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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scrape data from aon2e and generate csvs to import in to sqlite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies\n",
    "import pandas as pd\n",
    "from bs4 import BeautifulSoup as bs, Tag, NavigableString\n",
    "import os\n",
    "from splinter import Browser\n",
    "\n",
    "# Setting up Selenium\n",
    "chrome_driver = os.path.join('..', 'chromedriver.exe')\n",
    "executable_path = {'executable_path': chrome_driver}\n",
    "browser = Browser('chrome', **executable_path, headless=False)\n",
    "\n",
    "# Pandas config\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scrape_description(url, id_number):\n",
    "\n",
    "    # Empty lists to store the scraped values\n",
    "    name_list = []\n",
    "    description_list = []\n",
    "\n",
    "    print(f'Beginning Data Retrieval')\n",
    "    print(f'------------------------')\n",
    "\n",
    "    # Loop from 1 to the value in weapon_number\n",
    "    for page in range(1, id_number+1):\n",
    "\n",
    "        browser.visit(url + str(page))\n",
    "        html = browser.html\n",
    "        soup = bs(html, 'html.parser')\n",
    "\n",
    "        # Select only the content section\n",
    "        content = soup.find(id='ctl00_MainContent_DetailedOutput')\n",
    "\n",
    "        try:\n",
    "            # Store the name\n",
    "            name = content.find('h1', class_='title').a.text.strip()\n",
    "            name\n",
    "\n",
    "        except:\n",
    "            name = f'name: {page}'\n",
    "\n",
    "        try:\n",
    "            # Start the loop after the link to the book\n",
    "            start = content.find('a', class_='external-link').next_sibling\n",
    "            description = ''\n",
    "            for e in start.next_siblings:\n",
    "                if isinstance(e, Tag):\n",
    "                    if e.name == 'br':\n",
    "                        if e.next_sibling.name == 'br':\n",
    "                            # If the next 2 elements are br skip this\n",
    "                            # loop it will be handled in the elif\n",
    "                            continue\n",
    "                        elif e.previous_sibling.name == 'br':\n",
    "                            # If this element and the previous are br\n",
    "                            # and the next is not append /n\n",
    "                            description = description + ' /n/n'\n",
    "                        else:\n",
    "                            # If there is just one br append /n\n",
    "                            description =  description + ' /n'\n",
    "                    else:\n",
    "                        # Append the text inside the element\n",
    "                        description = description + e.text.strip()\n",
    "                elif isinstance(e, NavigableString):\n",
    "                    # Since it is just a text append it\n",
    "                    description = description + e\n",
    "\n",
    "        except:\n",
    "            description = f'name: {page}'\n",
    "\n",
    "        print(f'{page} of {id_number} | {name}')\n",
    "\n",
    "        # Append values to our empty lists\n",
    "        name_list.append(name)      \n",
    "        description_list.append(description)\n",
    "\n",
    "    print(f'------------------------')\n",
    "    print(f'Data Retrieval Complete')\n",
    "    \n",
    "    # Create df with the scraped data\n",
    "    data = {'Name': name_list, 'description': description_list}\n",
    "    \n",
    "    # Returns a data frame\n",
    "    return pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# scrape the descriptions\n",
    "url_background = 'https://2e.aonprd.com/Backgrounds.aspx?ID='\n",
    "number_background = 50 # number to scrape\n",
    "\n",
    "description_background = scrape_description(url_background, number_background)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "description_background.to_csv('background.csv', encoding='UTF-8', index=False)"
   ]
  }
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