chore: import upstream snapshot with attribution

Algorithm.Python/FuturesChainsMultipleFullDataRegressionAlgorithm.py

@@ -0,0 +1,57 @@
+# 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>
+### Regression algorithm illustrating the usage of the <see cref="QCAlgorithm.FuturesChains(IEnumerable{Symbol}, bool)"/>
+### method to get multiple futures chains.
+### </summary>
+class FuturesChainsMultipleFullDataRegressionAlgorithm(QCAlgorithm):
+
+    def initialize(self):
+        self.set_start_date(2013, 10, 7)
+        self.set_end_date(2013, 10, 7)
+
+        es_future = self.add_future(Futures.Indices.SP_500_E_MINI).symbol
+        gc_future = self.add_future(Futures.Metals.GOLD).symbol
+
+        chains = self.futures_chains([es_future, gc_future], flatten=True)
+
+        self._es_contract = self.get_contract(chains, es_future)
+        self._gc_contract = self.get_contract(chains, gc_future)
+
+        self.add_future_contract(self._es_contract)
+        self.add_future_contract(self._gc_contract)
+
+    def get_contract(self, chains: FuturesChains, canonical: Symbol) -> Symbol:
+        df = chains.data_frame
+
+        # Index by the requested underlying, by getting all data with canonicals which underlying is the requested underlying symbol:
+        canonicals = df.index.get_level_values('canonical')
+        condition = [symbol for symbol in canonicals if symbol == canonical]
+        contracts = df.loc[condition]
+
+        # Get contracts expiring within 6 months, with the latest expiration date, and lowest price
+        contracts = contracts.loc[(df.expiry <= self.time + timedelta(days=180))]
+        contracts = contracts.sort_values(['expiry', 'lastprice'], ascending=[False, True])
+
+        return contracts.index[0][1]
+
+    def on_data(self, data):
+        # Do some trading with the selected contract for sample purposes
+        if not self.portfolio.invested:
+            self.set_holdings(self._es_contract, 0.25)
+            self.set_holdings(self._gc_contract, 0.25)
+        else:
+            self.liquidate()