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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fit_cmd(argv=sys.argv[1:]):
 # pragma: no cover """\ Fit a model and save to database. Will use 'dataset_loader_train', 'model', and 'model_perister' from the configuration file, to load a dataset to train a model with, and persist it. Usage: pld-fit [options] Options: -n --no-save Don't persist the fitted model to disk. --no-activate Don't activate the fitted model. --save-if-better-than=<k> Persist only if test score better than given value. -e --evaluate Evaluate fitted model on train and test set and print out results. -h --help Show this screen. """

    arguments = docopt(fit_cmd.__doc__, argv=argv)
    no_save = arguments['--no-save']
    no_activate = arguments['--no-activate']
    save_if_better_than = arguments['--save-if-better-than']
    evaluate = arguments['--evaluate'] or bool(save_if_better_than)
    if save_if_better_than is not None:
        save_if_better_than = float(save_if_better_than)
    initialize_config(__mode__='fit')
    fit(
        persist=not no_save,
        activate=not no_activate,
        evaluate=evaluate,
        persist_if_better_than=save_if_better_than,
        )