Continuous Futures Refactor. Live Mappings (#6076)

* Continuous Futures Refactor. Live Mappings

- Adding support for live mappings. LiveTradingDataFeed will handle any
  symbol mapping at the configuration layer and resubscribe through the
  IDQH
- Refactoring continuous futures adding ContinuousFutureUniverse that
  will select the currently mapped security

* Minor fixes

- Remove addition of configurations in UniverseSelection step, leave
  resposability for universe.
- LiveTradingDF future unit test will only assert slice data for non
  internal feeds.
- ContinuousContractUniverse will respect internal option interest
  subscription

* Address review

Algorithm.Python/BasicTemplateContinuousFutureAlgorithm.py

@@ -0,0 +1,66 @@
+# 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 *
+
+### <summary>
+### Basic Continuous Futures Template Algorithm
+### </summary>
+class BasicTemplateContinuousFutureAlgorithm(QCAlgorithm):
+    '''Basic template algorithm simply initializes the date range and cash'''
+
+    def Initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+
+        self.SetStartDate(2013, 7, 1)
+        self.SetEndDate(2014, 1, 1)
+
+        self._continuousContract = self.AddFuture(Futures.Indices.SP500EMini,
+                                                  dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
+                                                  dataMappingMode = DataMappingMode.LastTradingDay,
+                                                  contractDepthOffset= 0)
+
+        self._fast = self.SMA(self._continuousContract.Symbol, 3, Resolution.Daily)
+        self._slow = self.SMA(self._continuousContract.Symbol, 10, Resolution.Daily)
+        self._currentContract = None
+
+    def OnData(self, data):
+        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+
+        Arguments:
+            data: Slice object keyed by symbol containing the stock data
+        '''
+        for changedEvent in data.SymbolChangedEvents.Values:
+            if changedEvent.Symbol == self._continuousContract.Symbol:
+                self.Log(f"SymbolChanged event: {changedEvent}")
+
+        if not self.Portfolio.Invested:
+            if self._fast.Current.Value > self._slow.Current.Value:
+                self._currentContract = self.Securities[self._continuousContract.Mapped]
+                self.Buy(self._currentContract.Symbol, 1)
+        elif self._fast.Current.Value < self._slow.Current.Value:
+            self.Liquidate()
+
+        if self._currentContract is not None and self._currentContract.Symbol != self._continuousContract.Mapped:
+            self.Log(f"{Time} - rolling position from {self._currentContract.Symbol} to {self._continuousContract.Mapped}")
+
+            currentPositionSize = self._currentContract.Holdings.Quantity
+            self.Liquidate(self._currentContract.Symbol)
+            self.Buy(self._continuousContract.Mapped, currentPositionSize)
+            self._currentContract = self.Securities[self._continuousContract.Mapped]
+
+    def OnOrderEvent(self, orderEvent):
+        self.Debug("Purchased Stock: {0}".format(orderEvent.Symbol))
+
+    def OnSecuritiesChanged(self, changes):
+        self.Debug(f"{self.Time}-{changes}")