Trim dataframe, not tickerlist

freqtrade/data/datahandlers/idatahandler.py

@@ -37,7 +37,7 @@ class IDataHandler(ABC):
         :param pair: Pair to load data for
         :param timeframe: Ticker timeframe (e.g. "5m")
         :param timerange: Limit data to be loaded to this timerange
-        :param fill_up_missing: Fill missing values with "No action"-candles
+        :param fill_missing: Fill missing values with "No action"-candles
         :param drop_incomplete: Drop last candle assuming it may be incomplete.
         :param startup_candles: Additional candles to load at the start of the period
         :return: DataFrame with ohlcv data, or empty DataFrame
@@ -75,30 +75,3 @@ class IDataHandler(ABC):
         if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
             logger.warning('Missing data at end for pair %s, data ends at %s',
                            pair, arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
-
-    @staticmethod
-    def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
-        """
-        TODO: investigate if this is needed ... we can probably cover this in a dataframe
-        Trim tickerlist based on given timerange
-        """
-        if not tickerlist:
-            return tickerlist
-
-        start_index = 0
-        stop_index = len(tickerlist)
-
-        if timerange.starttype == 'date':
-            while (start_index < len(tickerlist) and
-                   tickerlist[start_index][0] < timerange.startts * 1000):
-                start_index += 1
-
-        if timerange.stoptype == 'date':
-            while (stop_index > 0 and
-                   tickerlist[stop_index-1][0] > timerange.stopts * 1000):
-                stop_index -= 1
-
-        if start_index > stop_index:
-            raise ValueError(f'The timerange [{timerange.startts},{timerange.stopts}] is incorrect')
-
-        return tickerlist[start_index:stop_index]

freqtrade/data/datahandlers/jsondatahandler.py

@@ -8,6 +8,7 @@ from pandas import DataFrame, read_json, to_datetime
 from freqtrade import misc
 from freqtrade.configuration import TimeRange
 from freqtrade.data.converter import clean_ohlcv_dataframe
+from freqtrade.data.history import trim_dataframe
 
 from .idatahandler import IDataHandler
 
@@ -54,9 +55,15 @@ class JsonDataHandler(IDataHandler):
                     drop_incomplete: bool = True,
                     ) -> DataFrame:
         """
-        Load data for one pair from disk.
+        Internal method used to load data for one pair from disk.
         Implements the loading and conversation to a Pandas dataframe.
-        :return: Dataframe
+        :param pair: Pair to load data for
+        :param timeframe: Ticker timeframe (e.g. "5m")
+        :param timerange: Limit data to be loaded to this timerange
+        :param fill_missing: Fill missing values with "No action"-candles
+        :param drop_incomplete: Drop last candle assuming it may be incomplete.
+        :param startup_candles: Additional candles to load at the start of the period
+        :return: DataFrame with ohlcv data, or empty DataFrame
         """
         filename = self._pair_data_filename(self._datadir, pair, timeframe)
         pairdata = read_json(filename, orient='values')
@@ -67,7 +74,7 @@ class JsonDataHandler(IDataHandler):
                                        infer_datetime_format=True)
 
         if timerange:
-            pairdata = IDataHandler.trim_tickerlist(pairdata, timerange)
+            pairdata = trim_dataframe(pairdata, timerange)
 
         return clean_ohlcv_dataframe(pairdata, timeframe,
                                      pair=pair,

freqtrade/utils.py

@@ -285,6 +285,7 @@ def convert_ohlcv_format(config: Dict[str, Any], convert_from: str, convert_to:
     for timeframe in timeframes:
         for pair in config['pairs']:
             data = src.ohlcv_load(pair=pair, timeframe=timeframe,
+                                  timerange=None,
                                   fill_missing=False,
                                   drop_incomplete=False,
                                   startup_candles=0)