Clean up no longer used method

freqtrade/data/converter.py

@@ -1,9 +1,7 @@
 """
 Functions to convert data from one format to another
 """
-import itertools
 import logging
-from operator import itemgetter
 from typing import Dict, List
 
 import numpy as np
@@ -196,17 +194,6 @@ def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
     return frame
 
 
-def trades_remove_duplicates(trades: List[List]) -> List[List]:
-    """
-    Removes duplicates from the trades list.
-    Uses itertools.groupby to avoid converting to pandas.
-    Tests show it as being pretty efficient on lists of 4M Lists.
-    :param trades: List of Lists with constants.DEFAULT_TRADES_COLUMNS as columns
-    :return: same format as above, but with duplicates removed
-    """
-    return [i for i, _ in itertools.groupby(sorted(trades, key=itemgetter(0, 1)))]
-
-
 def trades_df_remove_duplicates(trades: pd.DataFrame) -> pd.DataFrame:
     """
     Removes duplicates from the trades DataFrame.

tests/data/test_converter.py

@@ -11,8 +11,7 @@ from freqtrade.configuration.timerange import TimeRange
 from freqtrade.data.converter import (convert_ohlcv_format, convert_trades_format,
                                       ohlcv_fill_up_missing_data, ohlcv_to_dataframe,
                                       reduce_dataframe_footprint, trades_df_remove_duplicates,
-                                      trades_dict_to_list, trades_remove_duplicates,
+                                      trades_dict_to_list, trades_to_ohlcv, trim_dataframe)
-                                      trades_to_ohlcv, trim_dataframe)
 from freqtrade.data.history import (get_timerange, load_data, load_pair_history,
                                     validate_backtest_data)
 from freqtrade.data.history.idatahandler import IDataHandler
@@ -299,15 +298,6 @@ def test_trim_dataframe(testdatadir) -> None:
     assert all(data_modify.iloc[0] == data.iloc[25])
 
 
-def test_trades_remove_duplicates(trades_history):
-    trades_history1 = trades_history * 3
-    assert len(trades_history1) == len(trades_history) * 3
-    res = trades_remove_duplicates(trades_history1)
-    assert len(res) == len(trades_history)
-    for i, t in enumerate(res):
-        assert t == trades_history[i]
-
-
 def test_trades_df_remove_duplicates(trades_history_df):
     trades_history1 = pd.concat([trades_history_df, trades_history_df, trades_history_df]
                                 ).reset_index(drop=True)