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Bachir Soussi Chiadmi
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# function pour stocker les mots
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import nltk
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from duckduckpy import query
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import random
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from googletrans import Translator
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from nltk.corpus import wordnet
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import codecs
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# ------------------ #
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# en-tête du script > déclaration des fonctions et des variables
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# ------------------ #
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# on crée une liste pour stocker tous les mots
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all_words = []
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sentences = []
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# fonction qui extrait les mots et les stockent dans une liste
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def words_extract( str ):
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tokens = nltk.word_tokenize( str )
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words = []
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for word, pos in nltk.pos_tag(tokens):
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if pos == 'NN':
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words.append(word)
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return words
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# fonction qui génère un nombre aléatoire à partir de la liste de mots pour pouvoir choisir un mot
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def rand_words( list ):
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# test si la longueur du tableau est egal à zero
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list_len = len( list )
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if list_len != 0:
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ran_num = random.randint(0,list_len-1)
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return ran_num
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else:
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return 0;
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# fonction pour chercher dans duckduckgo
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def srch_engine( list, num ):
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if len(list) != 0:
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print('ok')
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if list not in all_words:
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srch = query(list[num], container='dict')
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res = srch['related_topics'][0]['text']
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return res
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else:
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srch = query(all_words[num], container='dict')
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res = srch['related_topics'][0]['text']
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return res
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else:
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print('pas ok', num, len(all_words))
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if num < len(all_words) and num >= 0 :
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srch = query(all_words[num], container='dict')
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res = srch['related_topics'][0]['text']
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return res
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else:
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syn = wordnet.synsets('computer')
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num = random.randint(0,len(syn)-1)
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print(num)
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res = syn[num].definition()
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return res
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# fonction pour générer des définitions avec wordnet
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def words_gen(list, num):
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if len(list) != 0:
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print('ok')
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if list not in all_words:
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syn = wordnet.synsets(list[num])
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num = random.randint(0,len(syn)-1)
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print(num)
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res = syn[num].definition()
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return res
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else:
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syn = wordnet.synsets(all_words[num])
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num = random.randint(0,len(syn)-1)
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print(num)
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res = syn[num].definition()
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return res
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else:
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print('pas ok')
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if num < len(all_words) and num >= 0:
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syn = wordnet.synsets(all_words[num])
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num = random.randint(0,len(syn)-1)
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print(num)
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res = syn[num].definition()
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return res
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else:
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syn = wordnet.synsets('computer')
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num = random.randint(0,len(syn)-1)
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print(num)
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res = syn[num].definition()
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return res
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# fonction principale
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# ------------------ #
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# corps du script > appel des fonctions, lecture de la source
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# ------------------ #
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with open('input.txt') as f:
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sentences = f.read().splitlines()
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num = rand_words(sentences)
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# phrase de départ
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sentence = sentences[num]
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sentence.encode('utf-8')
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sentence.replace("(...$)/g", "")
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# ------------------- #
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# niveau 1
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# ------------------- #
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# 1
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print('\n')
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print('1. ' + sentence)
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# extraction des mots de la phrase de départ
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words = words_extract( sentence )
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# 1.2 on ajoute à all_words tous les mots trouver
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print(words)
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if words not in all_words:
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all_words.extend(words)
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print(all_words)
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# 1.3 - génération du nombre pour le choix du mot
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ran_num = rand_words( words )
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print(ran_num)
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# ------------------- #
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# niveau 2
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# ------------------- #
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# 2 - on va chercher une phrase à partir du mot sélectionné
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sentence2 = words_gen(words, ran_num)
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sentence2.encode('utf-8')
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sentence2.replace("(...$)/g", "")
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print('\t 2. ' + sentence2)
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# extraction des mots de la phrase 2
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words = words_extract( sentence2 )
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# 2.2
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print(words)
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if words not in all_words:
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all_words.extend(words)
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print(all_words)
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# 2.3 - génération du nombre pour le choix du mot
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ran_num = rand_words( words )
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print(ran_num)
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# ------------------- #
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# niveau 3
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# ------------------- #
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# 3 - on va chercher une phrase à partir du mot sélectionné
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sentence3 = srch_engine(words, ran_num)
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sentence3.encode('utf-8')
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sentence3.replace("(...$)/g", "")
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print('\t\t 3. ' + sentence3)
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# extraction des mots de la phrase 2
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words = words_extract( sentence3 )
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# 3.2
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print(words)
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if words not in all_words:
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all_words.extend(words)
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print(all_words)
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# 3.3 - génération du nombre pour le choix du mot
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ran_num = rand_words( words )
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print(ran_num)
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# ------------------- #
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# niveau 4
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# ------------------- #
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# 4 - on va chercher une phrase à partir du mot sélectionné
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sentence4 = words_gen(words, ran_num)
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sentence4.encode('utf-8')
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sentence4.replace("(...$)/g", "")
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print('\t\t\t 4. ' + sentence4)
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# extraction des mots de la phrase 2
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words = words_extract( sentence4 )
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# 4.2
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print(words)
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if words not in all_words:
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all_words.extend(words)
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print(all_words)
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# 4.3 - génération du nombre pour le choix du mot
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ran_num = rand_words( words )
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print(ran_num)
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# ------------------- #
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# niveau 5
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# ------------------- #
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# 5 - on va chercher une phrase à partir du mot sélectionné
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sentence5 = srch_engine(words, ran_num)
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sentence5.encode('utf-8')
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sentence5.replace("(...$)/g", "")
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print('\t\t\t\t 5. ' + sentence5)
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# extraction des mots de la phrase 2
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words = words_extract( sentence5 )
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# 5.2
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print(words)
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if words not in all_words:
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all_words.extend(words)
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print(all_words)
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# 5.3 - génération du nombre pour le choix du mot
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ran_num = rand_words( words )
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print(ran_num)
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# ------------------- #
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# niveau 6
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# ------------------- #
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# 6 - on va chercher une phrase à partir du mot sélectionné
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sentence6 = words_gen(words, ran_num)
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sentence6.encode('utf-8')
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sentence6.replace("(...$)/g", "")
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print('\t\t\t\t\t 6. ' + sentence6)
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# extraction des mots de la phrase 2
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words = words_extract( sentence6 )
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# 6.2
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print(words)
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if words not in all_words:
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all_words.extend(words)
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print(all_words)
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# 6.3 - génération du nombre pour le choix du mot
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ran_num = rand_words( words )
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print(ran_num)
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# ------------------- #
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# écriture du fichier
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# ------------------- #
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translator = Translator()
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translations = translator.translate([sentence, sentence2, sentence3, sentence4, sentence5, sentence6], dest='fr')
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i = 0
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for translation in translations:
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i += 1
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#print(i)
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# on ouvre un fichier
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file = open('ola#5doc/jeremie_nuel/sources/output.txt', 'a')
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# on l'écrit
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file.write('\n\n' + str(i) + '. ' + translation.text )
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file.write('\n\n')
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file.write('--------------- + ----------------')
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file.close()
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print('fichier écrit')
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