Add explicit test for parallel trades

freqtrade/tests/optimize/test_backtesting.py

@@ -655,6 +655,77 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
     assert len(results.loc[results.open_at_end]) == 0
 
 
+def test_backtest_multi_pair(default_conf, fee, mocker):
+
+    def evaluate_result_multi(results, freq, max_open_trades):
+            # Find overlapping trades by expanding each trade once per period
+            # and then counting overlaps
+        dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
+                 for row in results[['open_time', 'close_time']].iterrows()]
+        deltas = [len(x) for x in dates]
+        dates = pd.Series(pd.concat(dates).values, name='date')
+        df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
+
+        df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
+        df2 = pd.concat([dates, df2], axis=1)
+        df2 = df2.set_index('date')
+        df_final = df2.resample(freq)[['pair']].count()
+        return df_final[df_final['pair'] > max_open_trades]
+
+    def _trend_alternate_hold(dataframe=None, metadata=None):
+        """
+        Buy every 8th candle - sell every other 8th -2 (hold on to pairs a bit)
+        """
+        multi = 8
+        dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
+        dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
+        if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
+            dataframe['buy'] = dataframe['buy'].shift(-4)
+            dataframe['sell'] = dataframe['sell'].shift(-4)
+        return dataframe
+
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
+    data = optimize.load_data(None, ticker_interval='5m', pairs=pairs)
+    data = trim_dictlist(data, -500)
+    # We need to enable sell-signal - otherwise it sells on ROI!!
+    default_conf['experimental'] = {"use_sell_signal": True}
+    default_conf['ticker_interval'] = '5m'
+
+    backtesting = Backtesting(default_conf)
+    backtesting.advise_buy = _trend_alternate_hold  # Override
+    backtesting.advise_sell = _trend_alternate_hold  # Override
+
+    data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
+    min_date, max_date = get_timeframe(data_processed)
+    backtest_conf = {
+        'stake_amount': default_conf['stake_amount'],
+        'processed': data_processed,
+        'max_open_trades': 3,
+        'position_stacking': False,
+        'start_date': min_date,
+        'end_date': max_date,
+    }
+
+    results = backtesting.backtest(backtest_conf)
+
+    # Make sure we have parallel trades
+    assert len(evaluate_result_multi(results, '5min', 2)) > 0
+    # make sure we don't have trades with more than configured max_open_trades
+    assert len(evaluate_result_multi(results, '5min', 3)) == 0
+
+    backtest_conf = {
+        'stake_amount': default_conf['stake_amount'],
+        'processed': data_processed,
+        'max_open_trades': 1,
+        'position_stacking': False,
+        'start_date': min_date,
+        'end_date': max_date,
+    }
+    results = backtesting.backtest(backtest_conf)
+    assert len(evaluate_result_multi(results, '5min', 1)) == 0
+
+
 def test_backtest_record(default_conf, fee, mocker):
     names = []
     records = []