# from __future__ import division from nltk import sent_tokenize, word_tokenize, pos_tag from nltk.probability import FreqDist from nltk.corpus import stopwords import nltk import codecs import base64 nltk.download('stopwords') # faceapp_file = open('faceapp.txt','r') with open('tos_file/faceapp.txt', 'r') as faceapp_file: faceapp_text = faceapp_file.read() faceapp_text_list = faceapp_text.split("\n\n") with open('treaty_file/russia-estonia.txt', 'r') as russia_file: russia_text = russia_file.read() russia_text_list = russia_text.split("\n\n") #tos stopwords tos_default_stopwords = set(stopwords.words('english')) tos_custom_stopwords = set(codecs.open('stopwords.txt', 'r').read().splitlines()) tos_all_stopwords = tos_default_stopwords | tos_custom_stopwords #treaty stopwords t_default_stopwords = set(stopwords.words('english')) t_custom_stopwords = set(codecs.open('t_stopwords.txt', 'r').read().splitlines()) t_all_stopwords = t_default_stopwords | t_custom_stopwords # multi-line string HTML print(''' ''') #wrapper print('
') #insert an image # https://upload.wikimedia.org/wikipedia/commons/1/15/Joffe_signing_the_Treaty_of_Tartu.jpg FaceApp_img_url = base64.b64encode(open('img/faceapp_logo.png', 'rb').read()).decode('utf-8') FaceApp_image = '
FaceApp
'.format(FaceApp_img_url) print(FaceApp_image) #info box print('
') infotext = [('Name of Service', 'FaceApp'), ('Country of Origin', 'Russia'), ('Initial release', 'December 31, 2016'), ('Type', 'Image editing'), ('Word Counts', '5,392'), ('Original Source', 'link'), ('Description', 'FaceApp is a mobile application for iOS and Android developed by Russian company Wireless Lab. The app generates highly realistic transformations of human faces in photographs by using neural networks based on artificial intelligence. The app can transform a face to make it smile, look younger, look older, or change gender.')] for title, info in infotext: print('
{0}
{1}

'.format(title, info)) print('
') print('''
  • verb
  • noun
  • adjective
  • adverb
  • stopwords
    • ''') #ToS text print('
    ') tokenized_all = [] for paragraph in faceapp_text_list: tokenized = word_tokenize(paragraph) tokenized_all += tokenized # add to the tokenized_all tagged = pos_tag(tokenized) print('

    ') for word, pos in tagged: print('{2}'.format(pos.replace('PRP$', 'PRPS').replace('.', 'dot').replace(',', 'comma').replace('(', 'marks').replace(')', 'marks').replace(':', 'marks').replace(';', 'marks'), word.replace('’', 'apostrophe').replace('.', 'dot').replace(',', 'comma').replace('(', 'marks').replace(')', 'marks').replace(':', 'marks').replace(';', 'marks').lower(), word)) print('

    ') print('
    ') #tos top words list print('
    Frequent words
    ') tokens_without_stopwords = nltk.FreqDist(words.lower() for words in tokenized_all if words.lower() not in tos_custom_stopwords) frequency_word = FreqDist(tokens_without_stopwords) top_words = tokens_without_stopwords.most_common(30) for chosen_words, frequency in top_words: print('
     {} ({})
    '.format(chosen_words, frequency)) print('
    ') # at the end of wrapper print('') print('') print('''''')