__author__ = 'DarkWeb' # Here, we are importing the auxiliary functions to clean or convert data from MarketPlaces.Utilities.utilities import * def darkdock_description_parser(soup): """Parses the description pages of a DarkDock marketplace. It takes a BeautifulSoup object that represents the HTML page of a description page, and extracts various information such as vendor name, product name, etc. Args: soup: A BeautifulSoup object that represents the HTML page of a description page. Returns: The row of a description item as a tuple containing the information fields extracted from the description page. """ 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 Vendor vendor = soup.select_one('table tr:nth-of-type(2) td:nth-of-type(3) a u').text vendor = cleanString(vendor) vendor = vendor.strip() # Finding Product Name headings = soup.find('div', {'class': 'main'}).find_all('div', {'class': 'heading'}) name = headings[0].text name = cleanString(name) name = name.strip() # Finding the Product description describe = soup.find('div', {'class': 'tab1'}).text describe = cleanString(describe) describe = describe.strip() # Finding the Product category category = soup.select_one('table tr:nth-of-type(6) td:nth-of-type(3)').text category = cleanString(category) category = category.strip() # Finding Number of Product Reviews reviews = headings[1].text match = re.search(r'\((\d+)\)', reviews).group(1) reviews = cleanNumbers(reviews) reviews = reviews.strip() # Finding Prices USD = soup.select_one('table tr:nth-of-type(1) td:nth-of-type(3)').text USD = cleanNumbers(USD) USD = USD.strip() # Finding the Product Quantity Available left = soup.select_one('table tr:nth-of-type(7) td:nth-of-type(3)').text left = cleanNumbers(left) left = left.strip() # Finding Product Shipped From shipFrom = soup.select_one('table tr:nth-of-type(3) td:nth-of-type(3)').text shipFrom = cleanString(shipFrom) shipFrom = shipFrom.strip() # Finding Product Shipped To shipTo = soup.select_one('table tr:nth-of-type(5) td:nth-of-type(3)').text shipTo = cleanString(shipTo) shipTo = shipTo.strip() # Finding Product Image image = soup.find('img', {'class': 'bigthumbnail'}).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 def darkdock_listing_parser(soup): """Parses the listing pages of a DarkDock marketplace. It takes a BeautifulSoup object that represents the HTML page of a listing page, and extracts various information such as vendor name, product name, etc. It then removes and cleans the extracted information by passing it to the organizeProducts function. Args: soup: A BeautifulSoup object that represents the HTML page of a listing page. Returns: The row of a description item as a tuple containing the information fields extracted from the listing page. """ # Fields to be parsed nm = 0 # Total_Products (Should be Integer) mktName = "DarkDock" # 0 Marketplace_Name vendor = [] # 1 Vendor rating_vendor = [] # 2 Vendor_Rating success = [] # 3 Vendor_Successful_Transactions name = [] # 4 Product_Name 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 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 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 listings = soup.findAll('div', {'class': 'item'}) # Populating the Number of Products nm = len(listings) cat = soup.find('div', {'class': 'heading'}).text cat = cleanString(cat) cat = cat.strip() for listing in listings: # Finding the Vendor vendor_name = listing.find('div', {'class': 'seller'}).text vendor.append(vendor_name) # Finding the Product product = listing.find('div', {'class': 'title'}).text product = cleanString(product) product = product.strip() name.append(product) # Finding the Category category.append(cat) # Finding description description = listing.find('div', {'class': 'description'}).text description = cleanString(description) description = description.strip() describe.append(description) # Finding product views num_view = listing.select_one('.stats table tr:nth-of-type(3) td:nth-of-type(1)').text num_view = cleanNumbers(num_view) num_view = num_view.strip() views.append(num_view) # Finding product reviews num_reviews = listing.select_one('.stats table tr:nth-of-type(3) td:nth-of-type(3)').text num_reviews = cleanNumbers(num_reviews) num_reviews = num_reviews.strip() reviews.append(num_reviews) # Finding product rating based on width style rating = listing.find('div', {'class': 'stars2'}).get('style') rating = re.findall(r"\d+\.\d+|\d+", rating)[0] rating = cleanNumbers(rating) rating = rating.strip() rating_item.append(rating) # Finding Prices price = listing.find('div', {'class': 'price'}).text price = price.strip() USD.append(price) # Finding number of times product is sold num_sold = listing.select_one('.stats table tr:nth-of-type(3) td:nth-of-type(2)').text num_sold = cleanNumbers(num_sold) num_sold = num_sold.strip() sold.append(num_sold) # Finding shipping locations shipping = listing.find('div',{'class': 'shipping'}).text shippedFrom, shippedTo = cleanString(shipping).split(' > ') shipTo.append(shippedTo) shipFrom.append(shippedFrom) # Adding the url to the list of urls link = listing.find('a', recursive=False).get('href') href.append(link) image_vendor.append("-1") 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) def darkdock_links_parser(soup): """Returns a list of description links from a listing page. It takes a BeautifulSoup object that represents the HTML page of a listing page, and extracts all the description links from the page. Args: soup: A BeautifulSoup object that represents the HTML page of a listing page. Returns: A list of description links from a listing page. """ # Returning all links that should be visited by the Crawler href = [] listing = soup.find_all('a', href=lambda href: href and '/product/' in href) for a in listing: href.append(a['href']) return href