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- __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 torbay_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
- try:
- product_name = soup.find('div', {'class': 'product-information'}).find('h1').text
- name = cleanString(product_name.strip())
- except:
- product_name = soup.find('div', {'class': 'profile-info'}).find('h2').text
- name = cleanString(product_name.strip())
-
- # Finding Vendor FIx
- vendor_name = soup.find('div', {"class": "profile-info"}).find('h2').text
- vendor = cleanString(vendor_name.strip())
-
- # Finding Vendor Image
- vendor_image = soup.find('div', {'class': 'avatar'}).find('img')
- vendor_image = vendor_image.get('src')
- vendor_image = vendor_image.split('base64,')[-1]
-
- # Finding Prices
- USD = soup.find('div', {'class': "total-price"}).find('span').text.strip()
-
- # Finding the Product Category
- cat = soup.find('div', {'class': "profile-info"}).find('p').text
- category = cleanString(cat.strip())
-
- # Finding the Product description
- try:
- describe = soup.find('div', {'class': "info"}).find('p').text
- if "\n" in describe:
- describe = describe.replace("\n", " ")
- describe = describe.replace("\r", " ")
- describe = cleanString(describe.strip())
- except:
- # print("product desc")
- describe = soup.find('div', {'class': 'info'}).text
- describe = cleanString(describe.strip())
-
- # Finding Product Image
- image = soup.find('div', {'class': 'image text-center'}).find('img')
- image = image.get('src')
- image = image.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 torbay_listing_parser(soup):
-
- # Fields to be parsed
- nm = 0 # *Total_Products (Should be Integer)
- mktName = "TorBay" # 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)
- MS = [] # 6 Product_MS_Classification (Microsoft Security)
- 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": "product-card"})
-
- # Populating the Number of Products
- nm = len(listing)
-
- for a in listing:
-
- product_name = a.find('p', {'class': 'name'}).text
- name.append(cleanString(product_name.strip()))
-
- # Finding Product Image
- image.append("-1")
-
- prod = a.find('p', {'class': 'price'}).text # price
- USD.append(cleanString(prod.strip()))
-
- ven = a.find('div', {'class': 'pc-footer'}).find('div').find('a').text # pc-footer
- vendor.append(cleanString(ven.strip()))
- # print(ven)
-
- # Finding Vendor Image
- image_vendor.append("-1")
-
- h = a.find('p', {'class': 'name'}).find('a').get('href')
- href.append(h)
-
- CVE.append("-1")
- MS.append("-1")
- rating_vendor.append("-1")
- success.append("-1")
- describe.append("-1")
- views.append("-1")
- reviews.append("-1")
- rating_item.append("-1")
- addDate.append("-1")
- BTC.append("-1")
- EURO.append("-1")
- sold.append("-1")
- qLeft.append("-1")
- shipFrom.append("-1")
- shipTo.append("-1")
- category.append("Hacking")
-
- # 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 torbay_links_parser(soup):
-
- # Returning all links that should be visited by the Crawler
-
- href = []
- listing = soup.find('section', {"id": "content"}).findAll('div', {"class": "product-card"})
-
- for a in listing:
- bae = a.find('div', {"class": "pc-footer"}).find('a', {"class": "btn btn-primary"}, href=True)
- link = bae['href']
- href.append(link)
-
- return href
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