Replace calls to load_tickerdata_file with DataHandler calls

freqtrade/data/history.py

@@ -8,7 +8,6 @@ Includes:
 
 import logging
 import operator
-from copy import deepcopy
 from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Tuple
@@ -18,8 +17,9 @@ from pandas import DataFrame
 
 from freqtrade import OperationalException, misc
 from freqtrade.configuration import TimeRange
-from freqtrade.data.converter import parse_ticker_dataframe, trades_to_ohlcv
+from freqtrade.data.converter import trades_to_ohlcv
-from freqtrade.exchange import Exchange, timeframe_to_minutes, timeframe_to_seconds
+from freqtrade.exchange import Exchange, timeframe_to_minutes
+from .datahandlers import get_datahandlerclass
 
 logger = logging.getLogger(__name__)
 
@@ -126,11 +126,12 @@ def _validate_pairdata(pair, pairdata, timerange: TimeRange):
 
 def load_pair_history(pair: str,
                       timeframe: str,
-                      datadir: Path,
+                      datadir: Path, *,
                       timerange: Optional[TimeRange] = None,
                       fill_up_missing: bool = True,
                       drop_incomplete: bool = True,
                       startup_candles: int = 0,
+                      data_format: str = 'json'
                       ) -> DataFrame:
     """
     Load cached ticker history for the given pair.
@@ -142,26 +143,18 @@ def load_pair_history(pair: str,
     :param fill_up_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
+    :param data_format: Format of the data
     :return: DataFrame with ohlcv data, or empty DataFrame
     """
-    timerange_startup = deepcopy(timerange)
+    HandlerClass = get_datahandlerclass(data_format)
-    if startup_candles > 0 and timerange_startup:
+    loader = HandlerClass(datadir)
-        timerange_startup.subtract_start(timeframe_to_seconds(timeframe) * startup_candles)
+    return loader.ohlcv_load(pair=pair,
-
+                             timeframe=timeframe,
-    pairdata = load_tickerdata_file(datadir, pair, timeframe, timerange=timerange_startup)
+                             timerange=timerange,
-
-    if pairdata:
-        if timerange_startup:
-            _validate_pairdata(pair, pairdata, timerange_startup)
-        return parse_ticker_dataframe(pairdata, timeframe, pair=pair,
                              fill_missing=fill_up_missing,
-                                      drop_incomplete=drop_incomplete)
+                             drop_incomplete=drop_incomplete,
-    else:
+                             startup_candles=startup_candles,
-        logger.warning(
-            f'No history data for pair: "{pair}", timeframe: {timeframe}. '
-            'Use `freqtrade download-data` to download the data'
                              )
-        return DataFrame()
 
 
 def load_data(datadir: Path,

tests/data/test_history.py

@@ -96,8 +96,9 @@ def test_load_data_1min_ticker(ticker_history, mocker, caplog, testdatadir) -> N
 
 
 def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) -> None:
-    ltfmock = mocker.patch('freqtrade.data.history.load_tickerdata_file',
+    ltfmock = mocker.patch(
-                           MagicMock(return_value=None))
+        'freqtrade.data.datahandlers.jsondatahandler.JsonDataHandler._ohlcv_load',
+        MagicMock(return_value=DataFrame()))
     timerange = TimeRange('date', None, 1510639620, 0)
     load_pair_history(pair='UNITTEST/BTC', timeframe='1m',
                       datadir=testdatadir, timerange=timerange,
@@ -361,8 +362,8 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
     # timedifference in 5 minutes
     td = ((end - start).total_seconds() // 60 // 5) + 1
     assert td != len(tickerdata['UNITTEST/BTC'])
-    # Shift endtime with +5 - as last candle is dropped (partial candle)
+    # This validation happens now after parsing to pandas.
-    end_real = arrow.get(tickerdata['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5)
+    end_real = arrow.get(tickerdata['UNITTEST/BTC'].iloc[-1, 0])
     assert log_has(f'Missing data at end for pair '
                    f'UNITTEST/BTC, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
                    caplog)