khangtran
/
dark_web_forums


								__author__ = 'DarkWeb'


								# Here, we are importing the auxiliary functions to clean or convert data

								from MarketPlaces.Utilities.utilities import *


								# Here, we are importing BeautifulSoup to search through the HTML tree

								from bs4 import BeautifulSoup


								# parses description pages, so takes html pages of description pages using soup object, and parses it for info it needs

								# stores info it needs in different lists, these lists are returned after being organized

								# @param: soup object looking at html page of description page

								# return: 'row' that contains a variety of lists that each hold info on the description page

								def quest_description_parser(soup):

								    # Fields to be parsed


								    vendor = "-1"                       # 0 *Vendor_Name

								    success = "-1"                      # 1 Vendor_Successful_Transactions

								    rating_vendor = "-1"                # 2 Vendor_Rating

								    name = "-1"                         # 3 *Product_Name

								    describe = "-1"                     # 4 Product_Description

								    CVE = "-1"                          # 5 Product_CVE_Classification (Common Vulnerabilities and Exposures)

								    MS = "-1"                           # 6 Product_MS_Classification (Microsoft Security)

								    category = "-1"                     # 7 Product_Category

								    views = "-1"                        # 8 Product_Number_Of_Views

								    reviews = "-1"                      # 9 Product_Number_Of_Reviews

								    rating_item = "-1"                  # 10 Product_Rating

								    addDate = "-1"                      # 11 Product_AddedDate

								    BTC = "-1"                          # 12 Product_BTC_SellingPrice

								    USD = "-1"                          # 13 Product_USD_SellingPrice

								    EURO = "-1"                         # 14 Product_EURO_SellingPrice

								    sold = "-1"                         # 15 Product_QuantitySold

								    left = "-1"                         # 16 Product_QuantityLeft

								    shipFrom = "-1"                     # 17 Product_ShippedFrom

								    shipTo = "-1"                       # 18 Product_ShippedTo

								    image = "-1"                        # 19 Product_Image

								    vendor_image = "-1"                 # 20 Vendor_Image


								    # Finding Product Name

								    name = soup.find('div', class_='card-header bg-dark text-white rounded-0 text-center').text

								    name = cleanString(name).strip()


								    # USD Price

								    USD = soup.find('small', text='Product Price:').find_next('small').text.replace('$', '').strip()


								    # Product Description

								    describe = soup.find('textarea').text

								    describe = cleanString(describe).strip()


								    # Finding Product Image

								    image = soup.find('img', {'class': 'img-fluid'})

								    image = image.get('src').split('base64,')[-1]


								    # Finding Vendor Image

								    vendor_image = soup.select_one('.card-body.bg-mgray.css-selector.shadow img')

								    vendor_image = vendor_image.get('src').split('base64,')[-1]


								    # Finding Successful Transactions

								    success = soup.find('strong', text='Total Sales:').parent.text

								    success = cleanNumbers(success).strip()


								    # Finding Vendor Rating

								    temp = soup.find('strong', text='Rating:').parent

								    rating_vendor = len(temp.findAll('i', {"class": "fas fa-star"}))

								    half_stars = len(temp.findAll('i', {'class': "fas fa-star-half-alt"}))

								    if half_stars > 0:

								        rating_vendor += 0.5


								    # Finding Item Rating

								    temp = soup.find('small', text='Average Product Score:').find_next('small')

								    rating_item = len(temp.findAll('i', {"class": "fas fa-star"}))

								    half_stars = len(temp.findAll('i', {'class': "fas fa-star-half-alt"}))

								    if half_stars > 0:

								        rating_item += 0.5


								    # Populating the final variable (this should be a list with all fields scraped)

								    row = (vendor, rating_vendor, success, name, describe, CVE, MS, category, views, reviews, rating_item, addDate,

								           BTC, USD, EURO, sold, left, shipFrom, shipTo, image, vendor_image)


								    # Sending the results

								    return row


								# parses listing pages, so takes html pages of listing pages using soup object, and parses it for info it needs

								# stores info it needs in different lists, these lists are returned after being organized

								# @param: soup object looking at html page of listing page

								# return: 'row' that contains a variety of lists that each hold info on the listing page

								def quest_listing_parser(soup):


								    # Fields to be parsed

								    nm = 0  # *Total_Products (Should be Integer)

								    mktName = "quest"                     # 0 *Marketplace_Name

								    vendor = []                               # 1 *Vendor y

								    rating_vendor = []                        # 2 Vendor_Rating

								    success = []                              # 3 Vendor_Successful_Transactions

								    name = []                                 # 4 *Product_Name y

								    CVE = []                                  # 5 Product_CVE_Classification (Common Vulnerabilities and Exposures) dont worry about this

								    MS = []                                   # 6 Product_MS_Classification (Microsoft Security) dont worry about this

								    category = []                             # 7 Product_Category y

								    describe = []                             # 8 Product_Description

								    views = []                                # 9 Product_Number_Of_Views

								    reviews = []                              # 10 Product_Number_Of_Reviews

								    rating_item = []                          # 11 Product_Rating

								    addDate = []                              # 12 Product_AddDate

								    BTC = []                                  # 13 Product_BTC_SellingPrice

								    USD = []                                  # 14 Product_USD_SellingPrice y

								    EURO = []                                 # 15 Product_EURO_SellingPrice

								    sold = []                                 # 16 Product_QuantitySold

								    qLeft = []                                # 17 Product_QuantityLeft

								    shipFrom = []                             # 18 Product_ShippedFrom

								    shipTo = []                               # 19 Product_ShippedTo

								    image = []                                # 20 Product_Image

								    image_vendor = []                         # 21 Vendor_Image

								    href = []                                 # 22 Product_Links


								    # Extract all product listings

								    listing = soup.findAll('div', class_='col-md-2 my-md-0 col-12')

								    # Populating the Number of Products

								    nm = len(listing)


								    for a in listing:


								        # Extracting Product URL & Name

								        product_link_tags = a.find_all('a', class_='badge-info')

								        if product_link_tags:

								            # Using the first tag as default

								            product_link_tag = product_link_tags[0]

								            href.append(product_link_tag['href'])

								            name.append(cleanString(product_link_tag.text).strip())


								        # Extracting Product Image

								        img_tag = a.find('img')

								        if img_tag:

								            image_data = img_tag['src'].split('base64,')[-1]

								            image.append(image_data)


								        # Extracting Vendor Name

								        vendor_tag = a.find('a', class_='badge-dark')

								        if vendor_tag:

								            vendor.append(cleanString(vendor_tag.text.replace('👤', '')).strip())


								        # Extracting Product Price in USD

								        price_tag = a.find('a', class_='text')

								        if price_tag:

								            USD.append(price_tag.text.replace("$", "").strip())


								        category_tag = soup.find('span', class_= 'btn btn-sm btn-outline-mgray active border-info')

								        if category_tag:

								            category.append(cleanString(category_tag.text).strip())


								    # Populate the final variable (this should be a list with all fields scraped)

								    return organizeProducts(mktName, nm, vendor, rating_vendor, success, name, CVE, MS, category, describe, views,

								                            reviews, rating_item, addDate, BTC, USD, EURO, sold, qLeft, shipFrom, shipTo, href, image, image_vendor)


								# called by the crawler to get description links on a listing page

								# @param: beautifulsoup object that is using the correct html page (listing page)

								# return: list of description links from a listing page

								def quest_links_parser(soup):

								    # Returning all product links


								    href = []


								    # Locate all divs with class 'row'

								    row_divs = soup.findAll('div', class_='row')


								    for row_div in row_divs:

								        # Locate all product divs within the current 'row' div

								        product_divs = row_div.findAll('div', class_='col-md-2 my-md-0 col-12')


								        for product_div in product_divs:

								            # Locate the anchor tag containing the product link within each product div

								            product_link_tag = product_div.find('a', class_='badge-info')


								            if product_link_tag and product_link_tag.has_attr('href'):

								                href.append(product_link_tag['href'])


								    return href