def Calculate():
try:
news = request.form['inputNews'].lower()
topic = request.form['inputTopic']
category = request.form['inputCategory']
print news + "\t" + topic + "\t" + category
from havenondemand.hodindex import HODClient
client = HODClient(apikey='6b1f8438-56c7-45e0-98a6-6742c1be0d65', apiversiondefault=1)
"""def get_bias(url):
print "Hello"
data = {'url': url}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
print url + " | " + sentiment + " | " + str(score)
return score"""
paper = newspaper.build("http://" + news + ".com", language='en', memoize_articles=False)
url = []
for article in paper.articles:
url.append(article.url)
cumulative_score = 0.0
countNegative = 0
countPositive = 0
countNeutral = 0
"""import multiprocessing as mp
p = mp.Pool(3)
res = p.map(get_bias, url)"""
print newspaper.category
for u in url:
data = {'url': u}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
print u + " | " + sentiment + " | " + str(score)
cumulative_score += score
if sentiment == 'positive':
countPositive += 1
elif sentiment == 'negative':
countNegative += 1
elif sentiment == 'neutral':
countNeutral += 1
print cumulative_score
print cumulative_score/len(url)
except Exception as e:
return json.dumps({'error':str(e)})
return news + topic + category
def wikipediagrabber(filepath):
#make API call, as outlined in https://github.com/HPE-Haven-OnDemand/havenondemand-python
client = HODClient("http://api.havenondemand.com/", "5e8a3841-5bec-43cc-9dac-5e5d0a90bbc9")
r = client.post('extractentities', data={'entity_type': ['people_eng'], 'unique_entities': 'true'},files={'file':open(filepath,'rb')} )
#set variables
myjson = r.json()
identifiers = []
dictionary={}
#iterate through each named entity
for i in range(0, len(myjson['entities'])):
#try statement that only stores named entries with wikipedia descriptions in dictionary
try:
#record duplicate named entities
identifier = myjson['entities'][i]['additional_information']['wikidata_id']
#only add to dictionary if named entity has not already appeared
if identifier not in identifiers:
identifiers.append(identifier)
entry = myjson['entities'][i]['original_text']
dictionary[myjson['entities'][i]['additional_information']['wikidata_id']] = [myjson['entities'][i]['original_text'], wikipedia.summary(entry, sentences = 5), myjson['entities'][i]['additional_information']['wikipedia_eng']]
#do not add to dictionary if they do not have wikipedia pages
except (wikipedia.exceptions.DisambiguationError, wikipedia.exceptions.PageError) as e:
continue
return dictionary
def havenSentiment(text):
"""Takes a string as an input and runs it through the Haven API to gather sentiment analysis and returns it"""
from havenondemand.hodindex import HODClient
import os
key = os.environ.get('havenAPI')
client = HODClient(apikey=key, apiversiondefault=1)
data = {'text': text}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
# return text + " | " + sentiment + " | " + str(score)
return score
# if __name__ == "__main__":
# from twitterGrab import twitterUserGrab
# from twitterGrab import twitterTopicGrab
# print havenSentiment(twitterTopicGrab("python"))
# print havenSentiment(twitterUserGrab("kanyewest"))
def havenSentiment(text):
"""Takes a string as an input and runs it through the Haven API to gather sentiment analysis and returns it"""
from havenondemand.hodindex import HODClient
import os
key = os.environ.get('havenAPI')
client = HODClient(apikey=key, apiversiondefault=1)
data = {'text': text}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
# return text + " | " + sentiment + " | " + str(score)
return score
# if __name__ == "__main__":
# from twitterGrab import twitterUserGrab
# from twitterGrab import twitterTopicGrab
# print havenSentiment(twitterTopicGrab("python"))
# print havenSentiment(twitterUserGrab("kanyewest"))
from havenondemand.hodindex import HODClient
client = HODClient(apikey='API_KEY', apiversiondefault=1)
text = "I love puppies"
data = {'text': text}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
print(text + " | " + sentiment + " | " + str(score))
def Calculate():
try:
news = request.form['inputNews'].lower()
topic = request.form['inputTopic']
category = request.form['inputCategory']
print news + "\t" + topic + "\t" + category
from havenondemand.hodindex import HODClient
client = HODClient(apikey='6b1f8438-56c7-45e0-98a6-6742c1be0d65',
apiversiondefault=1)
"""def get_bias(url):
print "Hello"
data = {'url': url}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
print url + " | " + sentiment + " | " + str(score)
return score"""
paper = newspaper.build("http://" + news + ".com",
language='en',
memoize_articles=False)
url = []
for article in paper.articles:
url.append(article.url)
cumulative_score = 0.0
countNegative = 0
countPositive = 0
countNeutral = 0
"""import multiprocessing as mp
p = mp.Pool(3)
res = p.map(get_bias, url)"""
print newspaper.category
for u in url:
data = {'url': u}
r = client.post('analyzesentiment', data)
sentiment = r.json()['aggregate']['sentiment']
score = r.json()['aggregate']['score']
print u + " | " + sentiment + " | " + str(score)
cumulative_score += score
if sentiment == 'positive':
countPositive += 1
elif sentiment == 'negative':
countNegative += 1
elif sentiment == 'neutral':
countNeutral += 1
print cumulative_score
print cumulative_score / len(url)
except Exception as e:
return json.dumps({'error': str(e)})
return news + topic + category
