def get_sentiment(company_id, text):
alchemyapi = AlchemyAPI()
key_phrases = []
for apikey in engine.get_random_alchemy_credentials():
alchemyapi.apikey = apikey
response = alchemyapi.keywords('text', text, {'sentiment': 1})
if response['status'] == 'OK':
if len(response['keywords']) == 0:
return 0
# related_words = models.RelatedWord.query.filter_by(company_id=company_id).all()
for keyword in response["keywords"]:
if 'sentiment' in keyword:
if keyword['sentiment'].has_key('score'):
key_phrases.append(float(keyword['sentiment']['score']))
elif keyword['sentiment']['type'] == 'neutral':
key_phrases.append(0)
if len(key_phrases) == 0:
return 0
else:
return float("{0:.2f}".format(sum(key_phrases)/len(key_phrases)))
elif response['status'] == 'ERROR' and response['statusInfo'] != 'unsupported-text-language':
print "ERROR: getting sentiment " + response['statusInfo']
# Skip onto the next api key
continue
else:
print "None of the above " + response['statusInfo']
return 0
#Return none when all api keys are exhausted
return None
def generate_concepts_for_company(company_id, tweets):
all_tweets_as_string = ' '.join(tweets)
alchemyapi = AlchemyAPI()
api_error = False
for apikey in engine.get_random_alchemy_credentials():
alchemyapi.apikey = apikey
response = alchemyapi.concepts('text', all_tweets_as_string)
related_words = []
if response['status'] == 'OK':
for concept in response['concepts']:
related_words.append(concept['text'])
elif response['status'] == 'ERROR' and tweets != []:
print "ERROR getting concepts" + response['statusInfo']
api_error = True
# Move onto the next api key
continue
# Return null when all api keys are exhausted
if api_error and len(related_words) == 0:
return None
return related_words
