from chatterbot import utils
from chatterbot.conversation import Statement
from chatterbot.trainers import Trainer


class TwitterCorpusTrainer(Trainer):
    pass
    # def train(self, *args, **kwargs):
    #     """
    #     Train the chat bot based on the provided list of
    #     statements that represents a single conversation.
    #     """
    #     import twint
    #
    #     c = twint.Config()
    #     c.__dict__.update(kwargs)
    #     twint.run.Search(c)
    #
    #
    #     previous_statement_text = None
    #     previous_statement_search_text = ''
    #
    #     statements_to_create = []
    #
    #     for conversation_count, text in enumerate(conversation):
    #         if self.show_training_progress:
    #             utils.print_progress_bar(
    #                 'List Trainer',
    #                 conversation_count + 1, len(conversation)
    #             )
    #
    #         statement_search_text = self.chatbot.storage.tagger.get_text_index_string(text)
    #
    #         statement = self.get_preprocessed_statement(
    #             Statement(
    #                 text=text,
    #                 search_text=statement_search_text,
    #                 in_response_to=previous_statement_text,
    #                 search_in_response_to=previous_statement_search_text,
    #                 conversation='training'
    #             )
    #         )
    #
    #         previous_statement_text = statement.text
    #         previous_statement_search_text = statement_search_text
    #
    #         statements_to_create.append(statement)
    #
    #     self.chatbot.storage.create_many(statements_to_create)