Search Engine.ipynb

{
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  {
   "cell_type": "code",
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   },
   "outputs": [],
   "source": [
    "## Importing the required libraries\n",
    "\n",
    "import json \n",
    "import string\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "with open('recipes.json') as f:\n",
    "    info = json.load(f)\n",
    "with open('recipes.json') as f:\n",
    "    info1 = json.load(f)\n",
    "\n",
    "fd = pd.DataFrame( None,columns =['line','title','categories','ingredients','directions']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Creating a function for the pre-processing of the query\n",
    "\n",
    "def check_query(query):\n",
    "    if isinstance(query,list) == True:\n",
    "        query = ' '.join(query)\n",
    "    query = query.lower() \n",
    "    tab = query.maketrans(string.punctuation,'                                ') \n",
    "    query = query.translate(tab) \n",
    "   # '01234567890123456789012345678901'\n",
    "    tab = query.maketrans(string.digits,'          ') \n",
    "    query = query.translate(tab) \n",
    "\n",
    "    query = query.split()\n",
    "    if isinstance(query,list) == True:\n",
    "        i = 0\n",
    "        while i < len(query):\n",
    "            if len(query[i]) < 3:\n",
    "                query.remove(query[i])\n",
    "                i -= 1\n",
    "            i += 1\n",
    "    \n",
    "    return query  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>line</th>\n",
       "      <th>title</th>\n",
       "      <th>categories</th>\n",
       "      <th>ingredients</th>\n",
       "      <th>directions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>adult</th>\n",
       "      <td>[0, 11966, 14662, 15721, 17620]</td>\n",
       "      <td>[0]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[11966, 14662, 15721, 17620]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cheese</th>\n",
       "      <td>[0, 6, 28, 32, 34, 42, 54, 55, 91, 92, 94, 106...</td>\n",
       "      <td>[0, 32, 34, 92, 139, 159, 166, 176, 197, 251, ...</td>\n",
       "      <td>[0, 6, 28, 32, 34, 42, 54, 91, 92, 133, 139, 1...</td>\n",
       "      <td>[6, 28, 34, 42, 91, 92, 94, 106, 133, 139, 145...</td>\n",
       "      <td>[0, 28, 32, 34, 42, 55, 94, 106, 133, 139, 145...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pimiento</th>\n",
       "      <td>[0, 117, 503, 856, 899, 1195, 1204, 1422, 1912...</td>\n",
       "      <td>[0, 503, 6628, 7146, 11330, 11331, 11332, 11333]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[117, 503, 856, 899, 1195, 1204, 1422, 1912, 2...</td>\n",
       "      <td>[117, 503, 6628, 7146, 7545, 8284, 11330, 1133...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alabama</th>\n",
       "      <td>[0, 10317, 17320]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[0, 10317, 17320]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cheddar</th>\n",
       "      <td>[0, 28, 30, 248, 252, 254, 267, 286, 365, 456,...</td>\n",
       "      <td>[252, 267, 286, 365, 772, 798, 804, 805, 856, ...</td>\n",
       "      <td>[0, 248, 254, 267, 286, 772, 773, 788, 798, 80...</td>\n",
       "      <td>[0, 28, 30, 248, 252, 254, 267, 286, 365, 456,...</td>\n",
       "      <td>[0, 30, 252, 254, 786, 788, 798, 805, 856, 895...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kefalotíri</th>\n",
       "      <td>[17719]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[17719]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mozarella</th>\n",
       "      <td>[17723]</td>\n",
       "      <td>[17723]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>belt</th>\n",
       "      <td>[17730]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[17730]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rubs</th>\n",
       "      <td>[17730]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[17730]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zuni</th>\n",
       "      <td>[17732]</td>\n",
       "      <td>[17732]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13413 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         line  \\\n",
       "adult                         [0, 11966, 14662, 15721, 17620]   \n",
       "cheese      [0, 6, 28, 32, 34, 42, 54, 55, 91, 92, 94, 106...   \n",
       "pimiento    [0, 117, 503, 856, 899, 1195, 1204, 1422, 1912...   \n",
       "alabama                                     [0, 10317, 17320]   \n",
       "cheddar     [0, 28, 30, 248, 252, 254, 267, 286, 365, 456,...   \n",
       "...                                                       ...   \n",
       "kefalotíri                                            [17719]   \n",
       "mozarella                                             [17723]   \n",
       "belt                                                  [17730]   \n",
       "rubs                                                  [17730]   \n",
       "zuni                                                  [17732]   \n",
       "\n",
       "                                                        title  \\\n",
       "adult                                                     [0]   \n",
       "cheese      [0, 32, 34, 92, 139, 159, 166, 176, 197, 251, ...   \n",
       "pimiento     [0, 503, 6628, 7146, 11330, 11331, 11332, 11333]   \n",
       "alabama                                                   NaN   \n",
       "cheddar     [252, 267, 286, 365, 772, 798, 804, 805, 856, ...   \n",
       "...                                                       ...   \n",
       "kefalotíri                                                NaN   \n",
       "mozarella                                             [17723]   \n",
       "belt                                                      NaN   \n",
       "rubs                                                      NaN   \n",
       "zuni                                                  [17732]   \n",
       "\n",
       "                                                   categories  \\\n",
       "adult                                                     NaN   \n",
       "cheese      [0, 6, 28, 32, 34, 42, 54, 91, 92, 133, 139, 1...   \n",
       "pimiento                                                  NaN   \n",
       "alabama                                     [0, 10317, 17320]   \n",
       "cheddar     [0, 248, 254, 267, 286, 772, 773, 788, 798, 80...   \n",
       "...                                                       ...   \n",
       "kefalotíri                                                NaN   \n",
       "mozarella                                                 NaN   \n",
       "belt                                                      NaN   \n",
       "rubs                                                      NaN   \n",
       "zuni                                                      NaN   \n",
       "\n",
       "                                                  ingredients  \\\n",
       "adult                                                     NaN   \n",
       "cheese      [6, 28, 34, 42, 91, 92, 94, 106, 133, 139, 145...   \n",
       "pimiento    [117, 503, 856, 899, 1195, 1204, 1422, 1912, 2...   \n",
       "alabama                                                   NaN   \n",
       "cheddar     [0, 28, 30, 248, 252, 254, 267, 286, 365, 456,...   \n",
       "...                                                       ...   \n",
       "kefalotíri                                            [17719]   \n",
       "mozarella                                                 NaN   \n",
       "belt                                                      NaN   \n",
       "rubs                                                      NaN   \n",
       "zuni                                                      NaN   \n",
       "\n",
       "                                                   directions  \n",
       "adult                            [11966, 14662, 15721, 17620]  \n",
       "cheese      [0, 28, 32, 34, 42, 55, 94, 106, 133, 139, 145...  \n",
       "pimiento    [117, 503, 6628, 7146, 7545, 8284, 11330, 1133...  \n",
       "alabama                                                   NaN  \n",
       "cheddar     [0, 30, 252, 254, 786, 788, 798, 805, 856, 895...  \n",
       "...                                                       ...  \n",
       "kefalotíri                                                NaN  \n",
       "mozarella                                                 NaN  \n",
       "belt                                                  [17730]  \n",
       "rubs                                                  [17730]  \n",
       "zuni                                                      NaN  \n",
       "\n",
       "[13413 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "## Separating the words as per the keys\n",
    "\n",
    "for rec in range(len(info)):\n",
    "    w_list = []\n",
    "    \n",
    "    for head in ['title','categories','ingredients','directions']:\n",
    "        try:\n",
    "            info[rec][head] = check_query(info[rec][head]) \n",
    "            \n",
    "            wd, freq = np.unique(info[rec][head],return_counts= True)\n",
    "            wd = list(wd)\n",
    "            w_list = w_list+wd\n",
    "            \n",
    "            for w in range(len(wd)):\n",
    "                if wd[w] in fd.index:\n",
    "                    if isinstance(fd[head][wd[w]],list) == False:\n",
    "                        fd[head][wd[w]] = [rec]\n",
    "                    else:\n",
    "                        fd[head][wd[w]].append(rec)\n",
    "                else:\n",
    "                    fd.loc[wd[w]] = {'line':np.nan,'title':np.nan,'categories':np.nan,'ingredients':np.nan,'directions':np.nan}\n",
    "                    fd[head][wd[w]] = [rec]  \n",
    "        except:\n",
    "            pass\n",
    "    wds,freq = np.unique(w_list,return_counts= True)\n",
    "    wds = list(wds)\n",
    "    \n",
    "    for w in range(len(wds)):\n",
    "        if isinstance(fd['line'][wds[w]],list) == False:\n",
    "            fd['line'][wds[w]] = [rec]\n",
    "        else:\n",
    "            fd['line'][wds[w]].append(rec)\n",
    "                    \n",
    "fd              "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Creating a search function \n",
    "\n",
    "def search(query, ordering = 'normal', count = 10):\n",
    "    query = check_query(query) \n",
    "\n",
    "    try:\n",
    "        a= set(fd['line'][query[0]])\n",
    "    except:\n",
    "        return\n",
    "    \n",
    "    for k in query:\n",
    "        if k not in fd.index:\n",
    "\n",
    "            return \n",
    "        else:\n",
    "            a = a & set(fd['line'][k])\n",
    "\n",
    "    sc_r = []\n",
    "  \n",
    "    if  ordering ==  'normal' :\n",
    "        for k in a:\n",
    "            opt = 0.0\n",
    "            \n",
    "            try:\n",
    "                for p in range(len(info[k]['title'])):\n",
    "                    if info[k]['title'][p] in query:\n",
    "                        opt += 8.0\n",
    "            except:\n",
    "                opt += 0.0\n",
    "            \n",
    "            try:\n",
    "                for q in range(len(info[k]['categories'])):\n",
    "                    if info[k]['categories'][q] in query:\n",
    "                        opt += 4.0\n",
    "            except:\n",
    "                opt += 0.0\n",
    "            \n",
    "            try:\n",
    "                for r in range(len(info[k]['ingredients'])):\n",
    "                    if info[k]['ingredients'][r] in query:\n",
    "                        opt += 2.0\n",
    "            except:\n",
    "                opt += 0.0\n",
    "            \n",
    "            try:\n",
    "                for s in range(len(info[k]['directions'])):\n",
    "                    if info[k]['directions'][s] in query:\n",
    "                        opt += 1.0\n",
    "            except:\n",
    "                opt += 0.0\n",
    "                          \n",
    "            try:\n",
    "                opt += float(info[k]['rating'])\n",
    "            except:\n",
    "                opt += 0.0\n",
    "            sc_r.append((opt,k))\n",
    "            \n",
    "        if len(sc_r) < count:\n",
    "            count = len(sc_r) \n",
    "        for i in range(count):\n",
    "            c = max(sc_r)\n",
    "            print(info1[c[1]]['title'])\n",
    "            sc_r.remove(c)\n",
    "                                      \n",
    "    if  ordering ==  'simple' :\n",
    "        for k in a:  \n",
    "            try:\n",
    "                \n",
    "                p =len(info1[k]['ingredients'])\n",
    "                q =len(info1[k]['directions'])\n",
    "                if p >1 and q >1:\n",
    "                    opt = p*q\n",
    "                    sc_r.append((opt,k))   \n",
    "            except:\n",
    "                pass       \n",
    "        if len(sc_r) < count:\n",
    "              count = len(sc_r) \n",
    "        for i in range(count):\n",
    "            c = min(sc_r)\n",
    "            print(info1[c[1]]['title'])\n",
    "            sc_r.remove(c)    \n",
    "            \n",
    "    if  ordering ==  'healthy' :\n",
    "        for k in a:\n",
    "            try:\n",
    "                opt = []\n",
    "                for n in range(1,8):                    \n",
    "                    opt1 = (abs(info1[k]['calories']-(n*510))/510) + (2*abs(info1[k]['protein']-(n*18))/18) + (4*abs(info1[k]['fat']-(n*150))/150)\n",
    "                    \n",
    "       \n",
    "                    opt.append(opt1)\n",
    "                opt2 = min(opt)\n",
    "\n",
    "                sc_r.append((opt2,k))\n",
    "                \n",
    "            except:\n",
    "                pass   \n",
    "        if len(sc_r) < count:\n",
    "              count = len(sc_r) \n",
    "        for i in range(count):\n",
    "            c = min(sc_r)\n",
    "            print(info1[c[1]]['title'])\n",
    "            sc_r.remove(c)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tortillas in Black-Bean Purée \n",
      "Vegetable Medley in Garlic-Chile Sauce \n",
      "Fudgy Peanut Brownies \n",
      "Grilled Lemongrass Lamb Chops with Herbs \n",
      "Mocha Cake with Malted Semifreddo \n",
      "Cappuccino Brownies with White Chocolate-Espresso Sauce \n"
     ]
    }
   ],
   "source": [
    "## Example to check the search function\n",
    "\n",
    "search('coffee', ordering = 'healthy', count = 6)"
   ]
  }
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