p**|     |**i**|**n**|**a**|**c**|**c**|**e**|**s**|**s**|**i**|**b**|**l**|**e**|\n",
       "|     |**e**|     |**n**|     |**s**|     |     |     |**a**|     |     |**b**|**e**|**e**|     |**n**|     |**k**|     |**d**|     |**a**|     |**s**|     |**c**|     |**s**|     |     |**e**|     |     |**w**|     |     |**e**|     |**s**|     |**t**|     |     |**c**|     |**a**|     |\n",
       "|     |     |**e**|**g**|**g**|     |     |**r**|**i**|**c**|**h**|     |**l**|     |**n**|**p**|     |**p**|**i**|     |**y**|**e**|**l**|**l**|     |**j**|**o**|**i**|**n**|**d**|**e**|**r**|     |     |     |**s**|     |     |     |**s**|     |**a**|     |**c**|     |     |**t**|     |\n",
       "|     |**t**|     |     |     |     |**f**|     |     |**i**|     |     |**e**|     |**t**|     |**b**|     |**n**|     |     |     |**l**|     |**p**|     |**n**|     |**i**|     |     |**s**|     |**o**|     |**t**|     |     |**u**|     |**a**|**l**|**p**|**h**|**a**|**b**|**e**|**t**|\n",
       "|     |**y**|     |     |**b**|**a**|**l**|**m**|**l**|**i**|**k**|**e**|     |**a**|     |     |**u**|**n**|**g**|**l**|**a**|**m**|**o**|**r**|**o**|**u**|**s**|     |**t**|     |     |**t**|     |**s**|**o**|**f**|**a**|     |**n**|     |     |**l**|     |**i**|     |     |     |**e**|\n",
       "|     |**r**|     |     |**u**|     |**c**|     |     |**f**|     |**v**|     |**k**|     |     |**l**|     |     |     |     |     |**g**|     |**o**|     |**o**|     |     |**c**|     |     |     |**c**|     |**u**|     |     |**c**|**l**|**a**|**y**|     |**l**|**e**|**o**|**l**|**a**|\n",
       "|**s**|**o**|**d**|     |**r**|     |     |**g**|**e**|**o**|**d**|**e**|**t**|**i**|**c**|**a**|**l**|     |     |     |**w**|     |**e**|     |**r**|     |**l**|     |**p**|**o**|**i**|**n**|**t**|**e**|     |     |**w**|     |**u**|     |     |     |     |**i**|     |     |**o**|     |\n",
       "|**k**|     |**o**|     |**p**|**l**|     |     |     |**r**|     |**n**|     |     |     |**p**|     |     |**b**|**g**|**a**|     |**n**|     |     |**s**|**i**|**c**|     |**n**|     |     |     |**o**|     |     |**r**|     |**t**|     |     |**d**|**o**|**a**|**t**|**i**|**n**|**g**|\n",
       "|**i**|     |**w**|     |     |     |     |**s**|**i**|**m**|     |     |**n**|**a**|**g**|**p**|**u**|**r**|     |     |**l**|     |     |**w**|     |     |**d**|     |     |**t**|     |**w**|**i**|**l**|**d**|**f**|**i**|**r**|**e**|     |**e**|     |     |**s**|     |     |**g**|     |\n",
       "|**r**|     |**n**|     |     |**f**|**d**|**m**|     |     |**p**|**s**|     |     |     |**e**|     |     |     |     |**d**|**e**|**v**|**a**|**s**|**t**|**a**|**t**|**i**|**o**|**n**|     |     |**a**|     |     |**g**|     |     |**b**|**l**|**o**|**o**|**t**|**h**|     |**v**|     |\n",
       "|**r**|**e**|**s**|**e**|**t**|     |     |**e**|     |     |**i**|     |     |     |     |**r**|**o**|**u**|**p**|     |**r**|     |     |**t**|     |     |**t**|     |     |**r**|     |     |     |     |**p**|**i**|**g**|**g**|**y**|     |**s**|     |     |     |**d**|     |**i**|     |\n",
       "|     |     |**t**|     |**i**|     |**c**|**a**|**p**|**i**|**t**|**a**|**l**|**i**|**s**|**t**|     |     |**r**|     |**o**|     |     |**t**|     |**b**|**e**|**a**|**s**|**t**|     |     |     |**h**|     |     |**l**|     |     |     |**e**|**n**|**r**|**o**|**l**|**l**|**e**|**d**|\n",
       "|**m**|**e**|**a**|**s**|**l**|**y**|     |**t**|     |     |**k**|     |     |**d**|     |**a**|**l**|**l**|**y**|     |**n**|**c**|     |**l**|     |**e**|     |     |**o**|     |**m**|     |**w**|**a**|**n**|**t**|**e**|**d**|     |     |     |     |**a**|     |     |     |**w**|     |\n",
       "|**e**|     |**g**|     |**l**|     |     |**o**|     |**p**|**i**|**p**|     |**p**|     |**i**|     |     |     |     |     |     |     |**e**|     |**n**|     |     |**p**|     |**s**|     |     |**n**|     |     |**r**|     |     |     |**a**|     |**c**|     |     |     |     |     |\n",
       "|     |**k**|**e**|**y**|**p**|**o**|**i**|**n**|**t**|     |**n**|     |**g**|**r**|**a**|**n**|**d**|**f**|**a**|**t**|**h**|**e**|**r**|**l**|**y**|     |     |**w**|**a**|**r**|**b**|**i**|**r**|**d**|     |     |     |     |     |     |**c**|**l**|**e**|**a**|**n**|     |     |     |\n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%%prun\n",
    "gr, infos = create_word_grid(16*3,9*3, target_density=0.55)\n",
    "def grid2mdown(grid):\n",
    "    h,w  = grid.shape\n",
    "    \n",
    "    md_str = \"     \".join([\"|\"] * (w+1)) + \"\\n\"\n",
    "    md_str += \":---:\".join([\"|\"] * (w+1)) + \"\\n\"\n",
    "    \n",
    "    for y in range(h):\n",
    "        md_str += \"|\" + \"|\".join([(f\"**{grid[y,x]}**\" if grid[y,x] != \" \" else \"     \") for x in range(w)]) + \"|\\n\"\n",
    "    \n",
    "    return Markdown(md_str)\n",
    "\n",
    "display(grid2mdown(gr))\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "edie -- surname\n"
     ]
    }
   ],
   "source": [
    "i=220\n",
    "\n",
    "word = list(infos.keys())[i]\n",
    "\n",
    "print(word, \"--\", infos[word].get_hint())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "## wagenboom\n",
       "\n",
       "### Senses:\n",
       "\n",
       "* A South African proteaceous tree\n",
       "* The tough wood of this tree, used for making wagon wheels\n",
       "\n",
       "### Synonyms:\n",
       "\n",
       "* waboom\n",
       "* wagon tree\n",
       "\n",
       "### Antonyms:\n",
       "\n",
       "\n",
       "    \n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(display_info(\"wagenboom\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from enum import Enum\n",
    "\n",
    "class HintOrientation(Enum):\n",
    "    VERTICAL = 0\n",
    "    HORIZONTAL = 1\n",
    "    BOTH = 2\n",
    "    \n",
    "class FieldType(Enum):\n",
    "    EMPTY = 0\n",
    "    HINT = 1\n",
    "    LETTER = 2\n",
    "\n",
    "class Field(object):\n",
    "    def __init__(self, field_type: FieldType = FieldType.EMPTY):\n",
    "        self._field_type = field_type\n",
    "    \n",
    "    def get_type(self) -> FieldType:\n",
    "        return self._field_type\n",
    "    \n",
    "    def get_content(self) -> str:\n",
    "        return None\n",
    "\n",
    "class HintField(Field):\n",
    "    def __init__(self, horizontal_hint: str = None, vertical_hint: str = None):\n",
    "        super().__init__(field_type=FieldType.HINT)\n",
    "        \n",
    "        self._horizontal_hint = horizontal_hint\n",
    "        self._vertical_hint = vertical_hint\n",
    "    \n",
    "    def get_horizontal_hint(self) -> str:\n",
    "        return self._horizontal_hint\n",
    "    \n",
    "    def get_vertical_hint(self) -> str:\n",
    "        return self._vertical_hint\n",
    "    \n",
    "    def set_horizintal_hint(hint: str):\n",
    "        self._horizontal_hint = hint\n",
    "    \n",
    "    def set_vertical_hint(hint:str):\n",
    "        self._vertical_hint = hint\n",
    "\n",
    "class LetterField(Field):\n",
    "    def __init__(self, letter: str):\n",
    "        assert len(letter) <= 1\n",
    "        \n",
    "        super().__init__(field_type = FieldType.LETTER)\n",
    "        \n",
    "        self._letter = letter\n",
    "        self._revealed = False\n",
    "    \n",
    "    def get_content(self) -> str:\n",
    "        return self._letter\n",
    "    \n",
    "    def reveal(self):\n",
    "        self._revealed = True\n",
    "    \n",
    "    def is_revealed(self) -> bool:\n",
    "        return self._revealed\n",
    "\n",
    "class Grid(object):\n",
    "    def __init__(self, width: int, height: int, density = 0.5):\n",
    "        self._width = width\n",
    "        self._height = height\n",
    "        self._density = density\n",
    "        self._grid = []\n",
    "        self._build_grid()\n",
    "    \n",
    "    def _build_grid(self):\n",
    "        raw_grid, word_infos = create_word_grid(self._width - 1, self._height - 1, target_density=self._density)\n",
    "        \n",
    "        # note: we will append an additional row and column, to have enough space to place hint fields\n",
    "        \n",
    "        self._grid = [[Field()] * self._width] # initialize with empty row\n",
    "        \n",
    "        for y in range(self._height):\n",
    "            row = [Field()] # initialize row with empty column\n",
    "            for x in range(self._width):\n",
    "                raw_cell = raw_grid[y-1,x-1]\n",
    "                if raw_cell == \" \":\n",
    "                    row.append(Field())\n",
    "                else:\n",
    "                    row.append(LetterField(raw_cell))\n",
    "            \n",
    "            self._grid.append(row)\n",
    "        \n",
    "        # place hint fields:\n",
    "        for word, info in word_infos.items():\n",
    "            y,x = info.get_hint_location()\n",
    "            # correct offset\n",
    "            y += 1\n",
    "            x += 1\n",
    "            \n",
    "            cell = self._grid[y][x]\n",
    "            \n",
    "            # check if we already have a hint here:\n",
    "            if cell.get_type() == FieldType.HINT:\n",
    "                if info.is_vertical():\n",
    "                    cell.set_vertical_hint(info.get_hint())\n",
    "                else:\n",
    "                    cell.set_horizintal_hint(info.get_hint())\n",
    "            elif cell.get_type() == FieldType.LETTER:\n",
    "                # edge case: a word has \"eaten up\" another one, skipping that case\n",
    "                pass\n",
    "            \n",
    "            else:\n",
    "                if info.is_vertical():\n",
    "                    self._grid[y][x] = HintField(vertical_hint=info.get_hint())\n",
    "                else:\n",
    "                    self._grid[y][x] = HintField(horizontal_hint=info.get_hint())\n",
    "\n",
    "                        \n",
    "class Crossword(object):\n",
    "    def __init__(self, width: int, height: int, database: dict):\n",
    "        self._width = width\n",
    "        self._height = height\n",
    "        self._database = database\n",
    "        self._grid = Grid(width, height)\n",
    "    \n",
    "    \n",
    "        \n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "209\n"
     ]
    }
   ],
   "source": [
    "cw = Crossword(16*3, 9*3, english_vocab_db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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