Esempio n. 1
0
    def test_people(self):
        test_data = 'Barack Obama is scheduled to give a talk next Saturday at the White House.'
        response = people(test_data)
        self.assertTrue(isinstance(response, list))
        sorted_response = sorted(response, key=lambda x: x['confidence'], reverse=True)
        self.assertTrue(sorted_response[0]['text'] == 'Barack Obama')

        test_data = [test_data] * 2
        response = people(test_data)
        self.assertTrue(isinstance(response, list))
        sorted_response = [sorted(arr, key=lambda x: x['confidence'], reverse=True) for arr in response]
        self.assertEqual(len(sorted_response), 2)
        self.assertTrue(sorted_response[0][0]['text'] == 'Barack Obama')
Esempio n. 2
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    def test_people(self):
        test_data = 'Barack Obama is scheduled to give a talk next Saturday at the White House.'
        response = people(test_data)
        self.assertTrue(isinstance(response, list))
        sorted_response = sorted(response,
                                 key=lambda x: x['confidence'],
                                 reverse=True)
        self.assertTrue(sorted_response[0]['text'] == 'Barack Obama')

        test_data = [test_data] * 2
        response = people(test_data)
        self.assertTrue(isinstance(response, list))
        sorted_response = [
            sorted(arr, key=lambda x: x['confidence'], reverse=True)
            for arr in response
        ]
        self.assertEqual(len(sorted_response), 2)
        self.assertTrue(sorted_response[0][0]['text'] == 'Barack Obama')
Esempio n. 3
0
def keywords(blob): 
    things = []
    indicoio.config.api_key = 'ab83001ca5c484aa92fc18a5b2d6585c'
    people = indicoio.people(blob)
    for person in people: 
    	if person['confidence'] > 0.5: 
    		things.append(person['text'])		

    places = indicoio.places(blob)
    for place in places: 
    	if place['confidence'] > 0.5: 
    		things.append(place['text'])	
    print(things)
    blob = parse_stop_words(blob)
    tfdic = tf(blob)
    things.append(list(tfidf(tfdic, idf(tfdic, blob)).keys()))
    things = list(set(source_list))
    return things
Esempio n. 4
0
#with open('textfile.txt', 'r') as myfile:
#   data = myfile.read().replace('\n', '')
#print(data)
import os
import indicoio

# reads from the file which contains the audio to speech content
__location__ = os.path.realpath(
    os.path.join(os.getcwd(), os.path.dirname(__file__)))
file_contents = open(os.path.join(__location__, "textfile.txt"))
text = file_contents.read()

# next, feed it into the ML API
indicoio.config.api_key = 'd08fbca96c4341957f0a8a0b21d08b5d'
print("Political Allegiance: ")
print(indicoio.political(text))
print("\n")
print("Key Words: ")
print(indicoio.keywords(text, version=2))
print("\n")
print("Important Persons: ")
print(indicoio.people(text))
print("\n")
print("Significant Locations: ")
print(indicoio.places(text))
print("\n")
print("Relevant Organizations: ")
print(indicoio.organizations(text))