remove code duplicates

freqtrade/tests/test_backtesting.py

@@ -1,13 +1,12 @@
 # pragma pylint: disable=missing-docstring
 
-import json
+
 import logging
 import os
 from typing import Tuple, Dict
 
 import arrow
 import pytest
-from arrow import Arrow
 from pandas import DataFrame
 from tabulate import tabulate
 
@@ -16,6 +15,7 @@ from freqtrade.analyze import parse_ticker_dataframe, populate_indicators, \
     populate_buy_trend, populate_sell_trend
 from freqtrade.exchange import Bittrex
 from freqtrade.main import min_roi_reached
+from freqtrade.misc import load_config
 from freqtrade.persistence import Trade
 from freqtrade.tests import load_backtesting_data
 
@@ -32,11 +32,6 @@ def format_results(results: DataFrame):
            )
 
 
-def print_pair_results(pair: str, results: DataFrame):
-    print('For currency {}:'.format(pair))
-    print(format_results(results[results.currency == pair]))
-
-
 def preprocess(backdata) -> Dict[str, DataFrame]:
     processed = {}
     for pair, pair_data in backdata.items():
@@ -44,7 +39,7 @@ def preprocess(backdata) -> Dict[str, DataFrame]:
     return processed
 
 
-def get_timeframe(data: Dict[str, Dict]) -> Tuple[Arrow, Arrow]:
+def get_timeframe(data: Dict[str, Dict]) -> Tuple[arrow.Arrow, arrow.Arrow]:
     """
     Get the maximum timeframe for the given backtest data
     :param data: dictionary with backtesting data
@@ -118,38 +113,40 @@ def backtest(backtest_conf, processed, mocker):
 @pytest.mark.skipif(not os.environ.get('BACKTEST'), reason="BACKTEST not set")
 def test_backtest(backtest_conf, mocker):
     print('')
+    exchange._API = Bittrex({'key': '', 'secret': ''})
 
-    config = None
+    # Load configuration file based on env variable
     conf_path = os.environ.get('BACKTEST_CONFIG')
     if conf_path:
         print('Using config: {} ...'.format(conf_path))
-        with open(conf_path, 'r') as conf_file:
-            config = json.load(conf_file)
+        config = load_config(conf_path)
+    else:
+        config = backtest_conf
 
+    # Parse ticker interval
     ticker_interval = int(os.environ.get('BACKTEST_TICKER_INTERVAL') or 5)
     print('Using ticker_interval: {} ...'.format(ticker_interval))
 
     data = {}
     if os.environ.get('BACKTEST_LIVE'):
         print('Downloading data for all pairs in whitelist ...')
-        exchange._API = Bittrex({'key': '', 'secret': ''})
         for pair in config['exchange']['pair_whitelist']:
             data[pair] = exchange.get_ticker_history(pair, ticker_interval)
     else:
         print('Using local backtesting data (ignoring whitelist in given config)...')
         data = load_backtesting_data(ticker_interval)
 
-    config = config or backtest_conf
-
     print('Using stake_currency: {} ...\nUsing stake_amount: {} ...'.format(
         config['stake_currency'], config['stake_amount']
     ))
 
+    # Print timeframe
     min_date, max_date = get_timeframe(data)
     print('Measuring data from {} up to {} ...'.format(
         min_date.isoformat(), max_date.isoformat()
     ))
 
+    # Execute backtest and print results
     results = backtest(config, preprocess(data), mocker)
     print('====================== BACKTESTING REPORT ======================================\n\n'
           'NOTE: This Report doesn\'t respect the limits of max_open_trades, \n'

freqtrade/tests/test_hyperopt.py

@@ -9,6 +9,8 @@ import pytest
 from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
 from pandas import DataFrame
 
+from freqtrade import exchange
+from freqtrade.exchange import Bittrex
 from freqtrade.tests.test_backtesting import backtest, format_results
 from freqtrade.tests.test_backtesting import preprocess
 from freqtrade.vendor.qtpylib.indicators import crossed_above
@@ -70,6 +72,7 @@ def buy_strategy_generator(params):
 def test_hyperopt(backtest_conf, backdata, mocker):
     mocked_buy_trend = mocker.patch('freqtrade.tests.test_backtesting.populate_buy_trend')
     processed = preprocess(backdata)
+    exchange._API = Bittrex({'key': '', 'secret': ''})
 
     def optimizer(params):
         mocked_buy_trend.side_effect = buy_strategy_generator(params)