Merge pull request #508 from gcarq/faster_backtesting

Faster backtesting

freqtrade/main.py

@@ -301,12 +301,13 @@ def min_roi_reached(trade: Trade, current_rate: float, current_time: datetime) -
         return True
 
     # Check if time matches and current rate is above threshold
-    time_diff = (current_time - trade.open_date).total_seconds() / 60
+    time_diff = (current_time.timestamp() - trade.open_date.timestamp()) / 60
-    for duration, threshold in sorted(strategy.minimal_roi.items()):
+    for duration_string, threshold in strategy.minimal_roi.items():
-        if time_diff > float(duration) and current_profit > threshold:
+        duration = float(duration_string)
+        if time_diff > duration and current_profit > threshold:
             return True
-
+        if time_diff < duration:
-    logger.debug('Threshold not reached. (cur_profit: %1.2f%%)', float(current_profit) * 100.0)
+            return False
     return False
 
 

freqtrade/optimize/backtesting.py

@@ -78,15 +78,13 @@ def get_sell_trade_entry(pair, row, buy_subset, ticker, trade_count_lock, args):
                   )
 
     # calculate win/lose forwards from buy point
-    sell_subset = ticker[ticker.index > row.Index][['close', 'sell']]
+    sell_subset = ticker[ticker.index > row.Index][['close', 'sell', 'buy']]
     for row2 in sell_subset.itertuples(index=True):
         if max_open_trades > 0:
             # Increase trade_count_lock for every iteration
             trade_count_lock[row2.Index] = trade_count_lock.get(row2.Index, 0) + 1
 
-        # Buy is on is in the buy_subset there is a row that matches the date
+        buy_signal = row2.buy
-        # of the sell event
-        buy_signal = (buy_subset.index == row2.Index).any()
         if(should_sell(trade, row2.close, row2.Index, buy_signal, row2.sell)):
             return row2, (pair,
                           trade.calc_profit_percent(rate=row2.close),

freqtrade/persistence.py

@@ -187,8 +187,8 @@ class Trade(_DECL_BASE):
         """
         open_trade_price = self.calc_open_trade_price()
         close_trade_price = self.calc_close_trade_price(
-            rate=Decimal(rate or self.close_rate),
+            rate=(rate or self.close_rate),
-            fee=Decimal(fee or self.fee)
+            fee=(fee or self.fee)
         )
         return float("{0:.8f}".format(close_trade_price - open_trade_price))
 
@@ -206,8 +206,8 @@ class Trade(_DECL_BASE):
 
         open_trade_price = self.calc_open_trade_price()
         close_trade_price = self.calc_close_trade_price(
-            rate=Decimal(rate or self.close_rate),
+            rate=(rate or self.close_rate),
-            fee=Decimal(fee or self.fee)
+            fee=(fee or self.fee)
         )
 
         return float("{0:.8f}".format((close_trade_price / open_trade_price) - 1))

freqtrade/strategy/strategy.py

@@ -7,6 +7,7 @@ import os
 import sys
 import logging
 import importlib
+from collections import OrderedDict
 
 from pandas import DataFrame
 from freqtrade.strategy.interface import IStrategy
@@ -69,7 +70,9 @@ class Strategy(object):
             )
 
         # Minimal ROI designed for the strategy
-        self.minimal_roi = self.custom_strategy.minimal_roi
+        self.minimal_roi = OrderedDict(sorted(
+            self.custom_strategy.minimal_roi.items(),
+            key=lambda tuple: float(tuple[0])))  # sort after converting to number
 
         # Optimal stoploss designed for the strategy
         self.stoploss = self.custom_strategy.stoploss

freqtrade/tests/test_persistence.py

@@ -271,10 +271,6 @@ def test_calc_profit(limit_buy_order, limit_sell_order):
     # Lower than open rate
     assert trade.calc_profit(rate=0.00000123, fee=0.003) == -0.00089092
 
-    # Only custom fee without sell order applied
-    with pytest.raises(TypeError):
-        trade.calc_profit(fee=0.003)
-
     # Test when we apply a Sell order. Sell higher than open rate @ 0.00001173
     trade.update(limit_sell_order)
     assert trade.calc_profit() == 0.00006217
@@ -299,10 +295,6 @@ def test_calc_profit_percent(limit_buy_order, limit_sell_order):
     # Get percent of profit with a custom rate (Lower than open rate)
     assert trade.calc_profit_percent(rate=0.00000123) == -0.88863827
 
-    # Only custom fee without sell order applied
-    with pytest.raises(TypeError):
-        trade.calc_profit_percent(fee=0.003)
-
     # Test when we apply a Sell order. Sell higher than open rate @ 0.00001173
     trade.update(limit_sell_order)
     assert trade.calc_profit_percent() == 0.06201057