unnecessary libraries removed + arg help enriched

freqtrade/arguments.py

@@ -202,7 +202,8 @@ class Arguments(object):
         parser.add_argument(
             '--stoplosses',
             help='defines a range of stoploss against which edge will assess the strategy'
-                 'the format is "min,max,step" (without any space). example: --stoplosses=-0.01,-0.1,-0.001',
+                 'the format is "min,max,step" (without any space).'
+                 'example: --stoplosses=-0.01,-0.1,-0.001',
             type=str,
             dest='stoploss_range',
         )

freqtrade/optimize/edge.py

@@ -4,25 +4,14 @@
 This module contains the backtesting logic
 """
 import logging
-import operator
 from argparse import Namespace
-from copy import deepcopy
-from datetime import datetime, timedelta
-from pathlib import Path
-from typing import Any, Dict, List, NamedTuple, Optional, Tuple
-from freqtrade.edge import Edge
+from typing import Dict, Any
 from tabulate import tabulate
+from freqtrade.edge import Edge
 
-import freqtrade.optimize as optimize
-from freqtrade import DependencyException, constants
-from freqtrade.arguments import Arguments
 from freqtrade.configuration import Configuration
 from freqtrade.exchange import Exchange
-from freqtrade.misc import file_dump_json
-from freqtrade.persistence import Trade
-from freqtrade.strategy.interface import SellType
-from freqtrade.strategy.resolver import IStrategy, StrategyResolver
-import pdb
+from freqtrade.strategy.resolver import StrategyResolver
 
 logger = logging.getLogger(__name__)
 
@@ -56,7 +45,8 @@ class EdgeCli(object):
         floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', '.d')
         tabular_data = []
         headers = ['pair', 'stoploss', 'win rate', 'risk reward ratio',
-                   'required risk reward', 'expectancy', 'total number of trades', 'average duration (min)']
+                   'required risk reward', 'expectancy', 'total number of trades',
+                   'average duration (min)']
 
         for result in results.items():
             if result[1].nb_trades > 0: