add pandas-based converter-functions

freqtrade/data/converter.py

@@ -114,3 +114,23 @@ def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
                       keys=['b_sum', 'b_size', 'bids', 'asks', 'a_size', 'a_sum'])
     # logger.info('order book %s', frame )
     return frame
+
+
+def trades_to_ohlcv(trades, timeframe):
+    """
+    Converts trades list to ohlcv list
+    """
+    from freqtrade.exchange import timeframe_to_minutes
+    ticker_minutes = timeframe_to_minutes(timeframe)
+    df = pd.DataFrame(trades)
+    df['datetime'] = pd.to_datetime(df['datetime'])
+
+    df = df.set_index('datetime')
+    df_new = df['price'].resample(f'{ticker_minutes}min').ohlc()
+
+    df_new['volume'] = df['amount'].resample(f'{ticker_minutes}min').sum()
+    df_new['date'] = df_new.index.astype("int64") // 10 ** 6
+    # Drop 0 volume columns
+    df_new = df_new.dropna()
+    columns = ["date", "open", "high", "low", "close", "volume"]
+    return list(zip(*[df_new[x].values.tolist() for x in columns]))

freqtrade/data/history.py

@@ -17,7 +17,7 @@ from pandas import DataFrame
 
 from freqtrade import OperationalException, misc
 from freqtrade.configuration import TimeRange
-from freqtrade.data.converter import parse_ticker_dataframe
+from freqtrade.data.converter import parse_ticker_dataframe, trades_to_ohlcv
 from freqtrade.exchange import Exchange, timeframe_to_minutes
 
 logger = logging.getLogger(__name__)
@@ -398,7 +398,7 @@ def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir:
     return pairs_not_available
 
 
-def convert_trades_to_ohlcv(exchange: Exchange, pairs: List[str], timeframes: List[str],
+def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
                             datadir: Path, timerange: TimeRange, erase=False) -> None:
     """
     Convert stored trades data to ohlcv data
@@ -410,7 +410,7 @@ def convert_trades_to_ohlcv(exchange: Exchange, pairs: List[str], timeframes: Li
             if erase and ohlcv_file.exists():
                 logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
                 ohlcv_file.unlink()
-            ohlcv = exchange.build_ohlcv(trades, timeframe)
+            ohlcv = trades_to_ohlcv(trades, timeframe)
             # Store ohlcv
             store_tickerdata_file(datadir, pair, timeframe, data=ohlcv)
 

tests/data/test_history.py

@@ -24,7 +24,6 @@ from freqtrade.data.history import (_load_cached_data_for_updating,
                                     trim_tickerlist)
 from freqtrade.exchange import timeframe_to_minutes
 from freqtrade.misc import file_dump_json
-from freqtrade.resolvers.exchange_resolver import ExchangeResolver
 from freqtrade.strategy.default_strategy import DefaultStrategy
 from tests.conftest import (get_patched_exchange, log_has, log_has_re,
                             patch_exchange)
@@ -642,6 +641,7 @@ def test_download_trades_history(trades_history, mocker, default_conf, testdatad
 
 
 def test_convert_trades_to_ohlcv(mocker, default_conf, testdatadir, caplog):
+
     pair = 'XRP/ETH'
     file1 = testdatadir / 'XRP_ETH-1m.json'
     file5 = testdatadir / 'XRP_ETH-5m.json'
@@ -653,18 +653,15 @@ def test_convert_trades_to_ohlcv(mocker, default_conf, testdatadir, caplog):
                                          ticker_interval="5m",
                                          pair=pair)
 
-    _backup_file(file1)
+    _backup_file(file1, copy_file=True)
     _backup_file(file5)
 
-    exchange = ExchangeResolver('Bittrex', default_conf).exchange
     tr = TimeRange.parse_timerange('20191011-20191012')
-    # mocker.patch.object(Path, "exists", MagicMock(return_value=True))
-    # mocker.patch.object(Path, "unlink", MagicMock())
 
-    convert_trades_to_ohlcv(exchange, [pair], timeframes=['1m', '5m'],
+    convert_trades_to_ohlcv([pair], timeframes=['1m', '5m'],
                             datadir=testdatadir, timerange=tr, erase=True)
 
-    # assert log_has("Deleting existing data for XRP/ETH, interval 1m.", caplog)
+    assert log_has("Deleting existing data for pair XRP/ETH, interval 1m.", caplog)
     # Load new data
     df_1m = history.load_pair_history(datadir=testdatadir,
                                       ticker_interval="1m",