Scrape most reviewed news and tweet using Python

# Python program to get top 3 trendy news item 
 

import tweepy
import json
from datetime import date, timedelta, datetime
from pymongo import MongoClient
from html.parser import HTMLParser
import re
from pyshorteners import Shortener


NewsArrayIndex = 0
NewsArray = [None] * 3

class MyHTMLParser(HTMLParser):
    
    # This function collects the value
    # of href and stores in NewsArrayIndex 
    # variable
    def handle_starttag(self, tag, attrs):
        
        # Only parse the 'anchor' tag.
        global NewsArrayIndex
        if tag == "a":
           
            # Check the list of defined attributes.
            for name, value in attrs:
               
                # If href is defined, print it.
                if name == "href":
                   
                    # print(value + "\t" + News1)                                   
                    NewsArray[NewsArrayIndex] = value
                   
                    # print(NewsArray)
                    NewsArrayIndex += 1
                    
# This function is the primary place
# to tweet the collected daily news
# News is retrieved from Coll_DailyNewsPlusReview 
# collection (MongoDB collection) This collection
# holds the value of " News Headlines, Its review 
# count, news link" and based upon the review count,
# top most # reviewed news are taken As twitter allows
# only 280 characters, the retrieved news link got
# shortened by using BITLY API Hashtags related to
# the news are added underneath the retrieved top
# 3 news (All together allowed characters are 280)
# Then top 3 news gets tweeted from a credential
# Finally per day basis the tweeted news are stored
# into another collection for audit purposes as well
# as for weekly posting
def tweetDailyNews():
    
    try:
        
        # This is the collection name in mongodb
        cursor_P = db1.Coll_DailyNewsPlusReview.find({"time": date_str})
              
        p0 = cursor_P[0]
        News = p0.get('News')
        sortedNews = sorted(News, key = lambda x: int(x[1]), reverse = True)
        print(sortedNews[0][0]+"--" + sortedNews[0][1],
              sortedNews[1][0] + ".."+ sortedNews[1][1],
              sortedNews[2][0] + ".." + sortedNews[2][1])
        
        hyperlink_format = '<a href ="{link}">{text}</a>'
        parser = MyHTMLParser()
        dailyNews = "Impactful News of the Day" + "\n"
        
        News0 = sortedNews[0][2]
        parser.feed(hyperlink_format.format(link = News0, text = News0))
        
        News1 = sortedNews[1][2]
        print("News1", News1)
        parser.feed(hyperlink_format.format(link = News1, text = News1))
        
        News2 = sortedNews[2][2]
        print(News2)
        parser.feed(hyperlink_format.format(link = News2, text = News2))
        
        # News shortening pattern
        BITLY_ACCESS_TOKEN ="20dab258cc44c7d017bcd1c1f4b24484a37b8de9"
        b = Shortener(api_key = ACCESS_TOKEN) 
        
        NewsArray[0] = re.sub('\n', '', NewsArray[0])
        response1 = b.bitly.short(NewsArray[0]) 
        response1 = response1['url']
        
        NewsArray[1] = re.sub('\n', '', NewsArray[1])
        response2 = b.bitly.short(NewsArray[1]) 
        response2 = response2['url']
         
        NewsArray[2] = re.sub('\n', '', NewsArray[2])
        response3 = b.bitly.short(NewsArray[2]) 
        response3 = response3['url']
        
        news1FewWords = sortedNews[0][0].split()
        dailyNews += news1FewWords[0] + " " 
        + news1FewWords[1] + " " + news1FewWords[2] 
        + "...." + response1 + "\n"
        
        news2FewWords = sortedNews[1][0].split()
        dailyNews += news2FewWords[0] + " " 
        + news2FewWords[1] + " " + news2FewWords[2] 
        + "...." + response2+"\n"
        
        news3FewWords = sortedNews[2][0].split()
        dailyNews += news3FewWords[0] + " " 
        + news3FewWords[1] + " " + news3FewWords[2]
        + "...." + response3 + "\n" + "# bitcoin \
        # cryptocurrency # blockchain # investor # altcoins\
        # fintech # investment"
        print(dailyNews)
        
        status = api.update_status(status = dailyNews)
        if status:
            for i in range(3):
                datas = {}
                datas['time'] = str(date.today())
                datas['posted_as'] = i
                datas['news'] = sortedNews[i][0]
                datas['shortenedlink'] = NewsArray[i]
                datas['reviewcount'] = sortedNews[i][1]
                datas['link'] = sortedNews[i][2]
                db1.Collection_tweeted_news.insert(datas)
                 
             
    except Exception as e:
        print(e)
        print("Error in getting today news data", str(date_str))

        
# Driver Code
News1 = ' '
News2 = ' '

date_str = str(date.today())
print("today", date_str)
client = MongoClient('mongodb://localhost:27017/')

# Connect your database here
db1 = client.xxxx 

# credentials to tweet
consumer_key ="xxxx"
consumer_secret ="xxxx"
access_token ="xxxx"
access_token_secret ="xxxx"
 
# authentication of consumer key and secret 
auth = tweepy.OAuthHandler(consumer_key, consumer_secret) 
 
# authentication of access token and secret 
auth.set_access_token(access_token, access_token_secret) 
api = tweepy.API(auth,
                 wait_on_rate_limit = True,
                 wait_on_rate_limit_notify = True)   
    
tweetDailyNews()