import tweepy
from textblob import TextBlob
import sys
import matplotlib.pyplot as plt
import pprint

consumer_key=''
consumer_secret=''
access_token=''
access_token_secret=''

auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
 
# Creation of the actual interface, using authentication
api = tweepy.API(auth)
 
a=int(input('''What you want to do
		1)Display tweets having particular term
		2)Tweet something
		3)Sentimental Analysis of a term/Hashtag
		4)timeline of a particular user'''))


			

def update_status():
	tweet=input('Enter your tweet in 140 words')
	if len(tweet)>140:
		print('Maximum length exceded')
	else:
		api.update_status(tweet)
		print('Tweeted')


def stream_tweets():
	search_for=input('Enter the term/hastag')
	noOfterms=int(input('Number of tweets'))

	tweets=tweepy.Cursor(api.search,q=search_for,lang='English').items(noOfterms)

	for tweet in tweets:
		pprint.pprint(tweet.text)

def timeline():
	screen=input('Enter the username of the user ')
	a='' 
	for status in tweepy.Cursor(api.user_timeline, screen_name=screen).items():
		
		c=status._json['text']
		a=a+c
	with open('all_tweets.txt','w') as f:
		f.write(a)
		f.close()	
	print('Tweets stored in all_tweets.txt file')		


def percentage(part,whole):
	return 100*(float(part)/float(whole))

def sentimental_analysis():
	
	search_for=input('Enter the term/hastag')
	
	noOfterms=int(input('Number of tweets'))
	
	tweets=tweepy.Cursor(api.search,q=search_for,lang='English').items(noOfterms)
	
	positive=0
	negative=0
	neutral=0
	polarity=0

	for tweet in tweets:
		analysis=TextBlob(tweet.text)
		polarity+=analysis.sentiment.polarity

		if analysis.sentiment.polarity==0:
			neutral+=1
		elif analysis.sentiment.polarity>0.00:
			positive+=1
		elif analysis.sentiment.polarity<0.00:
			negative+=1	

	labels = 'Positive', 'Negative', 'Neutral'
	sizes = [positive,negative, neutral]
	colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']
	explode = (0.1, 0, 0)  
	 
	
	plt.pie(sizes, explode=explode, labels=labels, colors=colors,
	        autopct='%1.1f%%', shadow=True, startangle=140)
	 
	plt.axis('equal')
	plt.show()
if a==1:
	stream_tweets()
	
elif a==2:
	update_status()
	
elif a==3:
	sentimental_analysis()
	
elif a==4:
	timeline()
else:
	print('Not a Valid')

b288c558eea1fb40c965eef39e1ea1f6cf025a1f
<mask token>


def update_status():
    tweet = input('Enter your tweet in 140 words')
    if len(tweet) > 140:
        print('Maximum length exceded')
    else:
        api.update_status(tweet)
        print('Tweeted')


def stream_tweets():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    for tweet in tweets:
        pprint.pprint(tweet.text)


def timeline():
    screen = input('Enter the username of the user ')
    a = ''
    for status in tweepy.Cursor(api.user_timeline, screen_name=screen).items():
        c = status._json['text']
        a = a + c
    with open('all_tweets.txt', 'w') as f:
        f.write(a)
        f.close()
    print('Tweets stored in all_tweets.txt file')


<mask token>

<mask token>


def update_status():
    tweet = input('Enter your tweet in 140 words')
    if len(tweet) > 140:
        print('Maximum length exceded')
    else:
        api.update_status(tweet)
        print('Tweeted')


def stream_tweets():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    for tweet in tweets:
        pprint.pprint(tweet.text)


def timeline():
    screen = input('Enter the username of the user ')
    a = ''
    for status in tweepy.Cursor(api.user_timeline, screen_name=screen).items():
        c = status._json['text']
        a = a + c
    with open('all_tweets.txt', 'w') as f:
        f.write(a)
        f.close()
    print('Tweets stored in all_tweets.txt file')


def percentage(part, whole):
    return 100 * (float(part) / float(whole))


def sentimental_analysis():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    positive = 0
    negative = 0
    neutral = 0
    polarity = 0
    for tweet in tweets:
        analysis = TextBlob(tweet.text)
        polarity += analysis.sentiment.polarity
        if analysis.sentiment.polarity == 0:
            neutral += 1
        elif analysis.sentiment.polarity > 0.0:
            positive += 1
        elif analysis.sentiment.polarity < 0.0:
            negative += 1
    labels = 'Positive', 'Negative', 'Neutral'
    sizes = [positive, negative, neutral]
    colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']
    explode = 0.1, 0, 0
    plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct=
        '%1.1f%%', shadow=True, startangle=140)
    plt.axis('equal')
    plt.show()


<mask token>

<mask token>
auth.set_access_token(access_token, access_token_secret)
<mask token>


def update_status():
    tweet = input('Enter your tweet in 140 words')
    if len(tweet) > 140:
        print('Maximum length exceded')
    else:
        api.update_status(tweet)
        print('Tweeted')


def stream_tweets():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    for tweet in tweets:
        pprint.pprint(tweet.text)


def timeline():
    screen = input('Enter the username of the user ')
    a = ''
    for status in tweepy.Cursor(api.user_timeline, screen_name=screen).items():
        c = status._json['text']
        a = a + c
    with open('all_tweets.txt', 'w') as f:
        f.write(a)
        f.close()
    print('Tweets stored in all_tweets.txt file')


def percentage(part, whole):
    return 100 * (float(part) / float(whole))


def sentimental_analysis():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    positive = 0
    negative = 0
    neutral = 0
    polarity = 0
    for tweet in tweets:
        analysis = TextBlob(tweet.text)
        polarity += analysis.sentiment.polarity
        if analysis.sentiment.polarity == 0:
            neutral += 1
        elif analysis.sentiment.polarity > 0.0:
            positive += 1
        elif analysis.sentiment.polarity < 0.0:
            negative += 1
    labels = 'Positive', 'Negative', 'Neutral'
    sizes = [positive, negative, neutral]
    colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']
    explode = 0.1, 0, 0
    plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct=
        '%1.1f%%', shadow=True, startangle=140)
    plt.axis('equal')
    plt.show()


if a == 1:
    stream_tweets()
elif a == 2:
    update_status()
elif a == 3:
    sentimental_analysis()
elif a == 4:
    timeline()
else:
    print('Not a Valid')

import tweepy
from textblob import TextBlob
import sys
import matplotlib.pyplot as plt
import pprint
consumer_key = ''
consumer_secret = ''
access_token = ''
access_token_secret = ''
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
a = int(input(
    """What you want to do
		1)Display tweets having particular term
		2)Tweet something
		3)Sentimental Analysis of a term/Hashtag
		4)timeline of a particular user"""
    ))


def update_status():
    tweet = input('Enter your tweet in 140 words')
    if len(tweet) > 140:
        print('Maximum length exceded')
    else:
        api.update_status(tweet)
        print('Tweeted')


def stream_tweets():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    for tweet in tweets:
        pprint.pprint(tweet.text)


def timeline():
    screen = input('Enter the username of the user ')
    a = ''
    for status in tweepy.Cursor(api.user_timeline, screen_name=screen).items():
        c = status._json['text']
        a = a + c
    with open('all_tweets.txt', 'w') as f:
        f.write(a)
        f.close()
    print('Tweets stored in all_tweets.txt file')


def percentage(part, whole):
    return 100 * (float(part) / float(whole))


def sentimental_analysis():
    search_for = input('Enter the term/hastag')
    noOfterms = int(input('Number of tweets'))
    tweets = tweepy.Cursor(api.search, q=search_for, lang='English').items(
        noOfterms)
    positive = 0
    negative = 0
    neutral = 0
    polarity = 0
    for tweet in tweets:
        analysis = TextBlob(tweet.text)
        polarity += analysis.sentiment.polarity
        if analysis.sentiment.polarity == 0:
            neutral += 1
        elif analysis.sentiment.polarity > 0.0:
            positive += 1
        elif analysis.sentiment.polarity < 0.0:
            negative += 1
    labels = 'Positive', 'Negative', 'Neutral'
    sizes = [positive, negative, neutral]
    colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']
    explode = 0.1, 0, 0
    plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct=
        '%1.1f%%', shadow=True, startangle=140)
    plt.axis('equal')
    plt.show()


if a == 1:
    stream_tweets()
elif a == 2:
    update_status()
elif a == 3:
    sentimental_analysis()
elif a == 4:
    timeline()
else:
    print('Not a Valid')

import tweepy
from textblob import TextBlob
import sys
import matplotlib.pyplot as plt
import pprint

consumer_key=''
consumer_secret=''
access_token=''
access_token_secret=''

auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
 
# Creation of the actual interface, using authentication
api = tweepy.API(auth)
 
a=int(input('''What you want to do
		1)Display tweets having particular term
		2)Tweet something
		3)Sentimental Analysis of a term/Hashtag
		4)timeline of a particular user'''))


			

def update_status():
	tweet=input('Enter your tweet in 140 words')
	if len(tweet)>140:
		print('Maximum length exceded')
	else:
		api.update_status(tweet)
		print('Tweeted')


def stream_tweets():
	search_for=input('Enter the term/hastag')
	noOfterms=int(input('Number of tweets'))

	tweets=tweepy.Cursor(api.search,q=search_for,lang='English').items(noOfterms)

	for tweet in tweets:
		pprint.pprint(tweet.text)

def timeline():
	screen=input('Enter the username of the user ')
	a='' 
	for status in tweepy.Cursor(api.user_timeline, screen_name=screen).items():
		
		c=status._json['text']
		a=a+c
	with open('all_tweets.txt','w') as f:
		f.write(a)
		f.close()	
	print('Tweets stored in all_tweets.txt file')		


def percentage(part,whole):
	return 100*(float(part)/float(whole))

def sentimental_analysis():
	
	search_for=input('Enter the term/hastag')
	
	noOfterms=int(input('Number of tweets'))
	
	tweets=tweepy.Cursor(api.search,q=search_for,lang='English').items(noOfterms)
	
	positive=0
	negative=0
	neutral=0
	polarity=0

	for tweet in tweets:
		analysis=TextBlob(tweet.text)
		polarity+=analysis.sentiment.polarity

		if analysis.sentiment.polarity==0:
			neutral+=1
		elif analysis.sentiment.polarity>0.00:
			positive+=1
		elif analysis.sentiment.polarity<0.00:
			negative+=1	

	labels = 'Positive', 'Negative', 'Neutral'
	sizes = [positive,negative, neutral]
	colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']
	explode = (0.1, 0, 0)  
	 
	
	plt.pie(sizes, explode=explode, labels=labels, colors=colors,
	        autopct='%1.1f%%', shadow=True, startangle=140)
	 
	plt.axis('equal')
	plt.show()
if a==1:
	stream_tweets()
	
elif a==2:
	update_status()
	
elif a==3:
	sentimental_analysis()
	
elif a==4:
	timeline()
else:
	print('Not a Valid')
