Method train

AutoComplete_App/backend.py:66–127

Returns - string Input - str: a string of words called sentence ---------- Trains the sentence. It does this by creating a map of current words to next words and their counts for each time the next word appears after the current word - takes i

(self, sentence)

            )

    def train(self, sentence):
        """
        Returns - string
        Input - str: a string of words called sentence
        ----------
        Trains the sentence. It does this by creating a map of
        current words to next words and their counts for each
        time the next word appears after the current word
        - takes in the sentence and splits it into a list of words
        - retrieves the word map and predictions map
        - creates the word map and predictions map together
        - saves word map and predictions map to the database
        """
        cur = self.conn.cursor()
        words_list = sentence.split(" ")

        words_map = cur.execute(
            "SELECT value FROM WordMap WHERE name='wordsmap'"
        ).fetchone()[0]
        words_map = json.loads(words_map)

        predictions = cur.execute(
            "SELECT value FROM WordPrediction WHERE name='predictions'"
        ).fetchone()[0]
        predictions = json.loads(predictions)

        for idx in range(len(words_list) - 1):
            curr_word, next_word = words_list[idx], words_list[idx + 1]
            if curr_word not in words_map:
                words_map[curr_word] = {}
            if next_word not in words_map[curr_word]:
                words_map[curr_word][next_word] = 1
            else:
                words_map[curr_word][next_word] += 1

            # checking the completion word against the next word
            if curr_word not in predictions:
                predictions[curr_word] = {
                    "completion_word": next_word,
                    "completion_count": 1,
                }
            else:
                if (
                    words_map[curr_word][next_word]
                    > predictions[curr_word]["completion_count"]
                ):
                    predictions[curr_word]["completion_word"] = next_word
                    predictions[curr_word]["completion_count"] = words_map[curr_word][
                        next_word
                    ]

        words_map = json.dumps(words_map)
        predictions = json.dumps(predictions)

        cur.execute(
            "UPDATE WordMap SET value = (?) WHERE name='wordsmap'", (words_map,)
        )
        cur.execute(