if __name__ == '__main__':
    """
    Human-Machine Interface
    """
    cli = Cli()
    start(cli)

    while cli.option != 'x':
        if cli.option == 'h':
            display_help(cli)
        elif cli.option == 'c' or cli.option == "collect":
            collect(cli)
        elif cli.option == 't' or cli.option == "training":
            training()
        elif cli.option == 'p' or cli.option == "prediction":
            prediction()
        elif cli.option == 'tweets':
            data = Storage('collected').load()
            cli.tweets_colleted(data)
        elif cli.option == 'tweets trained':
            data = Storage('trained').load()
            cli.tweets_trained(data)
        elif cli.option == 'tweets metrics':
            collected = Storage('collected').load()
            trained   = Storage('trained').load()
            cli.tweets_metrics(collected, trained)

        cli.waiting_input()

    cli.finished()
Exemple #2
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if __name__ == '__main__':
    """
    Human-Machine Interface
    """
    cli = Cli()
    start(cli)

    while cli.option != 'x':
        if cli.option == 'h':
            display_help(cli)
        elif cli.option == 'c' or cli.option == "collect":
            collect(cli)
        elif cli.option == 't' or cli.option == "training":
            training()
        elif cli.option == 'p' or cli.option == "prediction":
            prediction()
        elif cli.option == 'tweets':
            data = Storage('collected').load()
            cli.tweets_colleted(data)
        elif cli.option == 'tweets trained':
            data = Storage('trained').load()
            cli.tweets_trained(data)
        elif cli.option == 'tweets metrics':
            collected = Storage('collected').load()
            trained = Storage('trained').load()
            cli.tweets_metrics(collected, trained)

        cli.waiting_input()

    cli.finished()