SCN Vanity App

pip install pandas #For Data Analysis and Data Frames

pip install mechanize #Headless Web Browser

pip install beatifulsoup4 #For Web Scrapping

#coding= utf8

USR = 'YourUserName'

PWD = 'YourPassword'

import sys

import re

import mechanize

from BeautifulSoup import BeautifulSoup

import pandas as pd

reload(sys)

sys.setdefaultencoding("iso-8859-1")

cookies = mechanize.CookieJar()

br = mechanize.Browser()

br.set_cookiejar(cookies)

br.set_handle_robots(False)

res = br.open("http://scn.sap.com/login.jspa")

br.select_form(nr=0)

br["j_username"] = USR

br["j_password"] = PWD

br.submit()

br.select_form(nr=0)

res = br.submit()

result = res.read()

author = re.search("username: \'.*",result)

author = re.sub('username: \'|\'|\,','',author.group(0))

displayname = re.search("displayName: \'.*",result)

displayname = re.sub('displayName: \'|\'|\,','',displayname.group(0))

j = 0

df = pd.DataFrame()

while(1==1):

  try:

  link = "http://scn.sap.com/people/%s/content?filterID="\

        "contentstatus[published]~objecttype~objecttype[blogpost]" %(author)

  if(j>0):

  link = "http://scn.sap.com/people/%s/content?filterID="\

  "contentstatus[published]~objecttype~objecttype[blogpost]&start=%j" %(author,str(j))

  j += 20

  res = br.open(link)

  Titles = []

  Likes = []

  Bookmarks = []

  Comments = []

  Views = []

  soup = BeautifulSoup(res.read())

  list_items = [list_item for list_item in soup.findAll('td',{'class':'j-td-title'})]

  if(len(list_items) == 0):

  break;

  for i in range(0, len(list_items)):

  title = re.search('[^<>]+(?=<)',str(list_items[i]))

  Titles.append(title.group(0))

  list_items = [list_item for list_item in soup.findAll('a',{'class':'j-meta-number'})]

  for i in range(0, len(list_items), 2):

  like = re.sub('<[^>]+>|in.*','',str(list_items[i]))

  bookmark = re.sub('<[^>]+>|in.*','',str(list_items[i+1]))

  Likes.append(int(like))

  Bookmarks.append(int(bookmark))

  list_items = [list_item for list_item in soup.findAll('span',{'title':'Replies'})]

  for i in range(0, len(list_items)):

  comment = re.sub('<[^>]+>|in.*','',str(list_items[i]))

  Comments.append(int(comment))

  list_items = [list_item for list_item in soup.findAll('span',{'title':'Views'})]

  for i in range(0, len(list_items)):

  views = re.sub('<[^>]+>|in.*','',str(list_items[i]))

  Views.append(int(views))

  for i in range(0, len(Titles)):

  df = df.append({'Title': Titles[i], 'Likes': Likes[i], 'Bookmarks': Bookmarks[i],

                 'Comments': Comments[i], 'Views': Views[i]}, ignore_index=True)

  except:

  break

print("Welcome " + displayname + "\n")

sum_row = df[["Views"]].sum()

print("Total number of Views" + " ==> " + str(sum_row.values[0]))

sum_row = df[["Comments"]].sum()

print("Total number of Comments" + " ==> " + str(sum_row.values[0]))

sum_row = df[["Bookmarks"]].sum()

print("Total number of Bookmarks" + " ==> " + str(sum_row.values[0]))

sum_row = df[["Likes"]].sum()

print("Total number of Likes" + " ==> " + str(sum_row.values[0]))

print("\nTop 3 Blogs with most Views")

print("---------------------------")

df = df.sort_values(by=['Views'],ascending=[False])

for i in range(0, 3):

  print(df.iloc[[i]]['Title'].values[0] + " ==> " + str(df.iloc[[i]]['Views'].values[0]))

print("\nTop 3 Blogs with most Comments")

print("---------------------------")

df = df.sort_values(by=['Comments'],ascending=[False])

for i in range(0, 3):

  print(df.iloc[[i]]['Title'].values[0] + " ==> " + str(df.iloc[[i]]['Comments'].values[0]))

print("\nTop 3 Blogs with most Bookmarks")

print("---------------------------")

df = df.sort_values(by=['Bookmarks'],ascending=[False])

for i in range(0, 3):

  print(df.iloc[[i]]['Title'].values[0] + " ==> " + str(df.iloc[[i]]['Bookmarks'].values[0]))

print("\nTop 3 Blogs with most Bookmarks")

print("---------------------------")

df = df.sort_values(by=['Likes'],ascending=[False])

for i in range(0, 3):

  print(df.iloc[[i]]['Title'].values[0] + " ==> " + str(df.iloc[[i]]['Likes'].values[0]))