Beispiel #1
0
    def run(self):

        #Load configurations
        util = Util()
        configurations = util.loadResources(
            path_from_root('configurations.txt'))

        model = configurations['model']

        hostname = configurations['local_server_hostname']
        port = int(configurations['local_server_port'])

        print("*** Starting Local Stance Classifier server ***")
        stance_classifier = StanceClassifier(model)
        serversocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
        serversocket.bind((hostname, port))
        serversocket.listen(5)
        print("Local Stance Classifier server ready!")
        print("Bound to " + hostname + ":" + str(port) +
              ". Listening for connections")

        #Upon receival of classification request, do:
        while 1:

            try:
                #Open connection:
                (conn, address) = serversocket.accept()

                print("*** Incoming connection from " + str(address))

                print('*** Receiving data in batches of 4096 bytes...')
                bs = conn.recv(8)
                (length, ) = unpack('>Q', bs)
                print('*** Data length (bytes): ' + str(length))
                data = b''
                c = 1
                while len(data) < length:
                    #print('Receiving batch %d ...' % c)
                    to_read = length - len(data)
                    data += conn.recv(4096 if to_read > 4096 else to_read)
                    c += 1
                assert len(b'\00') == 1
                conn.sendall(b'\00')

                source = json.loads(data)['original']
                reply = json.loads(data)['reply']

                output = stance_classifier.classify(source, reply)

                data = {}
                data['class'] = output[0]
                data['probs'] = {}
                for i in range(0, len(output[1])):
                    data['probs'][i] = output[1][i]

                print("Sending... " + str(data))
                conn.send(json.dumps(data).encode('utf-8'))
                conn.close()
            except Exception as ex:
                print(ex)
 def read_vulgar_words(self, f):
     f_vulgar = open(path_from_root(f), "r", encoding="utf-8")
     v_vulgar = []
     for l in f_vulgar.readlines():
         t = l.split("-")
         v_vulgar.append(t[0].strip())
     return v_vulgar
 def read_surprise_words(self, f):
     f_surprise = open(path_from_root(f), "r", encoding="utf-8")
     v_surprise = []
     for l in f_surprise.readlines():
         t = l.split("\t")
         v_surprise.append(t[0].strip())
     return v_surprise
 def read_google_bad_words(self, f):
     f_google_bad = open(path_from_root(f), "r", encoding="utf-8")
     v_google_bad = []
     for l in f_google_bad.readlines():
         t = l.split(":")
         v_google_bad.append(t[0].replace("\"", "").strip())
     return v_google_bad
 def read_emoticon(self, f):
     f_emoticon = open(path_from_root(f), "r", encoding="utf-8")
     dict_emoticon = {}
     for l in f_emoticon.readlines():
         t = l.strip().split("\t")
         dict_emoticon[t[0]] = int(t[1])
     return dict_emoticon
 def read_no_doubt_words(self, f):
     f_no_doubt = open(path_from_root(f), "r", encoding="utf-8")
     v_no_doubt = []
     for l in f_no_doubt.readlines():
         tokens = l.split(",")
         for t in tokens:
             v_no_doubt.append(t.strip())
     return v_no_doubt
 def loadGloveModel(self, gloveFile):
     print("Loading Glove Model")
     f = open(path_from_root(gloveFile), 'r', encoding="utf-8")
     model = {}
     for line in f:
         splitLine = line.split(" ")
         #print(splitLine)
         word = splitLine[0]
         embedding = np.array([float(val) for val in splitLine[1:]])
         model[word] = embedding
     print("Done.",len(model)," words loaded!")
     return model
    def __init__(self, resources): 
        self.emb_file = resources["embeddings_file"]
        self.emb_size = int(resources["embeddings_size"])
        self.emoticons = self.read_emoticon(resources["emoticon"])
        self.emoticons_cat = np.zeros(42)
        self.acronyms = self.read_acronyms(resources["acronyms"])
        self.vulgarWords = self.read_vulgar_words (resources["vulgar_words"])
        self.googleBadWords = self.read_google_bad_words(resources["google_bad_words"])
        self.surpriseWords = self.read_surprise_words(resources["affect_surprise"])
        self.doubtWords = self.read_doubt_words(resources["doubt_words"])
        self.noDoubtWords = self.read_no_doubt_words(resources["no_doubt_words"])

        self.scaler = load(path_from_root(resources["scaler"]))

        self.glove = self.loadGloveModel(self.emb_file)

        self.support_terms = ["support", "join", "confirm", "aid", "help"]
Beispiel #9
0
    def run(self):
        try:
            util = Util()
            configurations = util.loadResources(
                path_from_root('configurations.txt'))
            SERVER_PORT_NUMBER = int(configurations['main_server_port'])
            LOCAL_SERVER = configurations['local_server_hostname']
            LOCAL_PORT_NUMBER = int(configurations['local_server_port'])

            cs = StanceClassifier(LOCAL_SERVER, LOCAL_PORT_NUMBER)
            server = StanceClassifierServer(('', SERVER_PORT_NUMBER),
                                            StanceClassifierHandler)
            server.addStanceClassifier(cs)
            print("Bound to " + LOCAL_SERVER + ":" + str(SERVER_PORT_NUMBER) +
                  ". Listening for connections")
            server.serve_forever()

        except KeyboardInterrupt:
            server.socket.close()
 def read_acronyms(self, f):
     f_acronym = open(path_from_root(f), "r", encoding="utf-8")
     v_acronym = []
     for l in f_acronym.readlines():
         v_acronym.append(l.strip())
     return v_acronym
 def open_json(self, f):
     with open(path_from_root(f), encoding="utf-8") as json_file:
         data = json.load(json_file)
         return data