Add conversion function from fetch_trades to list

freqtrade/constants.py

@@ -24,7 +24,9 @@ AVAILABLE_DATAHANDLERS = ['json', 'jsongz']
 DRY_RUN_WALLET = 1000
 MATH_CLOSE_PREC = 1e-14  # Precision used for float comparisons
 DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
-DEFAULT_TRADES_COLUMNS = ['timestamp', 'type', 'side', 'price', 'amount', 'cost']
+# Don't modify sequence of DEFAULT_TRADES_COLUMNS
+# it has wide consequences for stored trades files
+DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
 
 USERPATH_HYPEROPTS = 'hyperopts'
 USERPATH_STRATEGIES = 'strategies'

freqtrade/data/converter.py

@@ -3,12 +3,13 @@ Functions to convert data from one format to another
 """
 import logging
 from datetime import datetime, timezone
-from typing import Any, Dict
+from typing import Any, Dict, List
 
 import pandas as pd
 from pandas import DataFrame, to_datetime
 
-from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS
+
 
 logger = logging.getLogger(__name__)
 
@@ -154,7 +155,16 @@ def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
     return frame
 
 
-def trades_to_ohlcv(trades: list, timeframe: str) -> DataFrame:
+def trades_dict_to_list(trades: List[Dict]) -> List[List]:
+    """
+    Convert fetch_trades result into a List (to be more memory efficient).
+    :param trades: List of trades, as returned by ccxt.fetch_trades.
+    :return: List of Lists, with constants.DEFAULT_TRADES_COLUMNS as columns
+    """
+    return [[t[col] for col in DEFAULT_TRADES_COLUMNS]for t in trades]
+
+
+def trades_to_ohlcv(trades: List, timeframe: str) -> DataFrame:
     """
     Converts trades list to OHLCV list
     TODO: This should get a dedicated test