__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 city_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
divmd7 = soup.find('div', {'class': "col-md-7"})
# Finding Vendor
vendor = divmd7.find('a').text.strip()
# Finding Prices
USD = soup.find('span', {'class': "total"}).text.strip()
tempBTC = soup.find('div', {'class': "text-center"}).text.strip()
BTC = tempBTC.replace("BTC", "").strip()
# Finding Product Image
image = soup.find('img', {'class': 'img-fluid'})
image = image.get('src')
image = image.split('base64,')[-1]
# Finding the Product description
describe = soup.find('div', {'class': "text-white"}).text
describe = cleanString(describe.strip())
# Searching for CVE and MS categories
cve = soup.findAll(text=re.compile('CVE-\d{4}-\d{4}'))
if cve:
CVE = " "
for idx in cve:
CVE += (idx)
CVE += " "
CVE = CVE.replace(',', ' ')
CVE = CVE.replace('\n', '')
ms = soup.findAll(text=re.compile('MS\d{2}-\d{3}'))
if ms:
MS = " "
for im in ms:
MS += (im)
MS += " "
MS = MS.replace(',', ' ')
MS = MS.replace('\n', '')
# 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 city_listing_parser(soup):
# Fields to be parsed
nm = 0 # *Total_Products (Should be Integer)
mktName = "CityMarket" # 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
listing = soup.findAll('div', {"class": "p-4"})
# Populating the Number of Products
nm = len(listing)
for a in listing:
bae = a.findAll('a', href=True)
# Adding the url to the list of urls
link = bae[0].get('href')
href.append(link)
# Category
tempCategory = soup.find('select', {"name": "category"})
tempCategory = tempCategory.find('option', selected=True).text.strip()
category.append(tempCategory)
# Product Name
product = a.find('h4', {"class": "text-center"}).text
product = product.replace('\n', ' ')
product = product.replace(",", "")
product = product.replace("...", "")
product = product.strip()
name.append(product)
# USD and BTC Price
price = a.find('div', {"class": "price"}).text
if "~" in price:
tempUSD = price.split("~")[0]
tempUSD = tempUSD.replace("$", "")
tempUSD = tempUSD.strip()
USD.append(tempUSD)
tempBTC = price.split("~")[1]
tempBTC = tempBTC.replace("BTC", "")
tempBTC = tempBTC.strip()
BTC.append(tempBTC)
else:
USD.append("-1")
BTC.append("-1")
# Img
product_image = a.find('img')
product_image = product_image.get('src')
product_image = product_image.split('base64,')[-1]
image.append(product_image)
# Searching for CVE and MS categories
cve = a.findAll(text=re.compile('CVE-\d{4}-\d{4}'))
if not cve:
cveValue="-1"
else:
cee = " "
for idx in cve:
cee += (idx)
cee += " "
cee = cee.replace(',', ' ')
cee = cee.replace('\n', '')
cveValue=cee
CVE.append(cveValue)
ms = a.findAll(text=re.compile('MS\d{2}-\d{3}'))
if not ms:
MSValue="-1"
else:
me = " "
for im in ms:
me += (im)
me += " "
me = me.replace(',', ' ')
me = me.replace('\n', '')
MSValue=me
MS.append(MSValue)
# 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 city_links_parser(soup):
# Returning all links that should be visited by the Crawler
href = []
listing = soup.findAll('div', {"class": "p-4"})
for a in listing:
bae = a.find('a', href=True)
link = bae['href']
href.append(link)
return href