tracking-order.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip3 install beautifulsoup4\n",
    "# !pip3 install pandas\n",
    "# !pip3 install requests\n",
    "# !pip3 install more-itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "import requests\n",
    "import pandas as pd \n",
    "from more_itertools import grouper\n",
    "import itertools\n",
    "from datetime import datetime\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CLASS BY Daniel Ellis, FROM:\n",
    "# https://betterprogramming.pub/custom-system-notifications-from-python-mac-5ff42e71214 \n",
    "\n",
    "from os import system\n",
    "import time\n",
    "\n",
    "class Alerts:\n",
    "\n",
    "  def sound(self, noise = '/System/Library/Sounds/Submarine.aiff'):\n",
    "    system(f'afplay {noise}')\n",
    "\n",
    "  \n",
    "  def repeat(self, times = 4, delay = 1, noise =  '/System/Library/Sounds/Submarine.aiff'):\n",
    "           for i in range(times):\n",
    "                sound(noise)\n",
    "                time.sleep(delay)\n",
    "  \n",
    "  def announce(self, text = 'The program has finished'):\n",
    "           system(f'say \"{text}\" &')\n",
    " \n",
    "  def notification(self, message='Notification from Python', app = 'Terminal'):\n",
    "           system(f'osascript -e \\'tell application \"{app}\" to display alert \"{message}\"\\'&')\n",
    "\n",
    "  #speak and notification    \n",
    "  def notify(self, message='Finished',app='Terminal'): \n",
    "      system(f'say \"{message}\"& osascript -e \\'tell application \"{app}\" to display alert \"{message}\"\\'&')\n",
    "\n",
    "  \n",
    "  @property\n",
    "  def beep(self):\n",
    "    self.repeat(10,1)\n",
    "      \n",
    "  end = property(notify)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers = {'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36'}\n",
    "numero_da_remessa = '20220012695943'\n",
    "r = requests.get(f'https://corporativo.directlog.com.br/track_individual/index.asp?numtracking={numero_da_remessa}',\n",
    "                headers=headers,\n",
    "                timeout=5)\n",
    "\n",
    "soup = BeautifulSoup(r.content, 'html.parser')\n",
    "tables = soup.find_all(\"table\")\n",
    "table = tables[7] # for directlog tracking there's no other way to identify the table :("
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data:  ['DATA', 'HORA', 'OPERAÇÃO', 'LOCAL', 'OBSERVAÇÃO', '12/06/2022', '14:21', 'Recebimento de Remessa por Api', '', '', '12/06/2022', '14:47', 'Geração da Remessa (CAT)', 'Seropédica', 'ARQUIVO - Remessa número : 20220012695943', 'None']\n",
      "\n",
      "\n",
      " sorry, no updates on your table!\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "for column_number, column in enumerate(table.find_all('td')):\n",
    "    if column_number== 0:\n",
    "         # this is an empty line idk what's doin' there\n",
    "        continue\n",
    "\n",
    "    for row_number,row in enumerate(table.find('tr')): \n",
    "        content = str(column.find('b'))\n",
    "        content = content.replace(\"<b>\",\"\").replace(\"</b>\",\"\").replace(\"<br/>\",\"\")\n",
    "        data.append(content)\n",
    "   \n",
    "\n",
    "print(f'data: ',data)\n",
    "list_of_lists = list(grouper(data, 5, fillvalue=None))\n",
    "\n",
    "if not os.path.exists(os.getcwd()+'//last_number_of_lines.txt'): # se arquivo de linhas, nao existir, é porque script ainda nao rodou\n",
    "    with open('last_number_of_lines.txt','w', encoding='utf-8') as text_file: \n",
    "        text_file.write(str(1))\n",
    "        print(\"\\n\\nDON'T DELETE THE last_number_of_lines.txt FILE, IT'S THE CONTROL SO WE KNOW IF WE HAD ANY UPDATES ON THE ORDER TRACKING TABLE\")\n",
    "\n",
    "with open('last_number_of_lines.txt','r', encoding='utf-8') as text_file:\n",
    "    n_linhas = int(text_file.read())\n",
    "\n",
    "if len(list_of_lists) > n_linhas: # length 1 is always the header, if len is 2 it means we have at least 1 line with real data of the order tracking update\n",
    "                                     # IMPROVEMENT POINT: datetime concat + comparison with current datetime instead of amount of table rows\n",
    "    print('\\n\\nOK, we got some update on your tracking')\n",
    "    info = Alerts()\n",
    "    info.notify(message ='THERE WAS AN UPDATE ON YOUR PACK! check where your order is! it might be arriving! ',app = 'System Preferences')\n",
    "    with open('last_number_of_lines.txt','w', encoding='utf-8') as text_file: \n",
    "        text_file.write(str(len(list_of_lists)))\n",
    "    print(f'updating row control txt: current amount of rows on table: {len(list_of_lists)} \\nexporting now CSV with current tracking state stolen on website\\n\\n')\n",
    "    df = pd.DataFrame(list_of_lists)\n",
    "    print(df)\n",
    "    datestamp = datetime.now().strftime(\"%Y_%m_%d-%H_%M_%S\")\n",
    "    filename = f'./a-{datestamp}.csv'\n",
    "    df.to_csv(filename, header=False)\n",
    "    print('exported csv!')\n",
    "\n",
    "else:\n",
    "    print('\\n\\n sorry, no updates on your table!')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.9 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.9"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}