async def markovGen(self):
            result = ""
            randomized_int = random.randint(1, 602)
            with open("modules/markov/markov ({}).txt".format(randomized_int), ) as file:
                #return returnable_file
                length = 50
                #print(file.name)
                word_dictionary = self.learn(file.read())
                punctuation = False
                last_word = "~~~~~~~~~~~~~~~~"

                while not punctuation:
                    new_word = self.get_next_word(last_word, word_dictionary).rstrip()
                    result = result + " " + new_word
                    result.replace("\r\n", '')
                    last_word = new_word

                    if len(result.split(" ")) > random.randint(4,9) and any(punct in result for punct in ["!", ".", "?", "\n", "\r\n"]):
                        punctuation = True
            await self.client.say(result)


    def learn(self, input):
        dict = {}
        word_tokens = input.split(" ")

        for i in range(0, len(word_tokens)-1):
            current_word = word_tokens[i]
            next_word = word_tokens[i+1]

            if current_word not in dict:
                # Create new entry in dictionary
                dict[current_word] = {next_word : 1}
            else:
                # Current word already exists
                all_next_words = dict[current_word]

                if next_word not in all_next_words:
                    # Add new next state (word)
                    dict[current_word][next_word] = 1
                else:
                    # Already exists, just increment
                    dict[current_word][next_word] = dict[current_word][next_word] + 1

        return dict

    def get_next_word(self, last_word, dict):
        if last_word not in dict:
            # Random
            new_word = self.pick_random(dict)
            return new_word
        else:
            # Pick next word from list
            candidates = dict[last_word]
            candidates_normalised = []

            for word in candidates:
                freq = candidates[word]
                for i in range(0, freq):
                    candidates_normalised.append(word)

            rnd = random.randint(0, len(candidates_normalised)-1)
            return candidates_normalised[rnd]


    def pick_random(self, dict):
        random_num = random.randint(0, len(dict)-1)
        new_word = list(dict.keys())[random_num]
        return new_word