chore: import upstream snapshot with attribution

Tests/Research/RegressionScripts/Test_QuantBookHistory.py

@@ -0,0 +1,103 @@
+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from AlgorithmImports import *
+
+from custom_data import *
+
+class SecurityHistoryTest():
+    def __init__(self, start_date, security_type, symbol):
+        self.qb = QuantBook()
+        self.qb.SetStartDate(start_date)
+        self.symbol = self.qb.AddSecurity(security_type, symbol).Symbol
+        self.column = 'close'
+
+    def __str__(self):
+        return "{} on {}".format(self.symbol.ID, self.qb.StartDate)
+
+    def test_period_overload(self, period):
+        history = self.qb.History([self.symbol], period)
+        return history[self.column].unstack(level=0)
+
+    def test_daterange_overload(self, end):
+        start = end - timedelta(1)
+        history = self.qb.History([self.symbol], start, end)
+        return history[self.column].unstack(level=0)
+
+class OptionHistoryTest(SecurityHistoryTest):
+    def test_daterange_overload(self, end, start = None):
+        if start is None:
+            start = end - timedelta(1)
+        history = self.qb.GetOptionHistory(self.symbol, start, end)
+        return history.GetAllData()
+
+class FutureHistoryTest(SecurityHistoryTest):
+    def test_daterange_overload(self, end, start = None, maxFilter = 182):
+        if start is None:
+            start = end - timedelta(1)
+        self.qb.Securities[self.symbol].SetFilter(0, maxFilter) # default is 35 days
+        history = self.qb.GetFutureHistory(self.symbol, start, end)
+        return history.GetAllData()
+
+class FutureContractHistoryTest():
+    def __init__(self, start_date, security_type, symbol):
+        self.qb = QuantBook()
+        self.qb.SetStartDate(start_date)
+        self.symbol = symbol
+        self.column = 'close'
+
+    def test_daterange_overload(self, end):
+        start = end - timedelta(1)
+        history = self.qb.GetFutureHistory(self.symbol, start, end)
+        return history.GetAllData()
+
+class OptionContractHistoryTest(FutureContractHistoryTest):
+    def test_daterange_overload(self, end):
+        start = end - timedelta(1)
+        history = self.qb.GetOptionHistory(self.symbol, start, end)
+        return history.GetAllData()
+
+class CustomDataHistoryTest(SecurityHistoryTest):
+    def __init__(self, start_date, security_type, symbol):
+        self.qb = QuantBook()
+        self.qb.SetStartDate(start_date)
+
+        if security_type == 'Nifty':
+            type = Nifty
+            self.column = 'close'
+        elif security_type == 'CustomPythonData':
+            type = CustomPythonData
+            self.column = 'close'
+        else:
+            raise
+
+        self.symbol = self.qb.AddData(type, symbol, Resolution.Daily).Symbol
+
+class MultipleSecuritiesHistoryTest(SecurityHistoryTest):
+    def __init__(self, start_date, security_type, symbol):
+        self.qb = QuantBook()
+        self.qb.SetStartDate(start_date)
+        self.qb.AddEquity('SPY', Resolution.Daily)
+        self.qb.AddForex('EURUSD', Resolution.Daily)
+        self.qb.AddCrypto('BTCUSD', Resolution.Daily)
+
+    def test_period_overload(self, period):
+        history = self.qb.History(self.qb.Securities.Keys, period)
+        return history['close'].unstack(level=0)
+
+class FundamentalHistoryTest():
+    def __init__(self):
+        self.qb = QuantBook()
+
+    def getFundamentals(self, ticker, selector, start, end):
+        return self.qb.GetFundamental(ticker, selector, start, end)

Tests/Research/RegressionScripts/Test_QuantBookIndicator.py

@@ -0,0 +1,47 @@
+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from AlgorithmImports import *
+
+class IndicatorTest():
+    def __init__(self, start_date, security_type, symbol):
+        self.qb = QuantBook()
+        self.qb.SetStartDate(start_date)
+        self.symbol = self.qb.AddSecurity(security_type, symbol).Symbol
+
+    def __str__(self):
+        return "{} on {}".format(self.symbol.ID, self.qb.StartDate)
+
+    def test_bollinger_bands(self, symbol, start, end, resolution):
+        ind = BollingerBands(10, 2)
+        return self.qb.IndicatorHistory(ind, symbol, start, end, resolution)
+
+    def test_average_true_range(self, symbol, start, end, resolution):
+        ind = AverageTrueRange(14)
+        return self.qb.IndicatorHistory(ind, symbol, start, end, resolution)
+
+    def test_on_balance_volume(self, symbol, start, end, resolution):
+        ind = OnBalanceVolume(symbol)
+        return self.qb.IndicatorHistory(ind, symbol, start, end, resolution)
+    
+    def test_bollinger_bands_backwards_compatibility(self, symbol, start, end, resolution):
+        ind = BollingerBands(10, 2)
+        return self.qb.Indicator(ind, symbol, start, end, resolution)
+
+    def test_average_true_range_backwards_compatibility(self, symbol, start, end, resolution):
+        ind = AverageTrueRange(14)
+        return self.qb.Indicator(ind, symbol, start, end, resolution)
+
+    def test_on_balance_volume_backwards_compatibility(self, symbol, start, end, resolution):
+        ind = OnBalanceVolume(symbol)
+        return self.qb.Indicator(ind, symbol, start, end, resolution)

Tests/Research/RegressionScripts/custom_data.py

@@ -0,0 +1,70 @@
+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from AlgorithmImports import *
+
+import decimal
+
+class CustomPythonData(PythonData):
+    def get_source(self, config, date, is_live):
+        source = Globals.DataFolder + "/equity/usa/daily/ibm.zip"
+        return SubscriptionDataSource(source, SubscriptionTransportMedium.LocalFile, FileFormat.Csv)
+
+    def reader(self, config, line, date, is_live):
+        if line == None:
+            return None
+
+        customPythonData = CustomPythonData()
+        customPythonData.Symbol = config.Symbol
+
+        scaleFactor = 1 / 10000
+        csv = line.split(",")
+        customPythonData.Time = datetime.strptime(csv[0], '%Y%m%d %H:%M')
+        customPythonData["Open"] = float(csv[1]) * scaleFactor
+        customPythonData["High"] = float(csv[2]) * scaleFactor
+        customPythonData["Low"] = float(csv[3]) * scaleFactor
+        customPythonData["Close"] = float(csv[4]) * scaleFactor
+        customPythonData["Volume"] = float(csv[5])
+        return customPythonData
+
+class Nifty(PythonData):
+    '''NIFTY Custom Data Class'''
+    def get_source(self, config, date, is_live_mode):
+        return SubscriptionDataSource("https://www.dropbox.com/s/rsmg44jr6wexn2h/CNXNIFTY.csv?dl=1", SubscriptionTransportMedium.REMOTE_FILE)
+
+
+    def reader(self, config, line, date, is_live_mode):
+        if not (line.strip() and line[0].isdigit()): return None
+
+        # New Nifty object
+        index = Nifty()
+        index.symbol = config.symbol
+
+        try:
+            # Example File Format:
+            # Date,       Open       High        Low       Close     Volume      Turnover
+            # 2011-09-13  7792.9    7799.9     7722.65    7748.7    116534670    6107.78
+            data = line.split(',')
+            index.time = datetime.strptime(data[0], "%Y-%m-%d")
+            index.value = decimal.Decimal(data[4])
+            index["Open"] = float(data[1])
+            index["High"] = float(data[2])
+            index["Low"] = float(data[3])
+            index["Close"] = float(data[4])
+
+
+        except ValueError:
+                # Do nothing
+                return None
+
+        return index