import nltk
#import feedparser
#import wikipedia
from duckduckpy import query
import random

#https://jcutrer.com/howto/dev/python/python-tutorial-howto-parse-rss-headlines
#feed = feedparser.parse('http://feeds.feedburner.com/time/scienceandhealth?format=xml')

#print(feed['title'][0])
#print(feed['feed']['title'][0])
#print (type(feed))

sentence = "Encoded inside a microchip are the patterns of my fingertips"

print('\n')
print(sentence)

tokens = nltk.word_tokenize(sentence)

words = []

for word, pos in nltk.pos_tag(tokens):
    if pos == 'NN':
        words.append(word)

print('\n')
print(words)

list_len = len(words)
ran_num = random.randint(0,list_len-1)
print(ran_num)

res = query(words[ran_num], container='dict')
print('\n\t' + res['related_topics'][0]['text'])

tokens = nltk.word_tokenize(res['related_topics'][0]['text'])

words = []

for word, pos in nltk.pos_tag(tokens):
    if pos == 'NN':
        words.append(word)

print('\n')
print(words)

list_len = len(words)
ran_num = random.randint(0,list_len-1)
print(ran_num)

res = query(words[ran_num], container='dict')
print('\n\t\t' + res['related_topics'][0]['text'])

tokens = nltk.word_tokenize(res['related_topics'][0]['text'])

words = []

for word, pos in nltk.pos_tag(tokens):
    if pos == 'NN':
        words.append(word)

print('\n')
print(words)

list_len = len(words)
ran_num = random.randint(0,list_len-1)
print(ran_num)

res = query(words[ran_num], container='dict')
print('\n\t\t\t' + res['related_topics'][0]['text'])