From 6ca6f62509122d06fcbf4a9d435a8dc96a27bbad Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 Nov 2021 09:39:10 +0100 Subject: [PATCH] Remove duplicate code in optimize_reports --- freqtrade/optimize/optimize_reports.py | 50 +++----------------------- 1 file changed, 4 insertions(+), 46 deletions(-) diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index c4002fcbe..dcd6b4e1f 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -46,20 +46,11 @@ def _get_line_floatfmt(stake_currency: str) -> List[str]: '.2f', 'd', 's', 's'] -def _get_line_header(first_column: str, stake_currency: str) -> List[str]: +def _get_line_header(first_column: str, stake_currency: str, direction: str = 'Buys') -> 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', - 'Win Draw Loss Win%'] - - -def _get_line_header_sell(first_column: str, stake_currency: str) -> List[str]: - """ - Generate header lines (goes in line with _generate_result_line()) - """ - return [first_column, 'Sells', 'Avg Profit %', 'Cum Profit %', + return [first_column, direction, 'Avg Profit %', 'Cum Profit %', f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration', 'Win Draw Loss Win%'] @@ -156,7 +147,7 @@ def generate_tag_metrics(tag_type: str, if skip_nan and result['profit_abs'].isnull().all(): continue - tabular_data.append(_generate_tag_result_line(result, starting_balance, tag)) + tabular_data.append(_generate_result_line(result, starting_balance, tag)) # Sort by total profit %: tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True) @@ -168,39 +159,6 @@ def generate_tag_metrics(tag_type: str, return [] -def _generate_tag_result_line(result: DataFrame, starting_balance: int, first_column: str) -> Dict: - """ - Generate one result dict, with "first_column" as key. - """ - profit_sum = result['profit_ratio'].sum() - # (end-capital - starting capital) / starting capital - profit_total = result['profit_abs'].sum() / starting_balance - - return { - 'key': first_column, - 'trades': len(result), - 'profit_mean': result['profit_ratio'].mean() if len(result) > 0 else 0.0, - 'profit_mean_pct': result['profit_ratio'].mean() * 100.0 if len(result) > 0 else 0.0, - 'profit_sum': profit_sum, - 'profit_sum_pct': round(profit_sum * 100.0, 2), - 'profit_total_abs': result['profit_abs'].sum(), - 'profit_total': profit_total, - 'profit_total_pct': round(profit_total * 100.0, 2), - '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_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]: """ Generate small table outlining Backtest results @@ -631,7 +589,7 @@ def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_curr if(tag_type == "buy_tag"): headers = _get_line_header("TAG", stake_currency) else: - headers = _get_line_header_sell("TAG", stake_currency) + headers = _get_line_header("TAG", stake_currency, 'Sells') floatfmt = _get_line_floatfmt(stake_currency) output = [ [