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212 lines
8.4 KiB
212 lines
8.4 KiB
# Here, we are importing the auxiliary functions to clean or convert data
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from Forums.Utilities.utilities import *
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import datetime
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import re
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# Here, we are importing BeautifulSoup to search through the HTML tree
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from bs4 import BeautifulSoup
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# This is the method to parse the Description Pages (one page to each topic in the Listing Pages)
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def endchan_description_parser(soup):
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# Fields to be parsed
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topic = "-1" # 0 *topic name
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user = [] # 1 *all users of each post
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status = [] # 2 all user's authority in each post such as (adm, member, dangerous)
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reputation = [] # 3 all user's karma in each post (usually found as a number)
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interest = [] # 4 all user's interest in each post
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sign = [] # 5 all user's signature in each post (usually a standard message after the content of the post)
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post = [] # 6 all messages of each post
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feedback = [] # 7 all feedbacks of each vendor (this was found in just one Forum and with a number format)
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addDate = [] # 8 all dates of each post
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image_user = [] # 9 all user avatars of each post
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image_post = [] # 10 all first images of each post
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# Finding the topic (should be just one coming from the Listing Page)
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entire_post = soup.find('div', {"id": "threadList"}).find('div', {"id": "divThreads"}).find('div',
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class_ = re.compile('opCell'))
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original_post = entire_post.find('div', {"class": "innerOP"})
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post_header = original_post.find('div', {"class": "opHead"})
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topic = post_header.find('span', {"class": "labelSubject"}).text
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topic = re.sub("\[\w*\]", '', topic)
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topic = topic.replace(",","")
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topic = topic.replace("\n","")
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topic = cleanString(topic.strip())
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# the replies are separated from the original post, so have to get original post and then get repeated tags for the replies
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#functions to reuse code:
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def get_user(area):
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name = area.find('a', class_=re.compile('linkName'))
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author = name.text.strip()
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#user.append(cleanString(author))
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def get_post(area):
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content = area.find('div', {"class": "divMessage"})
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content = content.text.strip()
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#post.append(cleanString(content))
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def get_date(area):
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dt = area.find('span', {"class": "labelCreated"}).text
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dt = dt.strip().split()
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date_time_obj = datetime.strftime(dt[0], '%m-%d-%Y')
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#addDate.append(date_time_obj)
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def get_user_img(area):
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avatar_img = area.find('img', class_= re.compile('imgFlag'))
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if avatar_img is not None:
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avatar_img = avatar_img.get('src').split('base64,')[-1]
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else:
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avatar_img = "-1"
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#image_user.append(avatar_img)
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def get_first_img(area):
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img_cell = area.find('div', class_= re.compile('panelUploads')).find('figure', {"class": "uploadCell"})
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if img_cell is not None:
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img = img_cell.find('img')
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img = img.get('src').split('base64,')[-1]
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else:
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img = "-1"
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#image_post.append(img)
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# Endchan does not have status, blurb, reputation, signature or feedback
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def set_other_lists():
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status.append("-1")
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reputation.append("-1")
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interest.append("-1")
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sign.append("-1")
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feedback.append("-1")
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# For the original post, get all fields we are interested in
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# get user
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get_user(post_header)
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# get post
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get_post(original_post)
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# get addDate
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get_date(post_header)
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# get user image
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get_user_img(post_header)
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#get first post image
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get_first_img(original_post)
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#no status, interest, reputation, feedback, or signature
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#set_other_lists()
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# Finding the repeated tag that corresponds to the listing of posts
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post_replies = entire_post.find('div', {"class": "divPosts"}).find_all('div', class_ = re.compile('postCell'))
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# For all replies, get all the fields we are interested in
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for ipost in post_replies:
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post_area = ipost.find('div', {"class": "innerPost"})
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# Finding user of the post
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get_user(post_area)
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# getting post date
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get_date(post_area)
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# getting the post content
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get_post(post_area)
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# get first image from post using panel uploads
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get_first_img(post_area)
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# get author avatar
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get_user_img(post_area)
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#set_other_lists()
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# Populate the final variable (this should be a list with all fields scraped)
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#row = (topic, user, status, reputation, interest, sign, post, feedback, addDate, image_user, image_post)
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# Sending the results
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#return row
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# This is the method to parse the Listing Pages (one page with many posts)
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def endchan_listing_parser(soup):
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nm = 0 # *this variable should receive the number of topics
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forum = "Endchan" # 0 *forum name
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board = "-1" # 1 *board name (the previous level of the topic in the Forum categorization tree.
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# For instance: Security/Malware/Tools to hack Facebook. The board here should be Malware)
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author = [] # 2 *all authors of each topic
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topic = [] # 3 *all topics
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views = [] # 4 number of views of each topic
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posts = [] # 5 number of posts of each topic
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href = [] # 6 this variable should receive all cleaned urls (we will use this to do the marge between
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# Listing and Description pages)
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addDate = [] # 7 when the topic was created (difficult to find)
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image_author = [] # 8 all author avatars used in each topic
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# Finding the board (should be just one)
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header = soup.find("header", {"class": "boardHeader"})
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labelName = header.find("p", {"id": "labelName"}).text
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board = cleanString(labelName.strip())
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# Finding the repeated tag that corresponds to the listing of topics
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topics = soup.find('div', {"id": "threadList"}).find('div', {"id": "divThreads"}).find_all('div',
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class_ = re.compile('opCell'))
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# Counting how many topics
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nm = len(topics)
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for itopic in topics:
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post_header = itopic.find('div', {"class": "innerOP"}).find('div', {"class": "opHead"})
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topics = post_header.find('span', {"class": "labelSubject"})
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# Adding the topic to the topic list
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topics = re.sub("\[\w*\]", '', topics)
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topic.append(cleanString(topics))
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# get author avatar
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avatar_img = post_header.find('img', class_ = re.compile('imgFlag'))
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if avatar_img is not None:
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avatar_img = avatar_img.get('src').split('base64,')[-1]
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else:
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avatar_img = "-1"
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image_author.append(avatar_img)
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# Adding the url to the list of urls
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#using linkSelf to get link, because the website is formatted differently.
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link = post_header.find('a', {"class": "linkSelf"}).get('href')
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href.append(link)
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# Finding the author of the topic
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name = post_header.find('a', class_= re.compile('linkName'))
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user = name.strip()
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author.append(cleanString(user))
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# Finding the number of replies
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replies = itopic.find('div', {"class": "divPosts"}).find_all('div', class_ = re.compile('postCell'))
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if replies is not None:
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num_replies = str(len(replies))
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posts.append(cleanString(num_replies))
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else:
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posts.append('-1')
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# No information on number of Views
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views.append('-1')
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#get date topic was added
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dt = post_header.find('span', {"class": "labelCreated"}).text
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dt = dt.strip().split()
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date_time_obj = datetime.strftime(dt[0], '%m-%d-%Y')
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addDate.append(date_time_obj)
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#return organizeTopics(forum, nm, board, author, topic, views, posts, href, addDate, image_author)
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def endchan_links_parser(soup):
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# Returning all links that should be visited by the Crawler
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href = []
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listing = soup.find('div', {"id": "threadList"}).find('div', {"id": "divThreads"}).find_all('div',
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class_ = re.compile('opCell'))
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for a in listing:
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link = a.find('a', {"class": "linkSelf"}).get('href')
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href.append(link)
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return href
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