__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
import re
#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 AnonMarket_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
name_of_product = soup.find("div", {"class": "heading"}).text
name = cleanString(name_of_product.strip())
description_div = soup.find("div", {"class": "tab1"})
if description_div is None:
describe = "-1"
else:
describe = cleanString(description_div.text.strip())
info_div = soup.find('div', {'class': 'information'})
table = info_div.find('table') if info_div else None
# Find all table rows
rows = table.find_all('tr')
# Parse each row to get relevant data
data = {}
for row in rows:
columns = row.find_all('td')
if len(columns) == 3:
key = columns[0].text.strip()
value = columns[2].text.strip()
data[key] = value
# Extract specific data from the dictionary and assign them to individual variables
vendor = data.get('Vendor', '-1')
shipFrom = data.get('Location', '-1')
shipTo = data.get('Ships to', '-1')
category = data.get('Category', '-1')
USD = data.get('Price', '-1').split()[0]
left = data.get('Stock', '-1')
# image
image = soup.find('img', {"class": "bigthumbnail"})
image = image.get('src').split('base64,')[-1]
# 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 AnonMarket_listing_parser(soup):
# Fields to be parsed
nm = 0 # *Total_Products (Should be Integer)
mktName = "AnonMarket" # 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
base_url = "http://2r7wa5og3ly4umqhmmqqytae6bufl5ql5kz7sorndpqtrkc2ri7tohad.onion"
cat = soup.find("div", {'class': 'heading'}).text
products_list = soup.find_all('div', {'class': 'item'})
nm = 0
for product in products_list:
name_of_product = product.find("div", {"class": "title"}).text.strip()
name.append(name_of_product)
name_of_vendor = product.find("a", {'class': 'seller'}).text.strip()
vendor.append(name_of_vendor)
category.append(cat)
tbody = product.find('div', {"class": "info"}).find('tbody')
# rating_item
width = tbody.find('div', {"class": "stars2"}).get('style')
rating_item.append(cleanNumbers(width.strip()))
tr = tbody.findAll('tr', recursive=False)
td = tr[2].findAll('td')
# sold
sold.append(td[0].text.strip())
# reviews
reviews.append(td[1].text.strip())
product_link_element = product.find("div", {"class": "title"}).find_parent('a')
link = product_link_element['href']
full_link = base_url + link
href.append(full_link)
# Append '-1' for unavailable data
rating_vendor.append("-1")
success.append("-1")
CVE.append("-1")
MS.append("-1")
describe.append("-1")
views.append("-1")
addDate.append("-1")
BTC.append("-1")
USD.append("-1")
EURO.append("-1")
qLeft.append("-1")
shipFrom.append("-1")
shipTo.append("-1")
nm += 1
# 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 AnonMarket_links_parser(soup):
# Base URL to prepend to each product link
base_url = "http://2r7wa5og3ly4umqhmmqqytae6bufl5ql5kz7sorndpqtrkc2ri7tohad.onion"
# Returning all links that should be visited by the Crawler
href = []
# Using a shorter, but still unique, class name
listing = soup.find('div', {'class': 'items'}).find_all('a', href=True, attrs={'href': lambda x: "/product/" in x})
for a in listing:
link = a.get('href')
if link: # Checks if 'href' attribute is not None
# Prepending the base URL to the scraped link
full_link = base_url + link
href.append(full_link)
# Filtering out any links that might not have '/product/' in them
product_links = [link for link in href if '/product/' in link]
return product_links