Update topics_extraction.py

topics_extraction.py

@@ -28,8 +28,8 @@ lemmatizer = WordNetLemmatizer()
 evType_stop = set(nltk.corpus.stopwords.words('english'))
 
 # read configuration file
-config = configparser.ConfigParser()
-config.read('myproject.ini')
+# config = configparser.ConfigParser()
+# config.read('myproject.ini')
 
 # initialize flask object
 app = Flask(__name__)
@@ -37,31 +37,31 @@ app = Flask(__name__)
 
 ### files to be load
 
-tag_similarModel_path = config['path']['tag_similar_model'] #word2vec model
-tag_trigram_path = config['path']['tag_trigram'] # trigram phraser
-tag_bigram_path = config['path']['tag_bigram'] # bigram phraser
+tag_similarModel_path = "word2vec.model" #config['path']['tag_similar_model'] #word2vec model
+tag_trigram_path = "tri_phrases.txt"#config['path']['tag_trigram'] # trigram phraser
+tag_bigram_path = "bi_phrases.txt"#config['path']['tag_bigram'] # bigram phraser
 
 tag_similarModel = Word2Vec.load(tag_similarModel_path)
 tag_trigram_phraser = Phraser.load(tag_trigram_path)
 tag_bigram_phraser = Phraser.load(tag_bigram_path)
 
 # load stopword file
-file2 = open(config['path']['tag_stopword'], "r+")
+file2 = open("stopwords_tag.txt", "r+")
 data2 = file2.read()
 stopword_tag = data2.split(",")
 
 # load vocabulary of single words
-file3 = open(config['path']['tag_vocabSingle'], "r+")
+file3 = open("vocabSingle.txt", "r+")
 data3 = file3.read()
 vocab1 = data3.split(",")
 
 # load vocabulary of words of length more than 2
-file4 = open(config['path']['tag_vocabMulti'], "r+")
+file4 = open("vocabMulti.txt", "r+")
 data4 = file4.read()
 vocab2 = data4.split(",")
 
 # load vocabulary of words of length 2
-file6 = open(config['path']['tag_vocabDouble'], "r+")
+file6 = open("vocabDouble.txt", "r+")
 data6 = file6.read()
 vocab4 = data6.split(",")