Merge branch 'develop' into backtest-export

freqtrade/tests/optimize/test_backtesting.py

@@ -11,6 +11,13 @@ from freqtrade.optimize.backtesting import backtest, generate_text_table, get_ti
 import freqtrade.optimize.backtesting as backtesting
 
 
+def trim_dictlist(dl, num):
+    new = {}
+    for pair, pair_data in dl.items():
+        new[pair] = pair_data[num:]
+    return new
+
+
 def test_generate_text_table():
     results = pd.DataFrame(
         {
@@ -43,6 +50,7 @@ def test_backtest(default_conf, mocker):
     exchange._API = Bittrex({'key': '', 'secret': ''})
 
     data = optimize.load_data(None, ticker_interval=5, pairs=['BTC_ETH'])
+    data = trim_dictlist(data, -200)
     results = backtest({'stake_amount': default_conf['stake_amount'],
                         'processed': optimize.preprocess(data),
                         'max_open_trades': 10,
@@ -56,6 +64,7 @@ def test_backtest_1min_ticker_interval(default_conf, mocker):
 
     # Run a backtesting for an exiting 5min ticker_interval
     data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'])
+    data = trim_dictlist(data, -200)
     results = backtest({'stake_amount': default_conf['stake_amount'],
                         'processed': optimize.preprocess(data),
                         'max_open_trades': 1,
@@ -63,16 +72,9 @@ def test_backtest_1min_ticker_interval(default_conf, mocker):
     assert not results.empty
 
 
-def trim_dictlist(dl, num):
-    new = {}
-    for pair, pair_data in dl.items():
-        new[pair] = pair_data[num:]
-    return new
-
-
 def load_data_test(what):
-    data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'])
-    data = trim_dictlist(data, -100)
+    timerange = ((None, 'line'), None, -100)
+    data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'], timerange=timerange)
     pair = data['BTC_UNITEST']
     datalen = len(pair)
     # Depending on the what parameter we now adjust the
@@ -132,6 +134,7 @@ def simple_backtest(config, contour, num_results):
 def test_backtest2(default_conf, mocker):
     mocker.patch.dict('freqtrade.main._CONF', default_conf)
     data = optimize.load_data(None, ticker_interval=5, pairs=['BTC_ETH'])
+    data = trim_dictlist(data, -200)
     results = backtest({'stake_amount': default_conf['stake_amount'],
                         'processed': optimize.preprocess(data),
                         'max_open_trades': 10,
@@ -158,10 +161,10 @@ def test_backtest_pricecontours(default_conf, mocker):
         simple_backtest(default_conf, contour, numres)
 
 
-def mocked_load_data(datadir, pairs=[], ticker_interval=0, refresh_pairs=False):
-    tickerdata = optimize.load_tickerdata_file(datadir, 'BTC_UNITEST', 1)
+def mocked_load_data(datadir, pairs=[], ticker_interval=0, refresh_pairs=False, timerange=None):
+    tickerdata = optimize.load_tickerdata_file(datadir, 'BTC_UNITEST', 1, timerange=timerange)
     pairdata = {'BTC_UNITEST': tickerdata}
-    return trim_dictlist(pairdata, -100)
+    return pairdata
 
 
 def test_backtest_start(default_conf, mocker, caplog):
@@ -176,6 +179,7 @@ def test_backtest_start(default_conf, mocker, caplog):
     args.live = False
     args.datadir = None
     args.export = None
+    args.timerange = '-100'  # needed due to MagicMock malleability
     backtesting.start(args)
     # check the logs, that will contain the backtest result
     exists = ['Using max_open_trades: 1 ...',

freqtrade/tests/optimize/test_hyperopt.py

@@ -54,6 +54,7 @@ def create_trials(mocker):
 
 def test_start_calls_fmin(mocker):
     trials = create_trials(mocker)
+    mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
     mocker.patch('freqtrade.optimize.hyperopt.TRIALS', return_value=trials)
     mocker.patch('freqtrade.optimize.hyperopt.sorted',
                  return_value=trials.results)
@@ -61,7 +62,8 @@ def test_start_calls_fmin(mocker):
     mocker.patch('freqtrade.optimize.load_data')
     mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
 
-    args = mocker.Mock(epochs=1, config='config.json.example', mongodb=False)
+    args = mocker.Mock(epochs=1, config='config.json.example', mongodb=False,
+                       timerange=None)
     start(args)
 
     mock_fmin.assert_called_once()
@@ -70,11 +72,12 @@ def test_start_calls_fmin(mocker):
 def test_start_uses_mongotrials(mocker):
     mock_mongotrials = mocker.patch('freqtrade.optimize.hyperopt.MongoTrials',
                                     return_value=create_trials(mocker))
-    mocker.patch('freqtrade.optimize.preprocess')
+    mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
     mocker.patch('freqtrade.optimize.load_data')
     mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
 
-    args = mocker.Mock(epochs=1, config='config.json.example', mongodb=True)
+    args = mocker.Mock(epochs=1, config='config.json.example', mongodb=True,
+                       timerange=None)
     start(args)
 
     mock_mongotrials.assert_called_once()
@@ -107,6 +110,7 @@ def test_no_log_if_loss_does_not_improve(mocker):
 
 def test_fmin_best_results(mocker, caplog):
     fmin_result = {
+        "macd_below_zero": 0,
         "adx": 1,
         "adx-value": 15.0,
         "fastd": 1,
@@ -124,11 +128,12 @@ def test_fmin_best_results(mocker, caplog):
     }
 
     mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
-    mocker.patch('freqtrade.optimize.preprocess')
+    mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
     mocker.patch('freqtrade.optimize.load_data')
     mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
 
-    args = mocker.Mock(epochs=1, config='config.json.example')
+    args = mocker.Mock(epochs=1, config='config.json.example',
+                       timerange=None)
     start(args)
 
     exists = [
@@ -136,7 +141,7 @@ def test_fmin_best_results(mocker, caplog):
         '"adx": {\n        "enabled": true,\n        "value": 15.0\n    },',
         '"green_candle": {\n        "enabled": true\n    },',
         '"mfi": {\n        "enabled": false\n    },',
-        '"trigger": {\n        "type": "ao_cross_zero"\n    },',
+        '"trigger": {\n        "type": "faststoch10"\n    },',
         '"stoploss": -0.1',
     ]
 
@@ -146,11 +151,12 @@ def test_fmin_best_results(mocker, caplog):
 
 def test_fmin_throw_value_error(mocker, caplog):
     mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
-    mocker.patch('freqtrade.optimize.preprocess')
+    mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
     mocker.patch('freqtrade.optimize.load_data')
     mocker.patch('freqtrade.optimize.hyperopt.fmin', side_effect=ValueError())
 
-    args = mocker.Mock(epochs=1, config='config.json.example')
+    args = mocker.Mock(epochs=1, config='config.json.example',
+                       timerange=None)
     start(args)
 
     exists = [
@@ -184,7 +190,8 @@ def test_resuming_previous_hyperopt_results_succeeds(mocker):
                  return_value={})
     args = mocker.Mock(epochs=1,
                        config='config.json.example',
-                       mongodb=False)
+                       mongodb=False,
+                       timerange=None)
 
     start(args)
 

freqtrade/tests/optimize/test_optimize.py

@@ -174,3 +174,11 @@ def test_load_tickerdata_file():
     assert not load_tickerdata_file(None, 'BTC_UNITEST', 7)
     tickerdata = load_tickerdata_file(None, 'BTC_UNITEST', 1)
     assert _btc_unittest_length == len(tickerdata)
+
+
+def test_tickerdata_to_dataframe():
+    timerange = ((None, 'line'), None, -100)
+    tick = load_tickerdata_file(None, 'BTC_UNITEST', 1, timerange=timerange)
+    tickerlist = {'BTC_UNITEST': tick}
+    data = optimize.tickerdata_to_dataframe(tickerlist)
+    assert 100 == len(data['BTC_UNITEST'])