Add orders column to btresult

freqtrade/data/btanalysis.py

@@ -26,7 +26,7 @@ BT_DATA_COLUMNS = ['pair', 'stake_amount', 'amount', 'open_date', 'close_date',
                    'profit_ratio', 'profit_abs', 'exit_reason',
                    'initial_stop_loss_abs', 'initial_stop_loss_ratio', 'stop_loss_abs',
                    'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'enter_tag',
-                   'is_short'
+                   'is_short', 'open_timestamp', 'close_timestamp', 'orders'
                    ]
 
 
@@ -283,6 +283,8 @@ def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = Non
             if 'enter_tag' not in df.columns:
                 df['enter_tag'] = df['buy_tag']
                 df = df.drop(['buy_tag'], axis=1)
+            if 'orders' not in df.columns:
+                df.loc[:, 'orders'] = None
 
     else:
         # old format - only with lists.

freqtrade/optimize/optimize_reports.py

@@ -4,7 +4,6 @@ from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Union
 
-from numpy import int64
 from pandas import DataFrame, to_datetime
 from tabulate import tabulate
 
@@ -417,9 +416,6 @@ def generate_strategy_stats(pairlist: List[str],
                     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'],
                      key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
-    if not results.empty:
-        results['open_timestamp'] = results['open_date'].view(int64) // 1e6
-        results['close_timestamp'] = results['close_date'].view(int64) // 1e6
 
     backtest_days = (max_date - min_date).days or 1
     strat_stats = {

tests/data/test_btanalysis.py

@@ -85,7 +85,7 @@ def test_load_backtest_data_new_format(testdatadir):
     filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     assert isinstance(bt_data, DataFrame)
-    assert set(bt_data.columns) == set(BT_DATA_COLUMNS + ['close_timestamp', 'open_timestamp'])
+    assert set(bt_data.columns) == set(BT_DATA_COLUMNS)
     assert len(bt_data) == 179
 
     # Test loading from string (must yield same result)
@@ -110,7 +110,7 @@ def test_load_backtest_data_multi(testdatadir):
         bt_data = load_backtest_data(filename, strategy=strategy)
         assert isinstance(bt_data, DataFrame)
         assert set(bt_data.columns) == set(
-            BT_DATA_COLUMNS + ['close_timestamp', 'open_timestamp'])
+            BT_DATA_COLUMNS)
         assert len(bt_data) == 179
 
         # Test loading from string (must yield same result)

tests/optimize/test_backtesting.py

@@ -795,10 +795,27 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
          'is_open': [False, False],
          'enter_tag': [None, None],
          "is_short": [False, False],
+         'open_timestamp': [1517251200000, 1517283000000],
+         'close_timestamp': [1517265300000, 1517285400000],
+         'orders': [
+            [
+                {'amount': 0.00957442, 'safe_price': 0.104445, 'ft_order_side': 'buy',
+                 'order_filled_timestamp': 1517251200000, 'ft_is_entry': True},
+                {'amount': 0.00957442, 'safe_price': 0.10496853383458644, 'ft_order_side': 'sell',
+                 'order_filled_timestamp': 1517265300000, 'ft_is_entry': False}
+            ], [
+                {'amount': 0.0097064, 'safe_price': 0.10302485, 'ft_order_side': 'buy',
+                 'order_filled_timestamp': 1517283000000, 'ft_is_entry': True},
+                {'amount': 0.0097064, 'safe_price': 0.10354126528822055, 'ft_order_side': 'sell',
+                 'order_filled_timestamp': 1517285400000, 'ft_is_entry': False}
+            ]
+         ]
          })
     pd.testing.assert_frame_equal(results, expected)
+    assert 'orders' in results.columns
     data_pair = processed[pair]
     for _, t in results.iterrows():
+        assert len(t['orders']) == 2
         ln = data_pair.loc[data_pair["date"] == t["open_date"]]
         # Check open trade rate alignes to open rate
         assert ln is not None

tests/optimize/test_backtesting_adjust_position.py

@@ -70,9 +70,14 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
          'is_open': [False, False],
          'enter_tag': [None, None],
          'is_short': [False, False],
+         'open_timestamp': [1517251200000, 1517283000000],
+         'close_timestamp': [1517265300000, 1517285400000],
          })
-    pd.testing.assert_frame_equal(results, expected)
+    pd.testing.assert_frame_equal(results.drop(columns=['orders']), expected)
     data_pair = processed[pair]
+    assert len(results.iloc[0]['orders']) == 6
+    assert len(results.iloc[1]['orders']) == 2
+
     for _, t in results.iterrows():
         ln = data_pair.loc[data_pair["date"] == t["open_date"]]
         # Check open trade rate alignes to open rate