store periodic breakdown in backtest results

This will enable the webserver to use this data.

freqtrade/optimize/hyperopt.py

@@ -379,7 +379,8 @@ class Hyperopt:
 
         strat_stats = generate_strategy_stats(
             self.pairlist, self.backtesting.strategy.get_strategy_name(),
-            backtesting_results, min_date, max_date, market_change=self.market_change
+            backtesting_results, min_date, max_date, market_change=self.market_change,
+            is_hyperopt=True,
         )
         results_explanation = HyperoptTools.format_results_explanation_string(
             strat_stats, self.config['stake_currency'])

freqtrade/optimize/optimize_reports.py

@@ -7,8 +7,8 @@ from typing import Any, Dict, List, Union
 from pandas import DataFrame, to_datetime
 from tabulate import tabulate
 
-from freqtrade.constants import (DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT,
+from freqtrade.constants import (BACKTEST_BREAKDOWNS, DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN,
-                                 Config, IntOrInf)
+                                 UNLIMITED_STAKE_AMOUNT, Config, IntOrInf)
 from freqtrade.data.metrics import (calculate_cagr, calculate_calmar, calculate_csum,
                                     calculate_expectancy, calculate_market_change,
                                     calculate_max_drawdown, calculate_sharpe, calculate_sortino)
@@ -296,6 +296,7 @@ def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dic
         stats.append(
             {
                 'date': name.strftime('%d/%m/%Y'),
+                'date_ts': int(name.to_pydatetime().timestamp() * 1000),
                 'profit_abs': profit_abs,
                 'wins': wins,
                 'draws': draws,
@@ -305,6 +306,13 @@ def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dic
     return stats
 
 
+def generate_all_periodic_breakdown_stats(trade_list: List) -> Dict[str, List]:
+    result = {}
+    for period in BACKTEST_BREAKDOWNS:
+        result[period] = generate_periodic_breakdown_stats(trade_list, period)
+    return result
+
+
 def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
     """ Generate overall trade statistics """
     if len(results) == 0:
@@ -381,7 +389,8 @@ def generate_strategy_stats(pairlist: List[str],
                             strategy: str,
                             content: Dict[str, Any],
                             min_date: datetime, max_date: datetime,
-                            market_change: float
+                            market_change: float,
+                            is_hyperopt: bool = False,
                             ) -> Dict[str, Any]:
     """
     :param pairlist: List of pairs to backtest
@@ -416,6 +425,11 @@ def generate_strategy_stats(pairlist: List[str],
 
     daily_stats = generate_daily_stats(results)
     trade_stats = generate_trading_stats(results)
+
+    periodic_breakdown = {}
+    if not is_hyperopt:
+        periodic_breakdown = {'periodic_breakdown': generate_all_periodic_breakdown_stats(results)}
+
     best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'],
                     key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
     worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
@@ -434,7 +448,6 @@ def generate_strategy_stats(pairlist: List[str],
         'results_per_enter_tag': enter_tag_results,
         'exit_reason_summary': exit_reason_stats,
         'left_open_trades': left_open_results,
-        # 'days_breakdown_stats': days_breakdown_stats,
 
         'total_trades': len(results),
         'trade_count_long': len(results.loc[~results['is_short']]),
@@ -499,6 +512,7 @@ def generate_strategy_stats(pairlist: List[str],
         'exit_profit_only': config['exit_profit_only'],
         'exit_profit_offset': config['exit_profit_offset'],
         'ignore_roi_if_entry_signal': config['ignore_roi_if_entry_signal'],
+        **periodic_breakdown,
         **daily_stats,
         **trade_stats
     }
@@ -891,8 +905,11 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
     print(table)
 
     for period in backtest_breakdown:
-        days_breakdown_stats = generate_periodic_breakdown_stats(
+        if period in results.get('periodic_breakdown', {}):
-            trade_list=results['trades'], period=period)
+            days_breakdown_stats = results['periodic_breakdown'][period]
+        else:
+            days_breakdown_stats = generate_periodic_breakdown_stats(
+                trade_list=results['trades'], period=period)
         table = text_table_periodic_breakdown(days_breakdown_stats=days_breakdown_stats,
                                               stake_currency=stake_currency, period=period)
         if isinstance(table, str) and len(table) > 0: