checkers.bully 

 1from . import Checker
 2import os
 3import pickle
 4
 5
 6class BullyChecker(Checker):
 7    def __init__(self):
 8        self.use_gpu = bool(os.getenv("USE_GPU", False))
 9        self.sensitivity_threshold = 0.8
10        self.model = None
11        self.load_model()
12
13    def load_model(self):
14        filename = './data/toxic_model.sav'
15        self.model = pickle.load(open(filename, 'rb'))
16
17    def check_message(self, msg: str):
18        """
19        Function to check if a message has profane words
20        :param msg: Message String
21        :return: Boolean
22        """
23        predicts_dict = self.model.predict(msg)
24
25        def getThreats(d):
26            ret = []
27            for x in sorted([(predicts_dict[k], k) for k in predicts_dict]):
28                if x[0] >= self.sensitivity_threshold:
29                    ret.append(x[1])
30            return ret
31
32        return getThreats(predicts_dict)
class BullyChecker(checkers.Checker): 
 7class BullyChecker(Checker):
 8    def __init__(self):
 9        self.use_gpu = bool(os.getenv("USE_GPU", False))
10        self.sensitivity_threshold = 0.8
11        self.model = None
12        self.load_model()
13
14    def load_model(self):
15        filename = './data/toxic_model.sav'
16        self.model = pickle.load(open(filename, 'rb'))
17
18    def check_message(self, msg: str):
19        """
20        Function to check if a message has profane words
21        :param msg: Message String
22        :return: Boolean
23        """
24        predicts_dict = self.model.predict(msg)
25
26        def getThreats(d):
27            ret = []
28            for x in sorted([(predicts_dict[k], k) for k in predicts_dict]):
29                if x[0] >= self.sensitivity_threshold:
30                    ret.append(x[1])
31            return ret
32
33        return getThreats(predicts_dict)

An Abstract Class for all Checker Classes. It is inherited by all the Checker objects

BullyChecker() 
 8    def __init__(self):
 9        self.use_gpu = bool(os.getenv("USE_GPU", False))
10        self.sensitivity_threshold = 0.8
11        self.model = None
12        self.load_model()
def load_model(self): 
14    def load_model(self):
15        filename = './data/toxic_model.sav'
16        self.model = pickle.load(open(filename, 'rb'))
def check_message(self, msg: str): 
18    def check_message(self, msg: str):
19        """
20        Function to check if a message has profane words
21        :param msg: Message String
22        :return: Boolean
23        """
24        predicts_dict = self.model.predict(msg)
25
26        def getThreats(d):
27            ret = []
28            for x in sorted([(predicts_dict[k], k) for k in predicts_dict]):
29                if x[0] >= self.sensitivity_threshold:
30                    ret.append(x[1])
31            return ret
32
33        return getThreats(predicts_dict)

Function to check if a message has profane words

Parameters
  • msg: Message String
Returns

Boolean