refactor: move index-handling into generator

freqtrade/optimize/backtesting.py

@@ -1440,7 +1440,12 @@ class Backtesting:
             current_time += self.timeframe_td
 
     def time_pair_generator(
-        self, start_date: datetime, end_date: datetime, increment: timedelta, pairs: list[str]
+        self,
+        start_date: datetime,
+        end_date: datetime,
+        increment: timedelta,
+        pairs: list[str],
+        data: dict[str, list[tuple]],
     ):
         """
         Backtest time and pair generator
@@ -1451,9 +1456,11 @@ class Backtesting:
         self.progress.init_step(
             BacktestState.BACKTEST, int((end_date - start_date) / self.timeframe_td)
         )
-        for current_time in self.time_generator(start_date, end_date):
+        # Indexes per pair, so some pairs are allowed to have a missing start.
-            # Loop for each time point.
+        indexes: dict = defaultdict(int)
 
+        for current_time in self.time_generator(start_date, end_date):
+            # Loop for each main candle.
             self.check_abort()
             # Reset open trade count for this candle
             # Critical to avoid exceeding max_open_trades in backtesting
@@ -1467,7 +1474,18 @@ class Backtesting:
             new_pairlist = list(dict.fromkeys([t.pair for t in LocalTrade.bt_trades_open] + pairs))
 
             for pair in new_pairlist:
-                yield current_time, pair
+                row_index = indexes[pair]
+                row = self.validate_row(data, pair, row_index, current_time)
+                if not row:
+                    continue
+
+                row_index += 1
+                indexes[pair] = row_index
+                is_last_row = current_time == end_date
+                self.dataprovider._set_dataframe_max_index(self.required_startup + row_index)
+                self.dataprovider._set_dataframe_max_date(current_time)
+
+                yield current_time, pair, row, is_last_row
 
             self.progress.increment()
 
@@ -1492,23 +1510,10 @@ class Backtesting:
         # (looping lists is a lot faster than pandas DataFrames)
         data: dict = self._get_ohlcv_as_lists(processed)
 
-        # Indexes per pair, so some pairs are allowed to have a missing start.
-        indexes: dict = defaultdict(int)
-
         # Loop timerange and get candle for each pair at that point in time
-        for current_time, pair in self.time_pair_generator(
+        for current_time, pair, row, is_last_row in self.time_pair_generator(
-            start_date, end_date, self.timeframe_td, list(data.keys())
+            start_date, end_date, self.timeframe_td, list(data.keys()), data
         ):
-            row_index = indexes[pair]
-            row = self.validate_row(data, pair, row_index, current_time)
-            if not row:
-                continue
-
-            row_index += 1
-            indexes[pair] = row_index
-            is_last_row = current_time == end_date
-            self.dataprovider._set_dataframe_max_index(self.required_startup + row_index)
-            self.dataprovider._set_dataframe_max_date(current_time)
             trade_dir: LongShort | None = self.check_for_trade_entry(row)
 
             pair_has_open_trades = len(LocalTrade.bt_trades_open_pp[pair]) > 0