import logging from operator import itemgetter from typing import Any, Dict, List from colorama import init as colorama_init from freqtrade.configuration import setup_utils_configuration from freqtrade.exceptions import OperationalException from freqtrade.state import RunMode logger = logging.getLogger(__name__) def start_hyperopt_list(args: Dict[str, Any]) -> None: """ List hyperopt epochs previously evaluated """ from freqtrade.optimize.hyperopt import Hyperopt config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) print_colorized = config.get('print_colorized', False) print_json = config.get('print_json', False) export_csv = config.get('export_csv', None) no_details = config.get('hyperopt_list_no_details', False) no_header = False filteroptions = { 'only_best': config.get('hyperopt_list_best', False), 'only_profitable': config.get('hyperopt_list_profitable', False), 'filter_min_trades': config.get('hyperopt_list_min_trades', 0), 'filter_max_trades': config.get('hyperopt_list_max_trades', 0), 'filter_min_avg_time': config.get('hyperopt_list_min_avg_time', None), 'filter_max_avg_time': config.get('hyperopt_list_max_avg_time', None), 'filter_min_avg_profit': config.get('hyperopt_list_min_avg_profit', None), 'filter_max_avg_profit': config.get('hyperopt_list_max_avg_profit', None), 'filter_min_total_profit': config.get('hyperopt_list_min_total_profit', None), 'filter_max_total_profit': config.get('hyperopt_list_max_total_profit', None) } trials_file = (config['user_data_dir'] / 'hyperopt_results' / 'hyperopt_results.pickle') # Previous evaluations trials = Hyperopt.load_previous_results(trials_file) total_epochs = len(trials) trials = _hyperopt_filter_trials(trials, filteroptions) if print_colorized: colorama_init(autoreset=True) if not export_csv: try: Hyperopt.print_result_table(config, trials, total_epochs, not filteroptions['only_best'], print_colorized, 0) except KeyboardInterrupt: print('User interrupted..') if trials and not no_details: sorted_trials = sorted(trials, key=itemgetter('loss')) results = sorted_trials[0] Hyperopt.print_epoch_details(results, total_epochs, print_json, no_header) if trials and export_csv: overwrite_csv = False if export_csv[0] == '+': overwrite_csv = True export_csv = export_csv[1:] Hyperopt.export_csv_file( config, trials, total_epochs, not filteroptions['only_best'], export_csv, overwrite_csv ) def start_hyperopt_show(args: Dict[str, Any]) -> None: """ Show details of a hyperopt epoch previously evaluated """ from freqtrade.optimize.hyperopt import Hyperopt config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) print_json = config.get('print_json', False) no_header = config.get('hyperopt_show_no_header', False) trials_file = (config['user_data_dir'] / 'hyperopt_results' / 'hyperopt_results.pickle') n = config.get('hyperopt_show_index', -1) filteroptions = { 'only_best': config.get('hyperopt_list_best', False), 'only_profitable': config.get('hyperopt_list_profitable', False), 'filter_min_trades': config.get('hyperopt_list_min_trades', 0), 'filter_max_trades': config.get('hyperopt_list_max_trades', 0), 'filter_min_avg_time': config.get('hyperopt_list_min_avg_time', None), 'filter_max_avg_time': config.get('hyperopt_list_max_avg_time', None), 'filter_min_avg_profit': config.get('hyperopt_list_min_avg_profit', None), 'filter_max_avg_profit': config.get('hyperopt_list_max_avg_profit', None), 'filter_min_total_profit': config.get('hyperopt_list_min_total_profit', None), 'filter_max_total_profit': config.get('hyperopt_list_max_total_profit', None) } # Previous evaluations trials = Hyperopt.load_previous_results(trials_file) total_epochs = len(trials) trials = _hyperopt_filter_trials(trials, filteroptions) trials_epochs = len(trials) if n > trials_epochs: raise OperationalException( f"The index of the epoch to show should be less than {trials_epochs + 1}.") if n < -trials_epochs: raise OperationalException( f"The index of the epoch to show should be greater than {-trials_epochs - 1}.") # Translate epoch index from human-readable format to pythonic if n > 0: n -= 1 if trials: val = trials[n] Hyperopt.print_epoch_details(val, total_epochs, print_json, no_header, header_str="Epoch details") def _hyperopt_filter_trials(trials: List, filteroptions: dict) -> List: """ Filter our items from the list of hyperopt results """ if filteroptions['only_best']: trials = [x for x in trials if x['is_best']] if filteroptions['only_profitable']: trials = [x for x in trials if x['results_metrics']['profit'] > 0] if filteroptions['filter_min_trades'] > 0: trials = [ x for x in trials if x['results_metrics']['trade_count'] > filteroptions['filter_min_trades'] ] if filteroptions['filter_max_trades'] > 0: trials = [ x for x in trials if x['results_metrics']['trade_count'] < filteroptions['filter_max_trades'] ] if filteroptions['filter_min_avg_time'] is not None: trials = [x for x in trials if x['results_metrics']['trade_count'] > 0] trials = [ x for x in trials if x['results_metrics']['duration'] > filteroptions['filter_min_avg_time'] ] if filteroptions['filter_max_avg_time'] is not None: trials = [x for x in trials if x['results_metrics']['trade_count'] > 0] trials = [ x for x in trials if x['results_metrics']['duration'] < filteroptions['filter_max_avg_time'] ] if filteroptions['filter_min_avg_profit'] is not None: trials = [x for x in trials if x['results_metrics']['trade_count'] > 0] trials = [ x for x in trials if x['results_metrics']['avg_profit'] > filteroptions['filter_min_avg_profit'] ] if filteroptions['filter_max_avg_profit'] is not None: trials = [x for x in trials if x['results_metrics']['trade_count'] > 0] trials = [ x for x in trials if x['results_metrics']['avg_profit'] < filteroptions['filter_max_avg_profit'] ] if filteroptions['filter_min_total_profit'] is not None: trials = [x for x in trials if x['results_metrics']['trade_count'] > 0] trials = [ x for x in trials if x['results_metrics']['profit'] > filteroptions['filter_min_total_profit'] ] if filteroptions['filter_max_total_profit'] is not None: trials = [x for x in trials if x['results_metrics']['trade_count'] > 0] trials = [ x for x in trials if x['results_metrics']['profit'] < filteroptions['filter_max_total_profit'] ] logger.info(f"{len(trials)} " + ("best " if filteroptions['only_best'] else "") + ("profitable " if filteroptions['only_profitable'] else "") + "epochs found.") return trials