def generate_param_config(ticks, isindex, look_back, num_features, start_date, data_source): ins = GetPriceData(sid=ticks, index=isindex, data_source=data_source) data = ins.batch_get_n_days_backward(start_date, look_back) data = [(tick, dta.drop(['tick'], axis=1)) for tick, dta in data.groupby(['tick'])] proc = partial(generate_features_and_labels, ta_factors=const.ta_factors, predict_type='next_day') ret = [proc(dta) for dta in data] ret2 = get_best_features(ret[0], num_features) params = batch_find_best_params(ret2) if not isinstance(params, list): params = [params] df = pd.DataFrame(params) return df