import logging from datetime import timedelta from pathlib import Path from typing import Any, Dict, List from pandas import DataFrame from tabulate import tabulate from freqtrade.misc import file_dump_json logger = logging.getLogger(__name__) def store_backtest_result(recordfilename: Path, all_results: Dict[str, DataFrame]) -> None: """ Stores backtest results to file (one file per strategy) :param recordfilename: Destination filename :param all_results: Dict of Dataframes, one results dataframe per strategy """ for strategy, results in all_results.items(): records = backtest_result_to_list(results) if records: filename = recordfilename if len(all_results) > 1: # Inject strategy to filename filename = Path.joinpath( recordfilename.parent, f'{recordfilename.stem}-{strategy}').with_suffix(recordfilename.suffix) logger.info(f'Dumping backtest results to {filename}') file_dump_json(filename, records) def backtest_result_to_list(results: DataFrame) -> List[List]: """ Converts a list of Backtest-results to list :param results: Dataframe containing results for one strategy :return: List of Lists containing the trades """ return [[t.pair, t.profit_percent, t.open_time.timestamp(), t.close_time.timestamp(), t.open_index - 1, t.trade_duration, t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value] for index, t in results.iterrows()] def _get_line_floatfmt() -> List[str]: """ Generate floatformat (goes in line with _generate_result_line()) """ return ['s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', 'd', 'd', 'd'] def _get_line_header(first_column: str, stake_currency: str) -> List[str]: """ Generate header lines (goes in line with _generate_result_line()) """ return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %', f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration', 'Wins', 'Draws', 'Losses'] def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: str) -> Dict: """ Generate one result dict, with "first_column" as key. """ return { 'key': first_column, 'trades': len(result), 'profit_mean': result['profit_percent'].mean(), 'profit_mean_pct': result['profit_percent'].mean() * 100.0, 'profit_sum': result['profit_percent'].sum(), 'profit_sum_pct': result['profit_percent'].sum() * 100.0, 'profit_total_abs': result['profit_abs'].sum(), 'profit_total_pct': result['profit_percent'].sum() * 100.0 / max_open_trades, 'duration_avg': str(timedelta( minutes=round(result['trade_duration'].mean())) ) if not result.empty else '0:00', # 'duration_max': str(timedelta( # minutes=round(result['trade_duration'].max())) # ) if not result.empty else '0:00', # 'duration_min': str(timedelta( # minutes=round(result['trade_duration'].min())) # ) if not result.empty else '0:00', 'wins': len(result[result['profit_abs'] > 0]), 'draws': len(result[result['profit_abs'] == 0]), 'losses': len(result[result['profit_abs'] < 0]), } def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_trades: int, results: DataFrame, skip_nan: bool = False) -> List[Dict]: """ Generates and returns a list for the given backtest data and the results dataframe :param data: Dict of containing data that was used during backtesting. :param stake_currency: stake-currency - used to correctly name headers :param max_open_trades: Maximum allowed open trades :param results: Dataframe containing the backtest results :param skip_nan: Print "left open" open trades :return: List of Dicts containing the metrics per pair """ tabular_data = [] for pair in data: result = results[results['pair'] == pair] if skip_nan and result['profit_abs'].isnull().all(): continue tabular_data.append(_generate_result_line(result, max_open_trades, pair)) # Append Total tabular_data.append(_generate_result_line(results, max_open_trades, 'TOTAL')) return tabular_data def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]: """ Generate small table outlining Backtest results :param max_open_trades: Max_open_trades parameter :param results: Dataframe containing the backtest result for one strategy :return: List of Dicts containing the metrics per Sell reason """ tabular_data = [] for reason, count in results['sell_reason'].value_counts().iteritems(): result = results.loc[results['sell_reason'] == reason] profit_mean = result['profit_percent'].mean() profit_sum = result["profit_percent"].sum() profit_percent_tot = round(result['profit_percent'].sum() * 100.0 / max_open_trades, 2) tabular_data.append( { 'sell_reason': reason.value, 'trades': count, 'wins': len(result[result['profit_abs'] > 0]), 'draws': len(result[result['profit_abs'] == 0]), 'losses': len(result[result['profit_abs'] < 0]), 'profit_mean': profit_mean, 'profit_mean_pct': round(profit_mean * 100, 2), 'profit_sum': profit_sum, 'profit_sum_pct': round(profit_sum * 100, 2), 'profit_total_abs': result['profit_abs'].sum(), 'profit_pct_total': profit_percent_tot, } ) return tabular_data def generate_strategy_metrics(stake_currency: str, max_open_trades: int, all_results: Dict) -> List[Dict]: """ Generate summary per strategy :param stake_currency: stake-currency - used to correctly name headers :param max_open_trades: Maximum allowed open trades used for backtest :param all_results: Dict of containing results for all strategies :return: List of Dicts containing the metrics per Strategy """ tabular_data = [] for strategy, results in all_results.items(): tabular_data.append(_generate_result_line(results, max_open_trades, strategy)) return tabular_data def generate_edge_table(results: dict) -> str: floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', 'd', 'd') tabular_data = [] headers = ['Pair', 'Stoploss', 'Win Rate', 'Risk Reward Ratio', 'Required Risk Reward', 'Expectancy', 'Total Number of Trades', 'Average Duration (min)'] for result in results.items(): if result[1].nb_trades > 0: tabular_data.append([ result[0], result[1].stoploss, result[1].winrate, result[1].risk_reward_ratio, result[1].required_risk_reward, result[1].expectancy, result[1].nb_trades, round(result[1].avg_trade_duration) ]) # Ignore type as floatfmt does allow tuples but mypy does not know that return tabulate(tabular_data, headers=headers, floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore def generate_backtest_stats(config: Dict, btdata: Dict[str, DataFrame], all_results: Dict[str, DataFrame]) -> Dict[str, Any]: """ :param config: Configuration object used for backtest :param btdata: Backtest data :param all_results: backtest result - dictionary with { Strategy: results}. :return: Dictionary containing results per strategy and a stratgy summary. """ stake_currency = config['stake_currency'] max_open_trades = config['max_open_trades'] result: Dict[str, Any] = {'strategy': {}} for strategy, results in all_results.items(): pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency, max_open_trades=max_open_trades, results=results, skip_nan=False) sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades, results=results) left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency, max_open_trades=max_open_trades, results=results.loc[results['open_at_end']], skip_nan=True) strat_stats = { 'trades': backtest_result_to_list(results), 'results_per_pair': pair_results, 'sell_reason_summary': sell_reason_stats, 'left_open_trades': left_open_results, } result['strategy'][strategy] = strat_stats strategy_results = generate_strategy_metrics(stake_currency=stake_currency, max_open_trades=max_open_trades, all_results=all_results) result['strategy_comparison'] = strategy_results return result ### # Start output section ### def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: str) -> str: """ Generates and returns a text table for the given backtest data and the results dataframe :param pair_results: List of Dictionaries - one entry per pair + final TOTAL row :param stake_currency: stake-currency - used to correctly name headers :return: pretty printed table with tabulate as string """ headers = _get_line_header('Pair', stake_currency) floatfmt = _get_line_floatfmt() output = [[ t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] ] for t in pair_results] # Ignore type as floatfmt does allow tuples but mypy does not know that return tabulate(output, headers=headers, floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str: """ Generate small table outlining Backtest results :param sell_reason_stats: Sell reason metrics :param stake_currency: Stakecurrency used :return: pretty printed table with tabulate as string """ headers = [ 'Sell Reason', 'Sells', 'Wins', 'Draws', 'Losses', 'Avg Profit %', 'Cum Profit %', f'Tot Profit {stake_currency}', 'Tot Profit %', ] output = [[ t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_pct_total'], ] for t in sell_reason_stats] return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right") def text_table_strategy(strategy_results, stake_currency: str) -> str: """ Generate summary table per strategy :param stake_currency: stake-currency - used to correctly name headers :param max_open_trades: Maximum allowed open trades used for backtest :param all_results: Dict of containing results for all strategies :return: pretty printed table with tabulate as string """ floatfmt = _get_line_floatfmt() headers = _get_line_header('Strategy', stake_currency) output = [[ t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] ] for t in strategy_results] # Ignore type as floatfmt does allow tuples but mypy does not know that return tabulate(output, headers=headers, floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") def show_backtest_results(config: Dict, backtest_stats: Dict): stake_currency = config['stake_currency'] for strategy, results in backtest_stats['strategy'].items(): # Print results print(f"Result for strategy {strategy}") table = text_table_bt_results(results['results_per_pair'], stake_currency=stake_currency) if isinstance(table, str): print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '=')) print(table) table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'], stake_currency=stake_currency) if isinstance(table, str): print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '=')) print(table) table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency) if isinstance(table, str): print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '=')) print(table) if isinstance(table, str): print('=' * len(table.splitlines()[0])) print() if len(backtest_stats['strategy']) > 1: # Print Strategy summary table table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency) print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '=')) print(table) print('=' * len(table.splitlines()[0])) print('\nFor more details, please look at the detail tables above')