def analyze(handle):
twitter_consumer_key = ''
twitter_consumer_secret = ''
twitter_access_token = ''
twitter_access_secret = ''
twitter_api = twitter.Api(consumer_key=twitter_consumer_key, consumer_secret=twitter_consumer_secret, access_token_key=twitter_access_token, access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
text = ""
for status in statuses:
if (status.lang =='en'): #English tweets
text += status.text.encode('utf-8')
pi_username = ''
pi_password = ''
personality_insights = PersonalityInsights(username=pi_username, password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
# Interact with Twitter API
twitter_api = twitter.Api(consumer_key = twitter_consumer_key, consumer_secret = twitter_consumer_secret,
access_token_key = twitter_access_token,
access_token_secret = twitter_access_secret)
# this will retrieve user status
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=1200, include_rts=False)
# this will be used to store the concatenated twitter posts
text = ""
for status in statuses:
if (status.lang == 'en'):
text += status.text.encode('utf-8')
# The IBM Bluemix credentials for Personality Insights
pi_username = username
pi_password = password
personality_insights = PersonalityInsights(username = pi_username, password = pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
twitter_consumer_key = 'kRCutYPdwXamqjWOMp8ovtAsM'
twitter_consumer_secret = 'wYxVJOxAJTEgrvkzrK794sevWMip0puIAvF9ddG9vkSvlKPITD'
twitter_access_token = '487095762-dwN6UmHQQjC3xtTyluY2x07rpp9DMODfDccP2FqZ'
twitter_access_secret = '8rnOZ5djDRFLcuNHl6CpfENFctxf7UdNAqRkw4pfUzGxM'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses=twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
text = ""
for status in statuses:
if(status.lang == 'en'):
text += status.text.encode('utf-8')
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username, password=pi_password)
pi_result = personality_insights.profile(text);
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'AQZTpudfZb2BG0jLeMX4JeEoA'
twitter_consumer_secret = 'OGYEV5aDs5N3hQoGLLRGkJ9UnDydkAEgsSvrrHfulK9cyCr0uf'
twitter_access_token = '886288195494838272-I3cEYrOCRJEqBDOxM6PPZCK5rvdwYXm'
twitter_access_secret = 'tYsVWxc17COz2fvky1R6ijAx9I8klsJPmk1HS0bIp5fth'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi.u, password=pi.p).profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
twitter_consumer_key = '0UAUzgrJqnbEHX8e6D6oeqAbT'
twitter_consumer_secret = 'h2fczsDeMWgpXovgpZwsJ7zLtOknd3QRuDGrXWucpEVAmEKHwv'
twitter_access_token = '839931355991535621-KiPSBgOFHHXVXj9XhYrGF1StFwR9usJ'
twitter_access_secret = 'PiEbJp9qhpUblGU2MdphEdNE7TszzgxsASIj8xIWUiiCV'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
text = ""
for status in statuses:
if (status.lang == 'en'): #English tweets
text += status.text.encode('utf-8')
#The IBM Bluemix credentials for Personality Insights!
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
twitter_consumer_key = 'EAmGMyOSwEAZpHo0lptAZ2iVN'
twitter_consumer_secret = 'iyY3miy99t7bKIw74uis8gwBZPnmcyhfqQUjBibiWP3a0ZmD2i'
twitter_access_token = '303258207-WwHLiL9YKBRDQQCTKOgqeAZTT0VXB0UQ0XhBBBCM'
twitter_access_secret = '85EK988Vj1G0mA3jHif8dgkgemWaqe8mmdCczH0AlCJ8y'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=2,
include_rts=False)
text = ""
for s in statuses:
if s.lang == 'en':
print(s.text)
text += s.text
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
twitter_consumer_key = os.environ['TWITTER_CONSUMER_KEY']
twitter_consumer_secret = os.environ['TWITTER_CONSUMER_SECRET']
twitter_access_token = os.environ['TWITTER_ACCESS_TOKEN']
twitter_access_secret = os.environ['TWITTER_ACCESS_SECRET']
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
text = ""
for status in statuses:
if (status.lang == 'en'):
text += status.text
pi_username = os.environ['WATSON_PI_USERNAME']
pi_password = os.environ['WATSON_PI_PASSWORD']
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=consumer_key,
consumer_secret=consumer_secret,
access_token_key=access_token,
access_token_secret=access_secret)
#Retrieving the last 200 tweets from a candidate1
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi_username,
password=pi_password).profile(text)
#Returning the Watson PI API results
return pi_result
def __init__(self, handle):
self.handle = handle
twitter_consumer_key = 'DJNYG9zMErdfOu6pEuyP6G42l'
twitter_consumer_secret = 'goURqOB0vN5BQvVQvcKTLkrIge9mjJkBV32pVeKK4zNgNAbRZw'
twitter_access_token = '947704874409578498-FJAbBVEoqTd3Q2Wal0HpUaJCw2CIzDO'
twitter_access_secret = 'pOxfJ8gecYnNldX9Thq2ydERYEnBuqr0zvWvgFGTemZnQ'
pi_username = '******'
pi_password = '******'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=self.handle,
count=200,
include_rts=False)
text = ""
for status in statuses:
if (status.lang == 'en'):
text += status.text #.encode('utf-8')
#py3 does not need the encode
#creating instace of Watson API
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
#anaylze the body of text retrieved from Twitter
self.pi_result = personality_insights.profile(text)
def analyze(handle):
twitter_consumer_key = consumer_key
twitter_consumer_secret = consumer_secret
twitter_access_token = access_token
twitter_access_secret = access_secret
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
# Enter credentials from IBM Bluemix Watson Personality Insights
pi_username = username
pi_password = password
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'bn2Yeb7AsbVORjDH7wbcJIhzm'
twitter_consumer_secret = 'A3XWXGCVC0i5f6u2oDuhzqmf96XQWtdArsVGmCM95SzrWdc4xA'
twitter_access_token = '614159902-sh3Vc2NhX2HkR2pIhUWVuj5T21LnzpfHJj3IYxyc'
twitter_access_secret = 'LsX9xHjEku0xmgViiZPv3zsaCy3tuqnlom8rBFpyyBvnD'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi.u, password=pi.p).profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
twitter_consumer_key = 'bGdNXwpmwC5HZfkeAaBxlD2W8'
twitter_consumer_secret = '5KEUc9otby7ZyEPq6nRBKGtdg1O1FyF2e88aY64ZvjX3K4LMFq'
twitter_access_token = '65173395-LN8bPsAjqIHrFtT1JXqLGKeSiKI9Zl1fokmhbJNEI'
twitter_access_secret = 'piehxmwFJuAoACRiML6YGOlOQQl4vvzgZ7S6QjOv2PBji'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
text = (b'')
for status in statuses:
if (status.lang == 'en'):
text += status.text.encode('utf8')
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'ADD YOUR CONSUMER KEY HERE'
twitter_consumer_secret = 'ADD YOUR CONSUMER SECRET HERE'
twitter_access_token = 'ADD YOUR ACCESS TOKEN HERE'
twitter_access_secret = 'ADD YOUR ACCESS SECRET HERE'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang =='en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi.u, password=pi.p).profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
# Get user's last 200 tweets
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
# Convert tweet from Unicode to UTF-8
# Append UTF-8 encoded tweets to the text variable
text = ""
for status in statuses:
if (status.lang == 'en'):
text += status.text.encode('utf-8')
# Initialize IBM Bluemix credentials for Personality Insights
pi_username = ''
pi_password = ''
# Initialize PersonalityInsights
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
# Analyze tweets
pi_result = personality_insights.profile(text)
# Return results
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'aGYdej7DSjm6cI5vzHaqk3jY0'
twitter_consumer_secret = 'AtY8BCzXbTCClswe0jFtWwD4yMDUWP8XTC5pDr0RiEx7jtIBdv'
twitter_access_token = '1425486745-TOs5Gajq44ofObjxC215Bz1LyQ49WOHBGI43MAM'
twitter_access_secret = 'AzW5qRsLv9grVSWqHz8S56ktEebm8SSHuCfeuQ5r5csIX'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=300,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
#Analyzing the 200 tweets with the Watson PI API
pi_result = personality_insights.profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
#This code should include the Twitter credentials, IBM credentials,
#statuses, and Personality Insights results
twitter_consumer_key = 'SSr4gQVk57aoo2Nf4WHWjSnN9'
twitter_consumer_secret = 'p7VAgFeMlbJuINVXklOxa6bepU8SMKXTfrJYrBYfwTvb6AcKHa'
twitter_access_token = '1365454350-DJJRdfYfrntQg25TlwbCMV0v92YDp4x0CIOpRU8'
twitter_access_secret = 'mQdeTSfr7Cvh4zSRxGphwusfVEab4otChcKaGuziC2qyD'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key, consumer_secret=twitter_consumer_secret, access_token_key=twitter_access_token, access_token_secret=twitter_access_secret)
statuses=twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
text = ""
for status in statuses:
if (status.lang =='en'): #English tweets
text += status.text.encode('utf-8')
#The IBM Bluemix credentials for Personality Insights!
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username, password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
twitter_consumer_key = 'cXpt4ecNmEN7UujnnDZCTxv9U'
twitter_consumer_secret = 'RyDbE95mi4qBRUkQOgnUY079Gr0S0a8HoFhVaRvf8ewsOEenzF'
twitter_access_token = '849260818453737473-dbfMiKDQZpOB6Z4IFRTRlTaLXIcrGqu'
twitter_access_secret = 'GHD8wl0iB2EtoF4RfCOYx4kRtf8gPNEqJLVfg940kabnb'
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
text = ""
for status in statuses:
if (status.lang == 'en'):
text += status.text.encode('utf-8')
pi_username = '******'
pi_password = '******'
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
CONSUMER_KEY = ''
CONSUMER_SECRET = ''
OAUTH_TOKEN = ''
OAUTH_TOKEN_SECRET = ''
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(OAUTH_TOKEN, OAUTH_TOKEN_SECRET)
api = tweepy.API(auth)
print(api)
statuses = api.user_timeline(screen_name=handle, count=100)
text = ""
for status in statuses:
text += (status._json)['text']
#ibm bluemix personal insight credentials
pi_username = ''
pi_password = ''
personality_insights = PersonalityInsights(username=pi_username,
password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'IneKk1d3i6O0lo5ZZbM4EEfK7'
twitter_consumer_secret = 'gffvWRNmNF9ZwHm0XPNZ9SFb6JsA0d7jR64BxQSiz49ro3VtVh'
twitter_access_token = '15281154-OuJBpU0ns2yhwhbOlMutCFLBBNDwP9d05PzUfzotO'
twitter_access_secret = 'muYF4xiuTZJHb7b2SyPLFfrsfbymFa04j985ofWhBiBmx'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang =='en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi.u, password=pi.p).profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = ''
twitter_consumer_secret = ''
twitter_access_token = '-'
twitter_access_secret = ''
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
text = ""
for s in statuses:
if (s.lang =='en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username="******", password="******").profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
twitter_consumer_key= input('Twitter consumer key: \n')
twitter_consumer_secret = input('Twitter consumer secret: \n')
twitter_access_token= input('Twitter Access Token: \n')
twitter_access_secret= input ('Twitter API: \n')
twitter_api = twitter.Api(consumer_key=twitter_consumer_key, consumer_secret=twitter_consumer_secret, access_token_key=twitter_access_token, access_token_secret=twitter_access_secret)
#Test
# handle = "@realdonaldtrump"
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
text = ""
for status in statuses:
# print status.text
if (status.lang =='en'): #English tweets
text += status.text.encode('utf-8')
pi_username = ''
pi_password = ''
personality_insights = PersonalityInsights(username=pi_username, password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'eUYIWnmgkJ8qj5GGfJenojIqR'
twitter_consumer_secret = 'ktHMKwAjDdxsILooxrK8awdwEmgAzBRB7FWtxImwJQuspFm39P'
twitter_access_token = '3815186718-jDm0o3GzcABtJ9PJmpAcKxN661KNdwwHrXRLAlI'
twitter_access_secret = 'ew62OaApFrEZJt1wZtw29XTc5QiqJFL6Z1A2xPFD47goD'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_username = '******'
pi_password = '******'
pi_result = PersonalityInsights(username=pi_username,
password=pi_password).profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'bXerZzt8GanD42o7kFHb0VPe3'
twitter_consumer_secret = 'gHr7A2PJCIX08bv8ZmyxuQLmuRva5w5bxvoWUKRmrmh3iJxuFO'
twitter_access_token = '211174890-8nY4AN2ZtZay6HnEchhmOrFgZSBLN5Ypxu13mSTG'
twitter_access_secret = 'TqhSFF6K90e4FncJ048JZYjsxSBefR6YoQ4H3OwNnLC0f'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi.u, password=pi.p).profile(text)
#Returning the Watson PI API results
return pi_result
def analyze(handle):
#The Twitter API credentials
twitter_consumer_key = 'fUsUxkx9MgobZhpSJi2qZii60'
twitter_consumer_secret = 'atzAGdDGycm7K5R6odlIwxX1Ohv04tGGkenL4Lf4jarg1PMwUm'
twitter_access_token = '2431135844-LqVC9YhOjvaapOpAaFWs3X1mhU3G243nCBsZzkw'
twitter_access_secret = 'FXM5d6o8Xf6WiE9ihfdwYkdjgAjojYVNifYwnaKcBx5Lh'
#Invoking the Twitter API
twitter_api = twitter.Api(consumer_key=twitter_consumer_key,
consumer_secret=twitter_consumer_secret,
access_token_key=twitter_access_token,
access_token_secret=twitter_access_secret)
#Retrieving the last 200 tweets from a user
statuses = twitter_api.GetUserTimeline(screen_name=handle,
count=200,
include_rts=False)
#Putting all 200 tweets into one large string called "text"
text = ""
for s in statuses:
if (s.lang == 'en'):
text += s.text.encode('utf-8')
#Analyzing the 200 tweets with the Watson PI API
pi_result = PersonalityInsights(username=pi.u, password=pi.p).profile(text)
#Returning the Watson PI API results
return pi_result
def analyzeUser(text):
watson_username = '******'
watson_password = '******'
watson_result = PersonalityInsights(username=watson_username,
password=watson_password).profile(text)
return watson_result
def analyze(handle):
statuses = twitter_api.GetUserTimeline(screen_name=handle, count=200, include_rts=False)
text= ""
for status in statuses:
if status.lang=='en':
text += status.text.encode('utf-8')
personality_insights = PersonalityInsights(username=pi_username, password=pi_password)
pi_result = personality_insights.profile(text)
return pi_result
def analyze(text):
# Watson PI API credentials
watson_username = '******'
watson_password = '******'
watson_result = PersonalityInsights(username=watson_username, password=watson_password).profile(text)
return watson_result
def get_pi_client():
try:
# IBM Bluemix credentials for Personality Insights
pi_username = os.environ['PI_USERNAME']
pi_password = os.environ['PI_PASSWORD']
except KeyError:
sys.stderr.write("PI_* environment variables not set\n")
sys.exit(1)
# Create Personality Insights instance
personality_insights = PersonalityInsights(username=pi_username, password=pi_password)
return personality_insights
def analyze_tweets(self):
"""
Uploads the string of tweets to the Personality Insights AI of Watson
to receive the values of the personality traits.
"""
personality_insights = PersonalityInsights(username=self.pi_username,
password=self.pi_password)
twitter_messages = ""
for status in self.statuses:
if (status.lang == 'en'):
twitter_messages += str(status.text.encode('utf-8')) + " "
self.pi_result = personality_insights.profile(twitter_messages)
def watson(commentlist, submissionlist):
print()
from watson_developer_cloud import PersonalityInsightsV2 as PersonalityInsights
from IBM_Watson import PIusername, PIpassword
if PIusername == '' or PIpassword == '':
print("Watson Analysis was requested, but the password and username seem to be empty")
return
print('\033[92m' + "[+] IBM Watson Personality Insights Results" + '\033[0m')
def flatten(orig):
data = {}
for c in orig['tree']['children']:
if 'children' in c:
for c2 in c['children']:
if 'children' in c2:
for c3 in c2['children']:
if 'children' in c3:
for c4 in c3['children']:
if (c4['category'] == 'personality'):
data[c4['id']] = c4['percentage']
if 'children' not in c3:
if (c3['category'] == 'personality'):
data[c3['id']] = c3['percentage']
return data
text = ""
for comment in commentlist:
text += comment['data']['body']
personality_insights = PersonalityInsights(username=PIusername, password=PIpassword)
pi_result = personality_insights.profile(text)
flattened_result = flatten(pi_result)
helperlist = []
for key in flattened_result.keys():
helperlist.append(len(key))
maxlen_key = max(helperlist)
for key in flattened_result.keys():
print("- ", ("{:<%d}" % maxlen_key).format(key), ":", end="")
value = "%.1f%%" % (flattened_result[key] * 100)
print(("{:>4}").format(value))