diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index 0799ebb23..94729b6a5 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -185,6 +185,16 @@ def generate_edge_table(results: dict) -> str: def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: + if len(results) == 0: + return { + 'backtest_best_day': 0, + 'backtest_worst_day': 0, + 'winning_days': 0, + 'draw_days': 0, + 'losing_days': 0, + 'winner_holding_avg': timedelta(), + 'loser_holding_avg': timedelta(), + } daily_profit = results.resample('1d', on='close_date')['profit_percent'].sum() worst = min(daily_profit) best = max(daily_profit) @@ -249,7 +259,7 @@ def generate_backtest_stats(config: Dict, btdata: Dict[str, DataFrame], 'sell_reason_summary': sell_reason_stats, 'left_open_trades': left_open_results, 'total_trades': len(results), - 'profit_mean': results['profit_percent'].mean(), + 'profit_mean': results['profit_percent'].mean() if len(results) > 0 else 0, 'profit_total': results['profit_percent'].sum(), 'profit_total_abs': results['profit_abs'].sum(), 'backtest_start': min_date.datetime, @@ -258,7 +268,7 @@ def generate_backtest_stats(config: Dict, btdata: Dict[str, DataFrame], 'backtest_end_ts': max_date.timestamp * 1000, 'backtest_days': backtest_days, - 'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else None, + 'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0, 'market_change': market_change, 'pairlist': list(btdata.keys()), 'stake_amount': config['stake_amount'], diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py index e5d98ca43..4f62e2e23 100644 --- a/tests/optimize/test_optimize_reports.py +++ b/tests/optimize/test_optimize_reports.py @@ -204,6 +204,14 @@ def test_generate_daily_stats(testdatadir): assert res['winner_holding_avg'] == timedelta(seconds=1440) assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420) + # Select empty dataframe! + res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :]) + assert isinstance(res, dict) + assert round(res['backtest_best_day'], 4) == 0.0 + assert res['winning_days'] == 0 + assert res['draw_days'] == 0 + assert res['losing_days'] == 0 + def test_text_table_sell_reason(default_conf):