price.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver as wb\n",
    "import time\n",
    "import pandas as pd\n",
    "from loguru import logger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7g/1dqbz5hx5994z2r91kw1_k2m0000gn/T/ipykernel_93949/4171513069.py:9: DeprecationWarning: executable_path has been deprecated, please pass in a Service object\n",
      "  driver = wb.Chrome('/Users/anvarshagvaleev/Education/DataScience/University/BusinessAnalysis/exercise_1/chromedriver', options=options)\n"
     ]
    }
   ],
   "source": [
    "url =  'https://www.google.com/search?q=Poco+X3+Pro+8%2F256+Gb+&sa=X&rlz=1C5CHFA_enRU988RU988&biw=1440'\\\n",
    "    '&bih=690&tbm=shop&sxsrf=ALiCzsYWOEznSSIhW9IqnXR7a4_MS_by8A%3A1671651853421&ei=DWKjY4qCGeevrgSbtI_gCQ&ved='\\\n",
    "    '0ahUKEwjKvKS3vIv8AhXnl4sKHRvaA5wQ4dUDCAg&uact=5&oq=Poco+X3+Pro+8%2F256+Gb+&gs_lcp='\\\n",
    "    'Cgtwcm9kdWN0cy1jYxADMgcIABCABBANMgcIABCABBANMgcIABCABBANMgcIABCABBANMgcIABCABBANMgkIABCABBANEBgyCQgAEIAEEA0QGDIJCAAQ'\\\n",
    "    'gAQQDRAYMgkIABCABBANEBgyCQgAEIAEEA0QGEoECEEYAFAAWABgowFoAHAAeACAAWOIAWOSAQExmAEAoAECoAEBwAEB&sclient=products-cc'\n",
    "options = wb.ChromeOptions()\n",
    "options.add_argument(\n",
    "'user-Agent=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.109 Safari/537.36')\n",
    "driver = wb.Chrome('/Users/anvarshagvaleev/Education/DataScience/University/BusinessAnalysis/exercise_1/chromedriver', options=options)\n",
    "driver.get(url=url)\n",
    "driver.maximize_window()\n",
    "time.sleep(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Dell S2721D'"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('NewData.xlsx', sheet_name='sr.2', index_col='id')\n",
    "names = data['name']\n",
    "names.iloc[44]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "# .send_keys('names.iloc[44]')\n",
    "prcs = []\n",
    "for i, name in enumerate(names):\n",
    "    logger.info(f'{i} / {len(names)}')\n",
    "    search = driver.find_elements(\"xpath\", '//input[@class=\"gLFyf\"]')[0]\n",
    "    button = driver.find_elements(\"xpath\", '//button[@jsname=\"Tg7LZd\"]')[0]\n",
    "    search.clear()\n",
    "    search.send_keys(name)\n",
    "    button.click()\n",
    "    time.sleep(3)\n",
    "    try:\n",
    "        price = driver.find_elements(\"xpath\", '(//div[@class=\"XrAfOe\"])[1]')[0]\n",
    "        prc = price.text\n",
    "    except:\n",
    "        prc = None\n",
    "    prcs.append(prc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
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     ]
    }
   ],
   "source": [
    "nprcs = []\n",
    "for i, p in enumerate(prcs):\n",
    "    logger.info(f'{i+1} / {len(names)}')\n",
    "    if p == None:\n",
    "        nprcs.append(p)\n",
    "    else:\n",
    "        nprcs.append(p.split(',')[0].replace(' ', ''))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfprice = pd.DataFrame(nprcs, columns=['price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['price'] = dfprice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "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>name</th>\n",
       "      <th>product_category_id</th>\n",
       "      <th>country_from</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Realme 9 Pro 8/128 Gb</td>\n",
       "      <td>1</td>\n",
       "      <td>Китай</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Redmi Note 10 Pro 8/128 Gb</td>\n",
       "      <td>1</td>\n",
       "      <td>Китай</td>\n",
       "      <td>15290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Poco X3 Pro 8/256 Gb</td>\n",
       "      <td>1</td>\n",
       "      <td>Китай</td>\n",
       "      <td>23490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Redmi Note 11 Pro 5G 8/128 GB</td>\n",
       "      <td>1</td>\n",
       "      <td>Китай</td>\n",
       "      <td>31990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Honor 50 8/128 Gb</td>\n",
       "      <td>1</td>\n",
       "      <td>Китай</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Huawei FreeBuds 4</td>\n",
       "      <td>7</td>\n",
       "      <td>Китай</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>JBL Tune 510BT</td>\n",
       "      <td>7</td>\n",
       "      <td>США</td>\n",
       "      <td>4939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>HyperX Cloud II</td>\n",
       "      <td>7</td>\n",
       "      <td>США</td>\n",
       "      <td>3990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>JBL Wave 200TWS</td>\n",
       "      <td>7</td>\n",
       "      <td>США</td>\n",
       "      <td>7988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>Logitech G Pro X</td>\n",
       "      <td>7</td>\n",
       "      <td>Швейцария</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              name  product_category_id country_from  price\n",
       "id                                                                         \n",
       "1            Realme 9 Pro 8/128 Gb                    1        Китай       \n",
       "2       Redmi Note 10 Pro 8/128 Gb                    1        Китай  15290\n",
       "3            Poco X3 Pro 8/256 Gb                     1        Китай  23490\n",
       "4    Redmi Note 11 Pro 5G 8/128 GB                    1        Китай  31990\n",
       "5                Honor 50 8/128 Gb                    1        Китай       \n",
       "..                             ...                  ...          ...    ...\n",
       "153              Huawei FreeBuds 4                    7        Китай       \n",
       "154                 JBL Tune 510BT                    7          США   4939\n",
       "155                HyperX Cloud II                    7          США   3990\n",
       "156                JBL Wave 200TWS                    7          США   7988\n",
       "157               Logitech G Pro X                    7    Швейцария    NaN\n",
       "\n",
       "[157 rows x 4 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7g/1dqbz5hx5994z2r91kw1_k2m0000gn/T/ipykernel_93949/72477652.py:5: FutureWarning: save is not part of the public API, usage can give unexpected results and will be removed in a future version\n",
      "  writer.save()\n"
     ]
    }
   ],
   "source": [
    "writer = pd.ExcelWriter('NNewDataFull.xlsx', engine='xlsxwriter')\n",
    "\n",
    "data.to_excel(writer, sheet_name='sr.2')\n",
    "\n",
    "writer.save()"
   ]
  }
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